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9 pages, 2510 KB

Open AccessProceeding Paper

Real-Time PHIL Validation of Inverter Grid-Support Functions for Low-Voltage Microgrids

by Maysam Soltanian, David Oyedokun, Pitambar Jankee and Hilary Chisepo

Eng. Proc. 2026, 140(1), 1; https://doi.org/10.3390/engproc2026140001 - 12 May 2026

Viewed by 686

The increased penetration of renewable energy resources with low inertia poses a risk to the frequency and voltage stability of modern power systems. Therefore, it is important to investigate grid-support functions from inverter-interfaced technologies. While conventional software simulations provide valuable insights into system [...] Read more.

The increased penetration of renewable energy resources with low inertia poses a risk to the frequency and voltage stability of modern power systems. Therefore, it is important to investigate grid-support functions from inverter-interfaced technologies. While conventional software simulations provide valuable insights into system behavior, they fail to capture physical interactions and hardware dynamics. This paper presents a power-hardware-in-the-loop (PHIL) platform used to evaluate inverter grid-support functions in a physical microgrid supplied by two synchronous generators connected to a load bus. The inverter is implemented in Simulink, executed on a real-time simulator and interfaced to the physical load bus through a power amplifier. The inverter controller uses droop control to inject power in response to frequency and voltage deviations. Experimental results demonstrate that the PHIL platform captures dynamic interactions between virtual and physical components. The paper concludes with practical guidelines and key considerations for the reliable application of PHIL in validating inverter control strategies in small-scale microgrids. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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8 pages, 1127 KB

Open AccessProceeding Paper

Co-Simulation of Power Flow, Fault Behaviour, and Protection Performance Using an Integrated MATLAB–DIgSILENT Framework on IEEE Benchmark Systems

by Abuyile Mpaka and Senthil Krishnamurthy

Eng. Proc. 2026, 140(1), 2; https://doi.org/10.3390/engproc2026140002 - 12 May 2026

Viewed by 254

Abstract

This study applies a combined load flow, short-circuit, and protection study of the IEEE four-bus and five-bus benchmarks as a comprehensive approach to power system modelling. A consistent per-unit base of 150 MVA and 132 kV is applied uniformly. The NR co-simulation approach [...] Read more.

This study applies a combined load flow, short-circuit, and protection study of the IEEE four-bus and five-bus benchmarks as a comprehensive approach to power system modelling. A consistent per-unit base of 150 MVA and 132 kV is applied uniformly. The NR co-simulation approach is used for load flow studies in both MATLAB_R2025b and DIgSILENT PowerFactory 2025. The simulation results indicate that voltages, power mismatches, and line flows are within the tolerance limits. Findings suggest that the NR method was highly implementable, yielding results in 2–3 iterations, and that the simulation results were comparable to those produced by commercial software, validating confidence in the power system modelling, load flow analysis, and protection study. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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9 pages, 1408 KB

Open AccessProceeding Paper

Technical Impacts of High PV Penetration in Low-Voltage Distribution Networks

by Oliver Dzobo and Prosper Mhlanga

Eng. Proc. 2026, 140(1), 3; https://doi.org/10.3390/engproc2026140003 - 12 May 2026

Viewed by 568

Abstract

The incorporation of Distributed Energy Resources (DERs), mainly photovoltaic (PV) systems, creates new challenges for distribution networks, even though these technologies provide significant benefits for decarbonization and grid flexibility. This paper evaluates the impact of high PV penetration on the low-voltage distribution network. [...] Read more.

The incorporation of Distributed Energy Resources (DERs), mainly photovoltaic (PV) systems, creates new challenges for distribution networks, even though these technologies provide significant benefits for decarbonization and grid flexibility. This paper evaluates the impact of high PV penetration on the low-voltage distribution network. The impact was tested on an IEEE 123-bus test network in 24 h simulations. Simulations to evaluate the impacts were conducted using the Open-Source Distribution System Simulator (OpenDSS) and MATLAB via the Component Object Model (COM) interface. The maximum hosting capacity of the different buses was evaluated and then enhanced using smart inverters (SI). The results obtained show improved hosting capacity using fixed lagging PF and Volt-Watt settings. The Volt-Var yielded the worst PV hosting capacity (HC). Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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9 pages, 1474 KB

Open AccessProceeding Paper

Multi-Objective Optimisation of Controllers for Frequency and Voltage Stability in Wind-Energy-Integrated Distribution Networks

by Kavita Behara and Ramesh Kumar Behara

Eng. Proc. 2026, 140(1), 4; https://doi.org/10.3390/engproc2026140004 - 12 May 2026

Viewed by 320

Abstract

High penetration of converter-based wind generation reduces system inertia. It poses challenges to frequency stability in modern distribution networks, particularly in doubly fed induction generator (DFIG)-based wind-energy-conversion systems (WECSs), where frequency regulation is coupled with point-of-common-coupling (PCC) voltage and power factor (PF) dynamics. [...] Read more.

High penetration of converter-based wind generation reduces system inertia. It poses challenges to frequency stability in modern distribution networks, particularly in doubly fed induction generator (DFIG)-based wind-energy-conversion systems (WECSs), where frequency regulation is coupled with point-of-common-coupling (PCC) voltage and power factor (PF) dynamics. This study presents a multi-objective comparative evaluation of proportional–integral (PI), proportional–integral–derivative (PID), fractional-order PID (FOPID), and adaptive neuro-fuzzy inference system (ANFIS) controllers for a DFIG-based WECS connected to a radial distribution feeder. Controller parameters are tuned using multi-objective optimisation, considering frequency deviation, overshoot, settling time, disturbance robustness, control smoothness, and computational cost, while maintaining PCC voltage and PF within acceptable limits. MATLAB/Simulink simulations are conducted under turbulent wind conditions, load variations, voltage disturbances, and measurement noise. The results indicate that conventional PI and PID controllers exhibit limited performance under low-inertia conditions, whereas FOPID improves damping and voltage/PF behaviour. ANFIS achieves the best overall performance, providing reduced frequency deviation, faster settling time (below 3 s), improved disturbance rejection, and significantly lower integral absolute error (up to ~90%) compared to PI control. These findings offer practical guidance for selecting and tuning controllers to enhance frequency-centric stability in wind-integrated distribution networks. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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10 pages, 1300 KB

Open AccessProceeding Paper

Performance Analysis and Resilience Assessment of a Hybrid PV–Wind Integrated 9-Bus Power System

by Senthil Krishnamurthy and Abuyile Mpaka

Eng. Proc. 2026, 140(1), 5; https://doi.org/10.3390/engproc2026140005 - 12 May 2026

Viewed by 589

Abstract

The addition of renewable energy sources (RES), including photovoltaic (PV) and wind generation technology, has introduced new challenges and opportunities for modern power systems. This paper examines the functionality and reliability of a hybrid PV–-wind-integrated 9-bus power system evaluated in DIgSILENT PowerFactory. The [...] Read more.

The addition of renewable energy sources (RES), including photovoltaic (PV) and wind generation technology, has introduced new challenges and opportunities for modern power systems. This paper examines the functionality and reliability of a hybrid PV–-wind-integrated 9-bus power system evaluated in DIgSILENT PowerFactory. The system has been designed with two solar PV plants, two offshore wind farms, multiple loads, and transformer interconnections, and aims to evaluate steady-state, dynamic, and contingency behavior. The system was evaluated using load-flow, quasi-dynamic, and RMS simulations to assess power balance, voltage stability, and fault recovery. The outcomes indicated convergence, balanced power flow, and system resilience under single-contingency conditions. This paper shows the effectiveness of the power system simulation tool for analyzing hybrid renewable power systems. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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8 pages, 2407 KB

Open AccessProceeding Paper

Anomaly Detection in Temporal Power Grid Using an LSTM Autoencoder Two-Phase Framework

by Ajibola Oyedeji and Peter Olukanmi

Eng. Proc. 2026, 140(1), 6; https://doi.org/10.3390/engproc2026140006 - 12 May 2026

Viewed by 566

Abstract

Detecting anomalies in high-dimensional temporal data in modern power grids is important for operational resilience. A long short-term memory (LSTM) autoencoder framework was introduced to detect anomalous windows. In the first phase, due to the lack of labeled anomalous data, the first 75% [...] Read more.

Detecting anomalies in high-dimensional temporal data in modern power grids is important for operational resilience. A long short-term memory (LSTM) autoencoder framework was introduced to detect anomalous windows. In the first phase, due to the lack of labeled anomalous data, the first 75% of the multi-feature nodal dataset was taken to represent normal operational patterns. From the normal, 75% was allocated for training and 25% for validation. In phase 2, statistical filtering was used to select the windows in the top 80% with the lowest reconstruction error calculated after training the phase 1 model. The LSTM autoencoder achieved a better reconstruction loss value of 0.000179 and identified 3062 anomalous windows in comparison to a standard autoencoder. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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11 pages, 2886 KB

Open AccessProceeding Paper

Optimized Shoot-Through Pulse Generation in High Voltage Boost Z-Source Inverters: A Performance-Based PWM Technique Comparison

by Sweta Kumari, Rajib Kumar Mandal and S. P. Daniel Chowdhury

Eng. Proc. 2026, 140(1), 7; https://doi.org/10.3390/engproc2026140007 - 12 May 2026

Viewed by 690

Abstract

Z-source inverters (ZSIs) provide single-stage power conversion with inherent voltage boost capability through shoot-through (ST) states achieved using specialized PWM methods. This study compares various ST PWM strategies, Simple Boost PWM, Maximum Boost PWM, Constant Boost Third Harmonic Injection PWM, and Space Vector [...] Read more.

Z-source inverters (ZSIs) provide single-stage power conversion with inherent voltage boost capability through shoot-through (ST) states achieved using specialized PWM methods. This study compares various ST PWM strategies, Simple Boost PWM, Maximum Boost PWM, Constant Boost Third Harmonic Injection PWM, and Space Vector PWM, for high-voltage boost ZSI (HVB-ZSI) applications. A MATLAB/Simulink 2024a model was developed to assess their performance in terms of output-voltage quality, THD, capacitor-voltage stress, switch stress, and inductor–current ripple. Results indicate that while all techniques enable ST operation effectively, their voltage stress and harmonic performance differ notably, guiding optimal PWM selection for advanced ZSI-based systems. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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10 pages, 2039 KB

Open AccessProceeding Paper

Integrating Higher-Order Thinking and Real-Time Simulation in Next-Generation Power Engineering Education

by Kavita Behara

Eng. Proc. 2026, 140(1), 8; https://doi.org/10.3390/engproc2026140008 - 12 May 2026

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Abstract

Power electronics is a cornerstone of modern electrical engineering, underpinning technologies from renewable energy systems to electric vehicles. Traditional lecture-based methods often emphasise rote learning and procedural skills but provide limited opportunities for higher-order thinking or experiential practice. To meet the needs of [...] Read more.

Power electronics is a cornerstone of modern electrical engineering, underpinning technologies from renewable energy systems to electric vehicles. Traditional lecture-based methods often emphasise rote learning and procedural skills but provide limited opportunities for higher-order thinking or experiential practice. To meet the needs of Generation Z learners and align with industry expectations, new pedagogical frameworks are required that combine cognitive rigour with authentic, technology-enhanced learning. This study introduces a Higher-Order Thinking Skills with Real-Time Simulation pedagogical framework to enhance learning outcomes in diploma-level power electronics. A quasi-experimental mixed-methods design was applied with 40 students divided into control and experimental groups. The control group received lectures, while the experimental group engaged with the HOTS–RTS framework across four topics: rectifiers, converters, inverters, and applications. Pre- and post-tests, Likert-scale surveys, reflections, and instructor observations provided data for both quantitative (t-tests, effect sizes) and qualitative thematic analysis. The experimental group achieved higher post-test gains (20.1 vs 9.5 points), with a large effect size (d = 1.9). Surveys revealed that 65 per cent of respondents rated RTS as highly effective, and Likert scores improved by 1 or more points in HOTS-related skills. Reflections emphasised clarity, confidence, and collaboration. HOTS–RTS effectively integrates cognitive rigour with real-time practice, aligning with STREAMS principles and equipping learners with next-generation industry competencies. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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8 pages, 810 KB

Open AccessProceeding Paper

Prosumer Clustering for Optimized Control and Peer-to-Peer Energy Trading in Solar-PV and Electric Vehicle Integrated Community Microgrids: A Comparative Analysis of K-Means and Spectral Methods

by Mukovhe Ratshitanga, Komla Agbenyo Folly and David Oyedokun

Eng. Proc. 2026, 140(1), 9; https://doi.org/10.3390/engproc2026140009 - 13 May 2026

Viewed by 574

Abstract

This study presents a comprehensive clustering analysis of residential prosumer profiles for optimizing control and peer-to-peer (P2P) energy trading in community renewable energy systems (CRES). Using data from 25 prosumer households equipped with rooftop solar photovoltaic (PV) systems and electric vehicle (EV) charging [...] Read more.

This study presents a comprehensive clustering analysis of residential prosumer profiles for optimizing control and peer-to-peer (P2P) energy trading in community renewable energy systems (CRES). Using data from 25 prosumer households equipped with rooftop solar photovoltaic (PV) systems and electric vehicle (EV) charging capabilities, this study implements and compares k-means and spectral clustering algorithms to identify optimal segmentation strategies for prosumer energy management. K-means clustering identifies seven practical prosumer categories with a silhouette coefficient of 0.17, while spectral clustering achieves superior mathematical separation with a silhouette coefficient of 0.275 in ten clusters, though producing six singleton outliers. The k-means solution demonstrates three primary prosumer categories: net producers, net consumers, and balanced profiles. Cluster size variation requires adaptive optimization, while singleton outliers need custom strategies. EV ownership impact consumption, so future proliferation demands dynamic clustering, and these findings will guide metaheuristic algorithms for energy trading and pricing. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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11 pages, 1656 KB

Open AccessProceeding Paper

Grid Stability Enhancement Using Machine Learning-Tuned Virtual Synchronous Generator

by Ayabonga Mjekula, Shongwe Thokozani and Peter Olukanmi

Eng. Proc. 2026, 140(1), 10; https://doi.org/10.3390/engproc2026140010 - 13 May 2026

Viewed by 653

Abstract

The increased penetration of renewable energy sources (RES) in the electrical grid has necessitated the concept of a Virtual Synchronous Generator (VSG) control which is used to make grid-connected power electronic converters behave as synchronous generators. While VSG controls are suitable for supporting [...] Read more.

The increased penetration of renewable energy sources (RES) in the electrical grid has necessitated the concept of a Virtual Synchronous Generator (VSG) control which is used to make grid-connected power electronic converters behave as synchronous generators. While VSG controls are suitable for supporting the inertia of a microgrid, their use leads to grid instability in the event of a disturbance. This research addresses this limitation by integrating a fully connected Feedforward Neural Network (FCNN) into a VSG control to dynamically adjust the damping coefficient and inertia constant in real time. This approach could enhance system stability by reducing frequency and active power oscillations during grid disturbances, particularly during partial load rejection. To evaluate the effectiveness of the proposed method, a supervised learning-based FCNN was trained on VSG damping behavior under various grid disturbances. The trained model was then implemented in a simulation environment to regulate the VSG parameters dynamically. Simulation results show the neural network-based approach reduces high overshoots at the point of disturbance in active power and frequency oscillations; however, the VSG signal settles faster after the grid disturbance. These findings highlight the potential of machine learning in enhancing the stability of VSG-based microgrids, offering a computationally efficient solution for improving transient response and power-sharing performance. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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7 pages, 1171 KB

Open AccessProceeding Paper

Comparative Analysis of Aggregate and Individual LV Energy Storage: Impacts on Grid Stability and Loading Using IEEE Standard Systems

by Franck Mushid and Mohamed Fayaz Khan

Eng. Proc. 2026, 140(1), 11; https://doi.org/10.3390/engproc2026140011 - 13 May 2026

Viewed by 440

Abstract

This paper presents a simulation-based comparative study on the deployment of aggregate versus individual battery energy storage systems (BESS) in low-voltage (LV) distribution networks, using IEEE standard test feeders. The analysis considers technical impacts on voltage regulation, energy losses, transformer loading, and feeder [...] Read more.

This paper presents a simulation-based comparative study on the deployment of aggregate versus individual battery energy storage systems (BESS) in low-voltage (LV) distribution networks, using IEEE standard test feeders. The analysis considers technical impacts on voltage regulation, energy losses, transformer loading, and feeder voltage stability under typical South African load profiles and time-of-use tariff conditions. Simulation results reveal that aggregate BESS configurations significantly outperform individual deployments in grid-support performance. The aggregate BESS reduced total feeder energy losses by up to 14%, improved voltage profiles across the network, and maintained transformer loading within safer operational margins. Furthermore, aggregate systems demonstrated superior energy arbitrage behavior and achieved lower values of the Feeder Voltage Stability Index (FVSI), indicating enhanced voltage resilience. While individual BESS units offer modularity and ease of deployment, their lack of coordination limits their effectiveness at the feeder level. This study provides valuable insights for utilities, policymakers, and researchers into optimal storage configurations that can strengthen distribution grid stability, reduce technical losses, and support renewable integration in developing energy markets such as South Africa. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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10 pages, 3746 KB

Open AccessProceeding Paper

Modeling and Simulation of a Smart Net Billing Electricity Meter for Small-Scale Embedded Generation

by Marvellous Ayomidele, Dwayne Jensen Reddy and Kabulo Loji

Eng. Proc. 2026, 140(1), 12; https://doi.org/10.3390/engproc2026140012 - 13 May 2026

Viewed by 595

Abstract

The existing studies on Small-Scale Embedded Generation (SSEG) have not addressed the net billing framework behavior that applies to different import and export tariff rates. This paper presents the simulation and modeling of a smart net billing electricity meter for SSEG in MATLAB/Simulink [...] Read more.

The existing studies on Small-Scale Embedded Generation (SSEG) have not addressed the net billing framework behavior that applies to different import and export tariff rates. This paper presents the simulation and modeling of a smart net billing electricity meter for SSEG in MATLAB/Simulink R2018b. The model integrates a PV array, MPPT controller, DC-DC boost converter, three-phase voltage source inverter (VSI), LC filter, synchronous generator, and a bidirectional energy meter. A smart billing subsystem was developed to compute real-time energy costs using differential tariff rates consistent with South African utility policies. Simulations were conducted under fixed irradiance, with electrical performance evaluated over a short interval and billing dynamics assessed over an extended period. Results show stable PV generation, proper inverter synchronization with the utility grid, and accurate tracking of imported and exported energy. The system effectively calculates the net bill, demonstrating transparency, automation, and economic accuracy in line with policy-driven net billing frameworks. These outcomes validate the technical feasibility and practical relevance of smart net billing meters in modern grid-connected renewable energy applications. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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10 pages, 553 KB

Open AccessProceeding Paper

Software-Defined PolyGlot Power System Architecture Template for Non-Terrestrial Data Centers

by Ayodele A. Periola

Eng. Proc. 2026, 140(1), 13; https://doi.org/10.3390/engproc2026140013 - 13 May 2026

Viewed by 455

Abstract

Non-terrestrial data centers (NTDCs) should be capable of functioning in harsh environments and are located in space, the stratosphere, and underwater. They require power to execute data processing and algorithm execution. NTDCs need power systems that are cyber-physical systems. These systems use data [...] Read more.

Non-terrestrial data centers (NTDCs) should be capable of functioning in harsh environments and are located in space, the stratosphere, and underwater. They require power to execute data processing and algorithm execution. NTDCs need power systems that are cyber-physical systems. These systems use data and programmed systems (using different programming languages), i.e., software enabling power system functionality, to realize the desired integration and functionality. Different programming languages have varying performance capabilities and integration support to enable the interworking of multiple entities in the software aspects of open NTDC power systems. Such open NTDC power systems support different operational objectives. It is important to achieve a high number of successful component integrations for system functioning. The proposed system considers the choice of the programming language, enabling multi-interface communications as a selectable and configuration parameter in a polyglot multi-language NTDC power system computing paradigm. Evaluation shows that the proposed approach increases the number of successful integrations between power system software-defined entities by 20.2%, with a maximum of 60%. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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10 pages, 929 KB

Open AccessProceeding Paper

Hyper-Scale Space Data Centers–Power System Mechanisms to Achieve Improved Communication Outcomes

by Ayodele A. Periola, Joyce B. Mfika and Likhanyise Jwente

Eng. Proc. 2026, 140(1), 14; https://doi.org/10.3390/engproc2026140014 - 13 May 2026

Viewed by 575

Abstract

The high environmental toll of terrestrial data centers described by their high land and water footprint has motivated new data center solutions. An important solution that has emerged from this motive is the space-based data center (SBDC). An SBDC is a space asset [...] Read more.

The high environmental toll of terrestrial data centers described by their high land and water footprint has motivated new data center solutions. An important solution that has emerged from this motive is the space-based data center (SBDC). An SBDC is a space asset capable of processing the increased amount of data arising from space-based applications. Being in a non-geostationary earth orbit, it is important for important high-capacity hyper-scale space-based data centers to be capable of transmitting data to ground stations where valuable applications are hosted. This challenge necessitates addressing the maximum use of communication windows for non-geostationary space assets requiring further research attention. The research presented proposes an algorithm enabling the scheduling of power for optimal communication window functioning, to achieve high quality of service and make the best use of a communication window opportunity. This is achieved by increasing the power available to the SBDC communication subsystem. The evaluation shows that using the proposed approach enhances communication window utilization readiness and the communication window by 82.8% and 55.9% on average, respectively. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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11 pages, 855 KB

Open AccessProceeding Paper

Mountain Data Centers—Design, Application and Analysis

by Ayodele A. Periola and Lateef A. Akinyemi

Eng. Proc. 2026, 140(1), 15; https://doi.org/10.3390/engproc2026140015 - 13 May 2026

Viewed by 557

Abstract

Future networks should provide access to cloud-based content to subscribers in mountainous region. This research proposes a network architecture incorporating mountain data centers that provide content access via caching in a capital-constrained context. It also discusses the aspects of the power system supporting [...] Read more.

Future networks should provide access to cloud-based content to subscribers in mountainous region. This research proposes a network architecture incorporating mountain data centers that provide content access via caching in a capital-constrained context. It also discusses the aspects of the power system supporting the network architecture. The use of content caching reduces content access latency. The research recognizes that mountains can host computing platforms while ensuring low to moderate operational costs. Using the proposed approach also reduces the number of network hops and associated power consumption by (26–37)% and (17–25)% on average, respectively. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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9 pages, 1218 KB

Open AccessProceeding Paper

Renewable Energy as a Driver for Sustainable Rural Electrification and Energy Management

by Mulizi David Ruhaya and Senthil Krishnamurthy

Eng. Proc. 2026, 140(1), 16; https://doi.org/10.3390/engproc2026140016 - 12 May 2026

Viewed by 483

Abstract

The smart hybrid microgrid energy management system is based on photovoltaic (PV) arrays, wind turbines, battery energy storage, and diesel generators, supplying clean, stable, and cost-effective energy to rural villages. Predictive control, load-demand/load-following, and SOC optimization enable supply and demand adjustments for stable [...] Read more.

The smart hybrid microgrid energy management system is based on photovoltaic (PV) arrays, wind turbines, battery energy storage, and diesel generators, supplying clean, stable, and cost-effective energy to rural villages. Predictive control, load-demand/load-following, and SOC optimization enable supply and demand adjustments for stable operation and reduced emissions/diesel consumption. MATLAB 2024a simulations support the concept that this system operates more sustainably, reliably, and efficiently when a compromise is made between conventional and renewable sources. By addressing the reliability issue of renewable energy’s intermittent production, such hybrid systems can provide the consistent power necessary for economic productivity and health/education in rural villages. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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9 pages, 1283 KB

Open AccessProceeding Paper

A Comprehensive Benchmarking of Evolutionary, Swarm-Intelligence, and Surrogate-Assisted Optimization for Residual Demand Forecasting in South African Microgrids

by Pfano Nemakonde, Fhulufhelo Nemangwele, Mukovhe Ratshitanga and Komla Agbenyo Folly

Eng. Proc. 2026, 140(1), 17; https://doi.org/10.3390/engproc2026140017 - 14 May 2026

Viewed by 341

Abstract

Accurate residual demand forecasting (RDF) is essential for stable peer-to-peer energy trading in developing economies. This study benchmarks three hyperparameter optimization paradigms, HEBO, PSO, and GP-BO, applied to XGBoost (2.1.4) forecasting using seven-fold TimeSeriesSplit validation on South African hourly grid data. Results demonstrate [...] Read more.

Accurate residual demand forecasting (RDF) is essential for stable peer-to-peer energy trading in developing economies. This study benchmarks three hyperparameter optimization paradigms, HEBO, PSO, and GP-BO, applied to XGBoost (2.1.4) forecasting using seven-fold TimeSeriesSplit validation on South African hourly grid data. Results demonstrate a fundamental trade-off between accuracy and efficiency: PSO achieves superior accuracy (0.47% MAPE) at the cost of substantial computation (23.4 h), while GP-BO offers revolutionary speed (19 min) with acceptable accuracy trade-offs. HEBO provides balanced performance with stable convergence. Crucially, we identify a “data–optimizer coupling” effect where optimal scaling methods are algorithm-dependent. These findings provide context-specific deployment strategies for microgrid operators addressing energy trilemma challenges. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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8 pages, 606 KB

Open AccessProceeding Paper

Energy Performance Assessment and Baseline Modelling for a Quarry in Gauteng Province, South Africa

by Tshilidzi Ramunenyiwa and Komla A. Folly

Eng. Proc. 2026, 140(1), 18; https://doi.org/10.3390/engproc2026140018 - 14 May 2026

Viewed by 549

Abstract

This paper presents an energy performance assessment and the development of an energy consumption baseline model for a quarry located in Gauteng Province, South Africa. Using 24 months of historical electricity consumption and production data, the energy use intensity (EUI) was calculated to [...] Read more.

This paper presents an energy performance assessment and the development of an energy consumption baseline model for a quarry located in Gauteng Province, South Africa. Using 24 months of historical electricity consumption and production data, the energy use intensity (EUI) was calculated to benchmark the quarry against similar international operations. The results show that the quarry performs competitively, ranking third among seven comparable sites despite having no energy conservation measures (ECMs) in place. A linear regression model was developed to predict energy consumption based on tons produced, yielding a strong correlation (R² = 0.92) and statistically significant parameters. Model validation metrics—including a CVRMSE of 9%, Durbin–Watson value of 2.818, and negligible Net Determination Bias—indicate a reliable and accurate baseline suitable for future energy savings verification. The study highlights opportunities to further improve performance through energy management programmes and operational changes. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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7 pages, 3014 KB

Open AccessProceeding Paper

Design, Modelling and Simulation of Fault Behavior in Hybrid Multiterminal HVDC Collection Systems

by Olumoroti Ikotun, Evans Eshiemogie Ojo and Musasa Kabeya

Eng. Proc. 2026, 140(1), 19; https://doi.org/10.3390/engproc2026140019 - 14 May 2026

Viewed by 475

Abstract

Previous studies showed that at the inverter end, the AC voltage will experience a slight increase, while further observations revealed an increase in DC current. Other findings indicated that the AC voltage at the rectifier side will experience a decrease, while both AC [...] Read more.

Previous studies showed that at the inverter end, the AC voltage will experience a slight increase, while further observations revealed an increase in DC current. Other findings indicated that the AC voltage at the rectifier side will experience a decrease, while both AC voltage and DC current will increase. This paper presents a hybrid multiterminal HVDC system, which was modelled and implemented using Matlab/Simulink software 2018b to investigate fault behaviors, focusing on DC line-to-ground faults and their impact on the overall system. Calculations were performed at the input of the Graetz bridge rectifier, the capacitor filter of the DC transmission line, and the three-phase LCL filter located at the inverter end. Results indicated that, at the rectifier end, the grid voltage will increase while the grid current will decrease with non-standard waveforms. It noted that at the inverter end, the AC voltage will decrease along with grid currents. In the DC transmission line, the DC current will decrease to near zero. Findings represent the contribution of the behaviors observed at both the rectifier and inverter ends of the grids during fault scenarios, providing a more profound understanding of how multiterminal HVDC systems behave under threat. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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8 pages, 682 KB

Open AccessProceeding Paper

Optimal Sizing and Placement for Campus-Wide PV System Without Battery Energy Storage System

by Yamkela Nompetsheni and Mukovhe Ratshitanga

Eng. Proc. 2026, 140(1), 20; https://doi.org/10.3390/engproc2026140020 - 15 May 2026

Viewed by 593

Abstract

As global energy demands rise and concerns about environmental sustainability intensify, renewable energy sources like solar photovoltaic (PV) systems have gained significant attention. An integrated approach is proposed, leveraging spatial analysis using Helioscope, a 3D solar design tool, incorporated with Geographic Information System [...] Read more.

As global energy demands rise and concerns about environmental sustainability intensify, renewable energy sources like solar photovoltaic (PV) systems have gained significant attention. An integrated approach is proposed, leveraging spatial analysis using Helioscope, a 3D solar design tool, incorporated with Geographic Information System (GIS) data. This study conducted a spatial analysis of Cape Peninsula University of Technology (CPUT) Bellville campus’s potential for renewable energy, and the results are promising. The research indicated that the campus has enough rooftop space to optimally place solar panels with a capacity of 7.8 megawatts, which is more than the campus’s total energy needs of 6.3 megawatts. This study identified 13,249 modules that can be optimally placed to achieve this. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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9 pages, 3016 KB

Open AccessProceeding Paper

Performance Evaluation of NFPP-Type Sodium-Ion Batteries

by Inus Grobler, Hanif Banderker, Reesen Govindsamy and Gideon van der Kolf

Eng. Proc. 2026, 140(1), 21; https://doi.org/10.3390/engproc2026140021 - 15 May 2026

Viewed by 1472

Abstract

This paper presents a performance evaluation of next-generation sodium-ion cells employing Sodium Iron Pyrophosphate (NFPP) chemistry, which is now commercially available. Building on prior research into early-generation SiB technologies, the study investigates NFPP cells under varied operating conditions, including high and low temperatures, [...] Read more.

This paper presents a performance evaluation of next-generation sodium-ion cells employing Sodium Iron Pyrophosphate (NFPP) chemistry, which is now commercially available. Building on prior research into early-generation SiB technologies, the study investigates NFPP cells under varied operating conditions, including high and low temperatures, extreme C-rate discharge, and zero-volt storage. Results indicate that NFPP cells deliver exceptional high-power capability, sustaining continuous discharge rates up to 30C without degradation, and they exhibit strong thermal stability at elevated temperatures. While safety features such as zero-volt tolerance remain intact, low-temperature operation continues to pose challenges, particularly for charging, with irreversible capacity loss observed when exceeding manufacturer specifications. Despite a relatively low energy density (~79.75 Wh/kg), NFPP cells demonstrate significant potential for high-power applications requiring reliability and safety in harsh environments. These findings position NFPP chemistry as a critical step toward advancing sodium-ion technology for specialised energy storage solutions. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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8 pages, 1080 KB

Open AccessProceeding Paper

Aggregation of Small-Scale Flexibility Providers for System Services Provision

by Haltor Mataifa, Ntanganedzeni Tshinavhe, Senthil Krishnamurthy, Mukovhe Ratshitanga and Marco Adonis

Eng. Proc. 2026, 140(1), 22; https://doi.org/10.3390/engproc2026140022 - 15 May 2026

Viewed by 271

Abstract

Electric power distribution systems have been undergoing a transformation that can be attributed to factors such as the deregulation of the electric power supply industry, growing public concern over energy security and the environmental impact of energy generation and utilization, and technological advancements [...] Read more.

Electric power distribution systems have been undergoing a transformation that can be attributed to factors such as the deregulation of the electric power supply industry, growing public concern over energy security and the environmental impact of energy generation and utilization, and technological advancements that have given impetus to concerted efforts to modernize the power grid in the framework of smart grid initiatives. The traditionally passive distribution network is increasingly becoming active due to the steady increase in the amount of distributed energy resources being integrated into the network. This has, in turn, given rise to a higher need for flexibility resources that can be used to handle the increased uncertainty caused by stochastic and intermittent distributed resources, such as variable renewable power generation. The provision of demand-side flexibility has largely been the purview of large industrial and commercial energy consumers. This article discusses the role that the aggregator can play in facilitating the provision of flexibility resources by small-scale consumers and prosumers and presents a case study on small-scale renewable generation and residential demand forecasting, which form an integral part of demand flexibility aggregation. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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10 pages, 5124 KB

Open AccessProceeding Paper

Predictive Maintenance of High-Voltage Railway Equipment Using Machine Learning: A Case Study on Pantograph and Auxiliary Converter Units in a 3 kV DC Rail System

by Mavhungu Mathalise, Elisha Markus and Malusi Sibiya

Eng. Proc. 2026, 140(1), 23; https://doi.org/10.3390/engproc2026140023 - 18 May 2026

Viewed by 401

Abstract

In 3 kV DC systems, the pantograph–catenary interface and auxiliary converter unit (ACU) are among the critical high-voltage subsystems, where electrical transients and thermal overload conditions frequently lead to service disruptions. This paper presents a case study on the application of machine-learning-based predictive [...] Read more.

In 3 kV DC systems, the pantograph–catenary interface and auxiliary converter unit (ACU) are among the critical high-voltage subsystems, where electrical transients and thermal overload conditions frequently lead to service disruptions. This paper presents a case study on the application of machine-learning-based predictive maintenance to a 3 kV DC electric train, with a specific focus on the pantograph and ACU. A 2-year period of operational data collected from a passenger rail fleet was analysed using a hybrid data sampling strategy to capture both operational conditions and events associated with failures. Logistic Regression (LR), and Random Forest (RF) were trained and evaluated using standard performance metrics. The RF model achieved superior predictive performance, with an accuracy of approximately 93%, a precision of 0.91, a recall of 0.88, and an F1-score of 0.89, outperforming the baseline across all metrics. The analyses demonstrated that anomalies in electrical arcing, line voltage, and ACU current and temperature frequently preceded recorded fault events, confirming that failures arise from subsystems interactions and that it is critical for such parameters to be monitored. The results demonstrate the technical feasibility and practical value of integrating machine learning into EMU maintenance practice, enabling earlier detection of degradation, more targeted interventions, and a transition towards condition-based maintenance. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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9 pages, 1988 KB

Open AccessProceeding Paper

AI-Enhanced Energy Management for Islanded Microgrids: A Comparative Study with Rule-Based Control

by Siphamandla Magobhiyane, Tlotlollo Sidwell Hlalele and Mbuyu Sumbwanyambe

Eng. Proc. 2026, 140(1), 24; https://doi.org/10.3390/engproc2026140024 - 15 May 2026

Viewed by 568

Abstract

Islanded microgrids face considerable operational difficulties because of the inconsistency of renewable energy sources and ongoing dependence on diesel power. This study offers a comparative assessment of a traditional rule-based energy management system versus an AI-augmented energy management system for a hybrid island [...] Read more.

Islanded microgrids face considerable operational difficulties because of the inconsistency of renewable energy sources and ongoing dependence on diesel power. This study offers a comparative assessment of a traditional rule-based energy management system versus an AI-augmented energy management system for a hybrid island microgrid that includes photovoltaic generation, wind generation, battery energy storage, and diesel generator. The suggested AI-driven controller incorporates short-term predictions and heuristic scheduling to enhance dispatch choices. Simulations using MATLAB and Simulink Ver-sion 25.2.0.2998904 (R2025b) over a 24 h period show enhanced management of battery state-of-charge, decreased operation of the diesel generator, and greater use of renewable energy. The findings show a decrease in fuel usage and carbon dioxide emissions of around 63% in comparison to the baseline rule-based approach. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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11 pages, 1018 KB

Open AccessProceeding Paper

The Effect of Pitch-Bearing Fatigue on Wind Turbine Electrical Traces

by Tumelo Molato, Goodness Ayanda Zamile Dlamini and Pitshou Ntambu Bokoro

Eng. Proc. 2026, 140(1), 25; https://doi.org/10.3390/engproc2026140025 - 18 May 2026

Viewed by 421

Abstract

This paper investigates whether event-level pitch-bearing fatigue damage can be estimated directly from turbine measurements, and whether these mechanical damage metrics leave measurable fingerprints in the generator DC-link voltage and current. To achieve this, a case study was performed using SCADA and structural [...] Read more.

This paper investigates whether event-level pitch-bearing fatigue damage can be estimated directly from turbine measurements, and whether these mechanical damage metrics leave measurable fingerprints in the generator DC-link voltage and current. To achieve this, a case study was performed using SCADA and structural load data from the 45 kW Chalmers (Björkö) research turbine. This data was segmented into 223 park-run-park pitch events. For each event, blade-root flapwise and edgewise bending moments were converted into radial and axial loads at the pitch bearing; an equivalent dynamic bearing load

P_{eq} (t)

was reconstructed using SKF and DG03 formulations; and rainflow counting with an S–N curve and Palmgren–Miner’s rule was used to compute event-level damage indices compatible with the International Standard Organization basic rating life concepts. In parallel, DC-link voltage and current were summarized into time-domain features, combined with operating-condition descriptors, and clustered using PCA-based k-means. The resulting clusters captured distinct electrical regimes that, across several event batches, corresponded to different levels of accumulated fatigue damage: regimes with sustained high DC-link voltage and longer duration tended to exhibit higher mean damage indices than lower, steadier DC regimes, indicating an electromechanical link. The results show that physics-based lifetime estimation and unsupervised analysis of existing electrical traces can be combined into a hybrid workflow for pitch-bearing condition assessment without additional sensors. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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9 pages, 2366 KB

Open AccessProceeding Paper

Liquid-Based Semiconductor Rheostat for DC Arc Fault Suppression

by Kagiso Ndlhovu, Temosho Mathabatha and James Braid

Eng. Proc. 2026, 140(1), 26; https://doi.org/10.3390/engproc2026140026 - 20 May 2026

Viewed by 482

Abstract

Validation testing of a liquid-based rheostat confirmed its efficacy in mitigating DC arc faults in photovoltaic systems by exceeding critical resistance and voltage–current thresholds. Experimental characterization of electrode immersion depth, separation, and electrolyte concentration identified zinc-galvanized steel to copper in NaHCO₃ as [...] Read more.

Validation testing of a liquid-based rheostat confirmed its efficacy in mitigating DC arc faults in photovoltaic systems by exceeding critical resistance and voltage–current thresholds. Experimental characterization of electrode immersion depth, separation, and electrolyte concentration identified zinc-galvanized steel to copper in NaHCO₃ as the optimal configuration, achieving a dynamic range factor of 39.10. Further analysis prioritized high minimum resistance (R_MIN) for arc extinction, favouring stable electrode pairs like copper to brass with a 10 g solute concentration. A unified piecewise resistance model validated arc suppression through a load line analysis, demonstrating non-intersection with the Mayr extinction boundary. These findings support scaling the device to a 5 kW, 250 V_DC rating for electric geysers, utilizing 200 mm × 50 mm electrodes and increased electrolyte volume to ensure operational stability. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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10 pages, 1075 KB

Open AccessProceeding Paper

Analysis of Conceptualized Space-Based Solar Power Plant

by Londiwe Mokoena, Namhla Faith Mtukushe and Evans Eshiemogie Ojo

Eng. Proc. 2026, 140(1), 27; https://doi.org/10.3390/engproc2026140027 - 19 May 2026

Viewed by 511

Abstract

Renewable energy sources such as wind, solar, and hydro have significantly reduced carbon emissions and have tried to meet the rising demands for clean, reliable, and continuous energy. However, challenges of intermittency, weather conditions, and geographical constraints still hamper the adequate utilization of [...] Read more.

Renewable energy sources such as wind, solar, and hydro have significantly reduced carbon emissions and have tried to meet the rising demands for clean, reliable, and continuous energy. However, challenges of intermittency, weather conditions, and geographical constraints still hamper the adequate utilization of these renewable energy sources. Space-Based Solar Power (SBSP) offers a potential solution by generating continuous, large-scale energy from the solar collectors in orbit. However, it faces major technical, political, and economic challenges, which include high launch costs, safety and efficiency concerns in wireless transmission, orbital congestion, and environmental risks. Recent studies, such as the European Modeling energy systems, evaluations by NASA, and feasibility studies by the European Space Agency, suggest that while SBSP remains expensive, certain design pathways could potentially reduce the costs, making SBSP a competitive or complementary technology mid-century. This paper reviews the latest advances in system design, transmission methods, orbital rectenna configurations, economic feasibility, as well as the legal and environmental impacts, providing a comprehensive view of where Space-Based Solar Power currently stands. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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9 pages, 2997 KB

Open AccessProceeding Paper

Techno-Economic Evaluation of a Renewable-Hydrogen System for African University Campuses: A Case Study at MUT

by Khumbula W. Ngidi, Cyncol A. Sibiya, Bubele P. Numbi, Kanzumba Kusakana and Ngancha Patrick

Eng. Proc. 2026, 140(1), 28; https://doi.org/10.3390/engproc2026140028 - 22 May 2026

Viewed by 452

Abstract

African universities face persistent energy insecurity that disrupts teaching, research, and campus operations. While renewable energy adoption is growing, hydrogen-based hybrid renewable energy systems (HRES) remain underexplored, and standard evaluation tools are lacking. This paper presents a replicable techno-economic framework for integrating renewable-hydrogen [...] Read more.

African universities face persistent energy insecurity that disrupts teaching, research, and campus operations. While renewable energy adoption is growing, hydrogen-based hybrid renewable energy systems (HRES) remain underexplored, and standard evaluation tools are lacking. This paper presents a replicable techno-economic framework for integrating renewable-hydrogen systems into university microgrids using Hybrid Optimization Model for Multiple Energy Resources (HOMER) simulation. The framework evaluates reliability, environmental impact, economic feasibility, and scalability under real campus conditions. A case study of the Mangosuthu University of Technology (MUT) Engineering Building compares three scenarios: grid-plus-diesel backup, (photovoltaic) PV–battery–hydrogen hybrid with grid support, and PV–battery–hydrogen hybrid with diesel backup. Results indicate that the PV–battery–hydrogen configuration with grid support achieved 98% reliability, a 74% reduction in Carbon dioxide (CO₂) emissions, and an Levelized Cost of Energy (LCOE) of $0.124/kWh, outperforming the current grid–diesel setup. These findings confirm the framework’s effectiveness as a benchmarking tool and its potential to guide African universities toward resilient, low-carbon energy systems aligned with national transition goals. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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7 pages, 676 KB

Open AccessProceeding Paper

The Impact of the Integration of Renewable Energy Sources into the Grid in Namibia

by Relebohile Jae, Tlotlollo Hlalele and Sumbwanyambe Mbuyu

Eng. Proc. 2026, 140(1), 29; https://doi.org/10.3390/engproc2026140029 - 25 May 2026

Viewed by 466

Abstract

Namibia’s strategy to lessen reliance on electricity imports and move toward sustainable energy includes integrating its abundant renewable energy resources—particularly solar and wind—into its grid. Although there are advantages of renewable energy, integrating it into the grid presents serious technical difficulties. This study [...] Read more.

Namibia’s strategy to lessen reliance on electricity imports and move toward sustainable energy includes integrating its abundant renewable energy resources—particularly solar and wind—into its grid. Although there are advantages of renewable energy, integrating it into the grid presents serious technical difficulties. This study examines how Namibia’s grid is affected by this integration, paying attention to fault level behaviour, load flow analysis, contingency response, and voltage stability using QV analysis. The impact of distributed generation on power flows, voltage profiles, and system reliability is illustrated through analytical formulations and simulation results. Findings reveal better bus voltages and lower power losses, but they also show changes in voltage stability margins and a decrease in the fault current contribution, showing that while integration increases sustainability, maintaining overall grid stability requires supplementary measures. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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11 pages, 1191 KB

Open AccessProceeding Paper

AI-Enabled Renewable Energy Systems for Rural Electrification in South Africa: A Technical, Environmental, and Ethical Analysis

by Khumbulani Derrick Sithole, Mbuyu Sumbwanyambe and Motlatsi Cletus Lehloka

Eng. Proc. 2026, 140(1), 30; https://doi.org/10.3390/engproc2026140030 - 26 May 2026

Viewed by 518

Abstract

The transition to decentralized, clean energy systems is essential for sustainable development, particularly in rural South African communities where grid extension costs can exceed R300,000 per km. This paper presents a comprehensive analysis of Artificial Intelligence (AI) integration into hybrid solar-battery systems to [...] Read more.

The transition to decentralized, clean energy systems is essential for sustainable development, particularly in rural South African communities where grid extension costs can exceed R300,000 per km. This paper presents a comprehensive analysis of Artificial Intelligence (AI) integration into hybrid solar-battery systems to address challenges of intermittency, load variability, and unreliable demand. We propose a model incorporating Long Short-Term Memory (LSTM) networks for energy forecasting and Reinforcement Learning (RL) for real-time optimization. Mathematical formulations for photovoltaic (PV) generation, battery state-of-charge dynamics, and a multi-objective cost function minimizing Levelized Cost of Energy (LCOE), carbon emissions, and reliability loss are derived with appropriate citations. A fairness metric is introduced as an operational constraint to mitigate algorithmic bias in energy allocation. Simulation results, calibrated with South African data, demonstrate a 20% improvement in forecasting accuracy (RMSE), a 30% reduction in diesel generator use, and a decrease in LCOE from R7.80 to R5.50/kWh. Furthermore, our fairness-constrained optimization reduced the Gini coefficient for load shedding from 0.38 to 0.19, ensuring more equitable access across households. This study concludes that AI-driven microgrids are technically viable, environmentally beneficial, and ethically sound for advancing equitable rural electrification in South Africa. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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9 pages, 5527 KB

Open AccessProceeding Paper

The Use of AI-Powered Finite Element Analysis for Predictive Maintenance on Electrical Rotating Machines

by Nonkululeko Mgidi Nkosi and Tlotlollo Hlalele

Eng. Proc. 2026, 140(1), 31; https://doi.org/10.3390/engproc2026140031 - 22 May 2026

Viewed by 324

Abstract

Electrical rotating machines are critical assets in industrial operations but are prone to unforeseen failures resulting in costly downtime. Traditional maintenance strategies such as preventive and reactive methods do not offer early warnings of faults. The paper presents an AI-based predictive maintenance system [...] Read more.

Electrical rotating machines are critical assets in industrial operations but are prone to unforeseen failures resulting in costly downtime. Traditional maintenance strategies such as preventive and reactive methods do not offer early warnings of faults. The paper presents an AI-based predictive maintenance system that integrates Finite Element Analysis (FEA), Fast Fourier Transform (FFT), and machine learning algorithms for detecting anomalies in electrical rotating machines. Historical failure data from industrial applications, along with simulation-based fault injections, were used to train and to validate the models. The results show high true positive rates in fault detection with improved accuracy over conventional monitoring systems. The proposed model achieved 84.2% accuracy in fault prediction and has the potential to enhance machine reliability, reduces maintenance cost, and improves operational safety. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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11 pages, 1757 KB

Open AccessProceeding Paper

Techno-Economic Assessment of Hybrid Renewable Energy Systems for Electric Vehicle Smart Charging (EVSC) in BRT Infrastructure

by Ayodeji Akinsoji Okubanjo, Ignatius Kema Okakwu, Adekunle Olorunlowo David, Julius Musyoka Ndambuki, Jacques Snyman, Williams Kehinde Kupolati and Mpho Muloiwa

Eng. Proc. 2026, 140(1), 32; https://doi.org/10.3390/engproc2026140032 - 26 May 2026

Viewed by 640

Abstract

The electrification of public transport, particularly Bus Rapid Transits (BRT), is a significant step toward achieving sustainable urban mobility and reducing dependency on fossil fuels. However, rapid adoption of Electric Vehicles Smart Charging (EVSC) infrastructure presents grid stability, economic and environmental concerns. The [...] Read more.

The electrification of public transport, particularly Bus Rapid Transits (BRT), is a significant step toward achieving sustainable urban mobility and reducing dependency on fossil fuels. However, rapid adoption of Electric Vehicles Smart Charging (EVSC) infrastructure presents grid stability, economic and environmental concerns. The rising demand for electric cars, particularly in developing nations such as Nigeria, highlights the urgent need for a sustainable hybrid renewable energy charging infrastructure for BRT systems. This study presents a techno-economic assessment of an off-grid hybrid systems that use photovoltaic (PV), wind turbines (WTs), hydrogen (H₂), fuel cell (FC) and battery technologies to power Electric Vehicles Smart Charging within Bus Rapid Transits networks. The Lagos BRT charging system at City Mall Station (CMS) serves as a case study, with hourly renewable resources obtained from National Aeronautics and Space Administration database (NASA). Using the HOMER pro-optimization tool, a multi-criteria analysis is performed to evaluate system viability, with special focus on key metrics such as levelized cost of energy (LCOE), net present cost (NPC), renewable energy fraction (REF), and greenhouse gas (GHG) emissions. The simulation results demonstrate that the hybrid PV/wind/FC/battery configuration is exceptionally economical, with an LCOE as low as $0.222/kWh, $2.03M NPC, 51.3% REF, and 159,209 kg of carbon dioxide emissions per year compared to grid-dependent charging. The study shows that integrated renewable-hydrogen systems are not only financially feasible, but also provide significant insights for policymakers, transportation authorities, and energy planners seeking to accelerate the transition to green public transportation infrastructure through innovative hybrid energy schemes. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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11 pages, 721 KB

Open AccessProceeding Paper

Role of Machine Learning in Improving Grid Resilience in Africa: A Comprehensive Review

by Allen Manyere and Sunetra Chowdhury

Eng. Proc. 2026, 140(1), 33; https://doi.org/10.3390/engproc2026140033 - 26 May 2026

Viewed by 726

Abstract

Electricity grids in Africa are encountering challenges due to rapid urbanization, variable renewable energy integration, aging infrastructure, and limited financial investments, leading to deterioration of grid resilience. This paper reviews how Machine Learning techniques are being applied to enhance grid resilience in Africa, [...] Read more.

Electricity grids in Africa are encountering challenges due to rapid urbanization, variable renewable energy integration, aging infrastructure, and limited financial investments, leading to deterioration of grid resilience. This paper reviews how Machine Learning techniques are being applied to enhance grid resilience in Africa, addressing issues like intermittent renewable energy, limited grid visibility, and infrastructure challenges. It analyzes recent research, applications, and case studies to identify key Machine Learning techniques for generation and demand forecasting, fault detection, intelligent energy control, and management. The paper also discusses barriers to implementation and proposes a roadmap for Machine Learning driven resilience strategies suited to Africa’s energy needs. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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13 pages, 5300 KB

Open AccessProceeding Paper

Intelligent and Adaptive Islanding Detection in Microgrids with Battery-Supercapacitor Hybrid Energy Storage

by Ernest Igbineweka and Sunetra Chowdhury

Eng. Proc. 2026, 140(1), 34; https://doi.org/10.3390/engproc2026140034 - 26 May 2026

Viewed by 361

Abstract

This paper presents the design and validation of an adaptive islanding detection method (AIDM) for an AC/DC hybrid microgrid integrated with a hybrid energy storage system (HESS) comprising a supercapacitor and a battery. The proposed AIDM combines dual-tree complex wavelet transform (DTCWT), synthetic [...] Read more.

This paper presents the design and validation of an adaptive islanding detection method (AIDM) for an AC/DC hybrid microgrid integrated with a hybrid energy storage system (HESS) comprising a supercapacitor and a battery. The proposed AIDM combines dual-tree complex wavelet transform (DTCWT), synthetic minority oversampling technique (SMOTE), and long short-term memory (LSTM) network to effectively detect islanding and non-islanding conditions in the microgrid following faults/disturbances. Fault and disturbance signals are captured at the point of common coupling, following which they are extracted and decomposed using DTCWT. The SMOTE algorithm is employed for data preprocessing to balance the dataset and enhance the accuracy of the intelligent classifier. Finally, LSTM is used for training and testing the AIDM for different faults/disturbance classification and detection. Two categories of datasets,

T_{D 1}

and

T_{D 2}

, are used for testing the AIDM. The results obtained from MATLAB/Simulink show that datasets incorporated with HESS achieve higher detection accuracy of 100% compared to datasets without HESS with average accuracy of 99.77% under sudden load increase. It is also established that the proposed AIDM maintains robustness when exposed to noise signals, confirming its reliability under noisy conditions. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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9 pages, 1103 KB

Open AccessProceeding Paper

Experimental Comparison of PI and PID for Field Excitation in a Synchronous Condenser

by Lindokuhle Madlala, Kumeshan Reddy and Enock Chekure

Eng. Proc. 2026, 140(1), 35; https://doi.org/10.3390/engproc2026140035 - 27 May 2026

Viewed by 465

Abstract

This paper presents an experimental comparison of proportional–integral (PI) and proportional–integral–derivative (PID) controllers for excitation regulation in a 1.5 kW synchronous condenser. The excitation current was controlled using a PWM-based converter driven by an ESP32 microcontroller, with reactive power feedback. Both controllers were [...] Read more.

This paper presents an experimental comparison of proportional–integral (PI) and proportional–integral–derivative (PID) controllers for excitation regulation in a 1.5 kW synchronous condenser. The excitation current was controlled using a PWM-based converter driven by an ESP32 microcontroller, with reactive power feedback. Both controllers were tested across multiple reactive power setpoints to evaluate settling time and steady-state accuracy performance. The results show that both achieved steady-state errors within ±5% of the reference. The PI controller provided faster settling, while the PID controller offered smoother but slower responses due to feedback bandwidth limitations. The findings confirm that PI control is an effective and low-computational-cost solution for embedded excitation systems. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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12 pages, 1092 KB

Open AccessProceeding Paper

A Nyquist-Based Method of Studying Control Interactions Between PSS and HVDC MSDC Damping Controllers

by Righteous Vengesai, John van Coller and Chandima Gomes

Eng. Proc. 2026, 140(1), 36; https://doi.org/10.3390/engproc2026140036 - 27 May 2026

Viewed by 591

Abstract

This paper presents a Nyquist-based method for assessing control interactions between a Power System Stabilizer (PSS) and an HVDC Modulation Supplementary Damping Controller (MSDC) in hybrid AC/DC networks. Loop-at-a-time perturbations are applied to reveal how one controller deforms the other’s Nyquist contour, directly [...] Read more.

This paper presents a Nyquist-based method for assessing control interactions between a Power System Stabilizer (PSS) and an HVDC Modulation Supplementary Damping Controller (MSDC) in hybrid AC/DC networks. Loop-at-a-time perturbations are applied to reveal how one controller deforms the other’s Nyquist contour, directly exposing frequency-dependent coupling. A spectral-radius margin is introduced as a quantitative robustness indicator. Reduced-order transfer functions identified using the Matrix Pencil Method enable accurate frequency-response analysis from transient-stability data. Application to Kundur’s two-area system with an embedded LCC–HVDC link demonstrates that the method clearly exposes controller dominance, interaction severity, and gain-sensitivity effects. The proposed framework thus provides a practical and measurement-compatible means for visualizing and coordinating damping controllers in weak hybrid AC/DC networks. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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11 pages, 874 KB

Open AccessProceeding Paper

Optimal Tuning of PSS and HVDC MSDC Damping Controllers to Reduce Control Interactions

by Righteous Vengesai, John van Coller and Chandima Gomes

Eng. Proc. 2026, 140(1), 37; https://doi.org/10.3390/engproc2026140037 - 27 May 2026

Viewed by 499

Abstract

This paper presents a measurement-based framework for studying and mitigating control interactions between power system stabilizers (PSSs) and HVDC modulation damping controllers in hybrid AC/DC systems. Using frequency-response data obtained from small-signal injections, the method embeds driving-point and transfer impedance directly into the [...] Read more.

This paper presents a measurement-based framework for studying and mitigating control interactions between power system stabilizers (PSSs) and HVDC modulation damping controllers in hybrid AC/DC systems. Using frequency-response data obtained from small-signal injections, the method embeds driving-point and transfer impedance directly into the control loops, eliminating reliance on simplified analytical models. A lightweight optimizer adjusts controller gains and lead–lag angles to enhance damping at the inter-area mode while ensuring HVDC-to-PSS dominance, magnitude-crossing consistency, and a minimum damping margin across the 0.3–1.5 Hz band. The approach, implemented in ETAP 16.0 and MATLAB R2024a (MathWorks, Natick, MA, USA), successfully improves damping and maintains stability under all tested conditions, providing a practical co-design strategy for coordinated PSS–HVDC control in weakly interconnected networks. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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12 pages, 1884 KB

Open AccessProceeding Paper

Experimental Analysis of Arc Path Behaviour on Polymeric Insulators Under Different Material, Geometric, and Surface Conditions

by Kimishca Naidoo, Afroz Minhas, Salman Minhas and Chandima Gomes

Eng. Proc. 2026, 140(1), 38; https://doi.org/10.3390/engproc2026140038 - 28 May 2026

Viewed by 599

Abstract

Understanding how geometry, surface condition, and polarity influence surface flashover is important for improving the reliability of polymeric insulation in high-voltage systems exposed to transient overvoltages. The purpose of this study was to experimentally investigate visible arc path behaviour on polymeric insulators made [...] Read more.

Understanding how geometry, surface condition, and polarity influence surface flashover is important for improving the reliability of polymeric insulation in high-voltage systems exposed to transient overvoltages. The purpose of this study was to experimentally investigate visible arc path behaviour on polymeric insulators made of polymethyl methacrylate (PMMA), polyvinyl chloride (PVC), and nylon under standard 1.2/50 µs lightning voltage impulses. Cylindrical, concave, and convex profiles were tested in a rod–plane configuration for both positive and negative polarities under clean and sunflower oil- coated surface conditions. Seven arc types were observed. While the visible arc path was governed mainly by geometry and polarity, the electrical breakdown response exhibited material-dependent effects. Positive-polarity oil-coated samples generally exhibited longer time-to-breakdown, while negative-polarity tests produced higher breakdown voltages, and oil often reduced the withstand level. The large variability in time-to-breakdown data indicates that impulse flashover is strongly stochastic and sensitive to small surface or field variations. The findings highlight the need for improving control of surface films, expanding environmental testing, and conducting further modelling to predict flashover behaviour across different insulator designs. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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12 pages, 1979 KB

Open AccessProceeding Paper

Evaluation of Optimization Methods for EV and REDG Integration into the Power System Under Various Operational Scenarios

by Mlungisi Ntombela and Musasa Kabeya

Eng. Proc. 2026, 140(1), 39; https://doi.org/10.3390/engproc2026140039 - 28 May 2026

Viewed by 466

Abstract

The exhaustion of fossil fuels, environmental concerns, and difficulties in deploying smart grids have expedited the development of renewable energy distributed generators (REDGs) and electric vehicles (EVs). In recent decades, there has been a notable rise in the production and marketing of EVs. [...] Read more.

The exhaustion of fossil fuels, environmental concerns, and difficulties in deploying smart grids have expedited the development of renewable energy distributed generators (REDGs) and electric vehicles (EVs). In recent decades, there has been a notable rise in the production and marketing of EVs. Previous research has proposed reactive power control solutions, including the use of power electronic converters associated with distributed generators (DGs) to alleviate voltage fluctuations. This research presents a strategy for the best integration of electric vehicles through bidirectional charging and renewable energy distributed generators inside power systems, with the objective of efficiently managing voltage, active power, and reactive power flows at interconnection points. Furthermore, it entails determining appropriate locations and dimensions for electric car charging stations through a comparative examination of computing time and iterations between the Hybrid Genetic Algorithm Improved Particle Swarm Optimization (HGAIPSO) and several other optimization methods, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Improved Particle Swarm Optimization (IPSO). This analysis was performed on the IEEE-118 bus system, incorporating Vehicle-to-Grid (V2G), Grid-to-Vehicle (G2V), and REDG allocations. The simulation results indicated that the suggested HGAIPSO approach is more rapid and effective regarding calculation time for complex networks, attaining optimal solutions with greater efficiency. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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9 pages, 2530 KB

Open AccessProceeding Paper

Assessment of Harmonic Distortion Compliance in South African Distribution Networks Under Increasing Penetration of Distributed Energy Resources

by Francis Bennie, Mohamed Khan and Andrew Swanson

Eng. Proc. 2026, 140(1), 40; https://doi.org/10.3390/engproc2026140040 - 28 May 2026

Viewed by 309

Abstract

The increasing penetration of inverter-based distributed energy resources (DERs) within distribution networks has resulted in harmonic distortion risks that can affect transformer thermal loading, service life, and network hosting capacity. This study assesses harmonic behaviour under increasing DER penetration using a detailed MATLAB [...] Read more.

The increasing penetration of inverter-based distributed energy resources (DERs) within distribution networks has resulted in harmonic distortion risks that can affect transformer thermal loading, service life, and network hosting capacity. This study assesses harmonic behaviour under increasing DER penetration using a detailed MATLAB 2025b/Simulink model of the CIGRÉ low-voltage benchmark feeder, adapted to reflect representative network parameters and run at a 400 V point of common coupling (PCC). DER penetration is incrementally increased from 0% to 195% of feeder load, and for each penetration level the PCC currents and voltages are examined using FFT-based spectrum extraction. The short-circuit strength is first calculated (I_SC/I_L = 14.1), and harmonic current and voltage distortion thresholds are benchmarked against IEEE 519:2022 and NRS 048-2:2025 respectively. Results show that while DER inverters introduce increasing odd-order harmonics, mainly the 3rd, 5th, 7th and 11th, the feeder’s moderate short-circuit capacity suppresses PCC voltage distortion, keeping voltage THD below 3% across all scenarios. As the inverter-based DER penetration increases, so does the harmonic current distortion. At 180%, Total Demand Distortion (TDD) nears the IEEE limit of 5%. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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8 pages, 232 KB

Open AccessProceeding Paper

Frequency Response of Voltage Transformers for Harmonic Measurement in South African Renewable Grids

by Suline Engelbrecht and Jan A. de Kock

Eng. Proc. 2026, 140(1), 41; https://doi.org/10.3390/engproc2026140041 - 28 May 2026

Viewed by 601

Abstract

Voltage transformers (VTs) are part of the power quality (PQ) measurement system in renewable energy installations where harmonic distortion (HD) exists. Although they are designed for fundamental-frequency operation, VTs exhibit frequency-dependent behaviour that causes ratio and phase errors at harmonic frequencies. These errors [...] Read more.

Voltage transformers (VTs) are part of the power quality (PQ) measurement system in renewable energy installations where harmonic distortion (HD) exists. Although they are designed for fundamental-frequency operation, VTs exhibit frequency-dependent behaviour that causes ratio and phase errors at harmonic frequencies. These errors decrease measurement accuracy and impact compliance verification under South African grid code standards. International standards such as IEC TR 61869-103 and IEEE 519 do not specify harmonic-frequency accuracy classes or correction methods. This paper examines published research on VT frequency response and considers its effects on harmonic measurement in South African renewable networks. The review highlights technical and regulatory challenges that affect the reliability of harmonic measurements and emphasises the need for structured frequency-response testing under local operating conditions. A complementary methodological study addressing this need has been submitted for publication. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

9 pages, 1585 KB

Open AccessProceeding Paper

Developing a Standardised Method for Frequency Response Evaluation of Voltage Transformers for Power Quality Compliance

by Suline Engelbrecht and Jan A. de Kock

Eng. Proc. 2026, 140(1), 42; https://doi.org/10.3390/engproc2026140042 - 28 May 2026

Viewed by 188

Abstract

Accurate harmonic measurement is required for power quality (PQ) compliance in South Africa’s inverter-based renewable grids. The frequency response of the current transformer (CT) has been characterised through structured testing, while voltage transformers (VTs) remain untested under harmonic excitation in local conditions. This [...] Read more.

Accurate harmonic measurement is required for power quality (PQ) compliance in South Africa’s inverter-based renewable grids. The frequency response of the current transformer (CT) has been characterised through structured testing, while voltage transformers (VTs) remain untested under harmonic excitation in local conditions. This paper proposes a method for evaluating single-phase VT frequency response by adapting CT test strategies to voltage excitation. MATLAB R2025b Simulink models support interpreting measured data. The framework measures ratio and phase errors up to the 60th harmonic (3 kHz) and detects resonances important for PQ assessment. The study addresses a methodological gap in South African PQ measurement and supports the development of standardised procedures for evaluating VT frequency response in renewable power systems. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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8 pages, 1546 KB

Open AccessProceeding Paper

A Machine Learning Framework to Detect Fraud Energy Consumption Patterns in a Smart Meter Dataset

by Mulizi David Ruhaya, Senthil Krishnamurthy, Doudou Luta and Haltor Mataifa

Eng. Proc. 2026, 140(1), 43; https://doi.org/10.3390/engproc2026140043 - 28 May 2026

Viewed by 422

Abstract

Electricity theft remains a critical challenge that destabilizes power systems, causes significant financial losses, and disrupts the grid, particularly in developing countries. This study presents a machine learning framework integrating an ANN and advanced performance metrics to accurately detect fraud consumption patterns in [...] Read more.

Electricity theft remains a critical challenge that destabilizes power systems, causes significant financial losses, and disrupts the grid, particularly in developing countries. This study presents a machine learning framework integrating an ANN and advanced performance metrics to accurately detect fraud consumption patterns in a smart meter dataset. The method achieves strong categorization between normal and abnormal conduct by simulating temporal behavior across seasons, applying feature extraction to high-resolution energy signals, and assessing performance using RMSE, MAE, and R². The experimental results demonstrate that intelligent algorithms significantly improve theft-detection accuracy; reduce losses, especially NTLs; and provide a scalable foundation for future smart-grid security. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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11 pages, 10839 KB

Open AccessProceeding Paper

A Coordinated HVDC and Energy Storage Framework for Grid Stability in Renewable Systems

by Xander Abbey and Abayomi A. Adebiyi

Eng. Proc. 2026, 140(1), 44; https://doi.org/10.3390/engproc2026140044 - 28 May 2026

Viewed by 217

Abstract

With the rising trend of replacing synchronous generators with inverter-based resources, the grid inertia, frequency control, voltage stability, and fault ride-through are compromised. The current research focuses on the coordinated control of Voltage Source Converter-based HVDC (VSC HVDC) and Battery Energy Storage Systems [...] Read more.

With the rising trend of replacing synchronous generators with inverter-based resources, the grid inertia, frequency control, voltage stability, and fault ride-through are compromised. The current research focuses on the coordinated control of Voltage Source Converter-based HVDC (VSC HVDC) and Battery Energy Storage Systems (BESS) for improving the grid stability in the presence of intermittent sources. Two models are created in the MATLAB/Simulink 2025a environment: one for the grid-connected PV system with the addition of BESS in grid-forming mode (GFM) and grid-following mode (GFL), and the other for the multi-terminal HVDC system with the integration of wind energy from the ocean. The results show that the grid-forming converters perform better than grid-following converters in the event of disturbances, and the coordinated control structure aligns with the IEEE 2800-2022 for low-inertia grids. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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9 pages, 6770 KB

Open AccessProceeding Paper

The Performance Evaluation of a Solar PV-Fuel Cell System Under Dynamic Irradiance and Temperature Conditions

by Mbekezeli Sandile Maduna, Evans Ojo and Nelson Chetty

Eng. Proc. 2026, 140(1), 45; https://doi.org/10.3390/engproc2026140045 - 1 Jun 2026

Viewed by 363

Abstract

Renewable energy sources (RESs) in microgrids are vital for sustainable and resilient power networks, especially in rural South Africa with diverse climatic conditions. Photovoltaic (PV) energy generation is intermittent, making it difficult to offer reliable electricity in varying conditions. The Proton Exchange Membrane [...] Read more.

Renewable energy sources (RESs) in microgrids are vital for sustainable and resilient power networks, especially in rural South Africa with diverse climatic conditions. Photovoltaic (PV) energy generation is intermittent, making it difficult to offer reliable electricity in varying conditions. The Proton Exchange Membrane Fuel Cell (PEMFC) and solar system are integrated in this study to provide a sustainable energy source that can address these issues. Under varying temperature and irradiance conditions, the PV system was evaluated with and without an LCL filter and PEMFC unit using PVGIS Northern Cape daily solar irradiation data. Results show that solar input variability causes large voltage fluctuations in the standalone PV system. This study adds to the expanding knowledge on RES resilience by utilising real-world climatic data and shows that PV-FC systems can be a sustainable and reliable option for microgrid and standalone applications in rural locations with ample resources or without electrical infrastructure. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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10 pages, 1639 KB

Open AccessProceeding Paper

The Evaluation of Simple Boost Control and Space Vector PWM Techniques for Power Quality Improvement on a PV-FC Microgrid

by Mbekezeli Sandile Maduna, Nelson Chetty and Evans Ojo

Eng. Proc. 2026, 140(1), 46; https://doi.org/10.3390/engproc2026140046 - 2 Jun 2026

Viewed by 365

Abstract

The increasing penetration of renewable technologies, particularly photovoltaic (PV) and fuel cell (FC) systems, into microgrid networks has created new challenges in maintaining voltage stability, harmonic performance, and overall power quality. This study presents a comparative evaluation of two modulation and control strategies, [...] Read more.

The increasing penetration of renewable technologies, particularly photovoltaic (PV) and fuel cell (FC) systems, into microgrid networks has created new challenges in maintaining voltage stability, harmonic performance, and overall power quality. This study presents a comparative evaluation of two modulation and control strategies, which are a Simple Boost Control (SBC) and Space Vector Modulation (SVM). The system is modeled and simulated under standard test conditions (STC) as well as dynamic fluctuations in irradiance to evaluate the inverter performance, total harmonic distortion (THD), and DC-link voltage stability. Simulation findings indicate that although SBC provides structural simplicity and dependable voltage enhancement, the SVM approach delivers greater harmonic mitigation, more seamless inverter performance, and improved voltage utilisation in variable conditions. The results enhance the optimisation of power electronic control systems for renewable energy microgrids, facilitating steady and efficient operation in accordance with South Africa’s green energy goals. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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10 pages, 1447 KB

Open AccessProceeding Paper

Coordinated Control of Flywheel and Battery Energy Storage Systems for Stabilizing Low-Inertia Power Networks

by Willy Stephane Ngaha, John Van Coller and Chandima Gomes

Eng. Proc. 2026, 140(1), 47; https://doi.org/10.3390/engproc2026140047 - 4 Jun 2026

Viewed by 547

Abstract

The increasing penetration of inverter-based renewable energy sources has significantly reduced system inertia, leading to faster frequency deviations in low-inertia power systems. This paper proposes an asynchronous distributed model predictive control (AD-MPC) strategy to coordinate flywheel energy storage systems (FESSs) and battery energy [...] Read more.

The increasing penetration of inverter-based renewable energy sources has significantly reduced system inertia, leading to faster frequency deviations in low-inertia power systems. This paper proposes an asynchronous distributed model predictive control (AD-MPC) strategy to coordinate flywheel energy storage systems (FESSs) and battery energy storage systems (BESSs) for enhanced frequency stability in low-inertia power grids. A modified IEEE 39-bus system integrating a 3 MW wind energy conversion system (WECS), a 2 MW PV solar unit, and an electric vehicle (EV) load emulator unit was simulated to evaluate the system performance of the controller under a 30% increase in load disturbance. The results show that the coordinated FESS–BESS operation using the proposed AD-MPC controller achieves faster frequency recovery and reduces frequency deviation by 4% compared to single storage configurations. The proposed approach demonstrates that the high-speed FESS can provide a rapid inertial response, while the BESS delivers primary frequency support, offering a promising solution for maintaining dynamic stability in future renewable-dominated power systems. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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7 pages, 1098 KB

Open AccessProceeding Paper

A Hybrid Mini-Grid System for Rural Electrification in Lesotho

by Tsitso Nkhabu and Akshay Kumar Saha

Eng. Proc. 2026, 140(1), 48; https://doi.org/10.3390/engproc2026140048 - 4 Jun 2026

Viewed by 438

Abstract

This study outlines the design and assessment of a hybrid renewable energy system aimed at powering rural electrification for five villages in the Butha-Buthe district of Lesotho, which has an overall daily energy consumption of 1342 kWh and a peak demand of 112 [...] Read more.

This study outlines the design and assessment of a hybrid renewable energy system aimed at powering rural electrification for five villages in the Butha-Buthe district of Lesotho, which has an overall daily energy consumption of 1342 kWh and a peak demand of 112 kW. Utilizing HOMER Pro (version 3.18.4), various configurations were analyzed. The most cost-effective system, comprising PV, wind, hydro, batteries, and a diesel generator, resulted in an LCOE of USD 0.3194, alongside a renewable share of 73%. An entirely renewable setup was also explored, achieving a 100% renewable share but with a higher LCOE of USD 0.6615. Sensitivity analysis regarding diesel pricing and hydro flow rates revealed significant effects on Net Present Cost and fuel consumption. The results highlight feasible options for economically efficient, renewable-centric rural electrification in isolated areas. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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8 pages, 1197 KB

Open AccessProceeding Paper

Mitigating Frequency Collapse in Low-Inertia Systems: A Case for Optimal BESS Placement

by Ntando Madiba, Best Khoza and Oluwagbenga Apata

Eng. Proc. 2026, 140(1), 49; https://doi.org/10.3390/engproc2026140049 - 5 Jun 2026

Viewed by 340

Abstract

The displacement of synchronous generators by inverter-based renewable energy sources (RES) has eroded system inertia, weakening frequency stability even as voltage stability improves. This paradox poses a major challenge for modern grids. Battery Energy Storage Systems (BESS) offer synthetic inertia and rapid frequency [...] Read more.

The displacement of synchronous generators by inverter-based renewable energy sources (RES) has eroded system inertia, weakening frequency stability even as voltage stability improves. This paradox poses a major challenge for modern grids. Battery Energy Storage Systems (BESS) offer synthetic inertia and rapid frequency response, but their stabilising impact depends critically on placement. Using dynamic simulations on the IEEE 9-bus system, this study demonstrates the voltage–frequency paradox across increasing RES penetration. Results show that strategic siting prevents frequency collapse while enhancing voltage recovery, providing a unified mitigation strategy for high-renewable systems. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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8 pages, 735 KB

Open AccessProceeding Paper

Risk-Based Inspection Applied to Cost Savings in Pumped Energy Storage Scheme Pressure Vessels

by Thendo Mphaphathi, Shanil Narain Singh, Takalani Madzivhandila, Antoine-Floribert Mulaba-Bafubiandi and Jan Harm C. Pretorius

Eng. Proc. 2026, 140(1), 50; https://doi.org/10.3390/engproc2026140050 - 5 Jun 2026

Viewed by 423

Abstract

Pumped Energy Storage Schemes play a critical role in electricity grid stability and energy security by storing excess electricity for later use. Pressure vessels in these systems are subject to rigorous inspection regimes because of their potential risks to safety and performance. Traditional [...] Read more.

Pumped Energy Storage Schemes play a critical role in electricity grid stability and energy security by storing excess electricity for later use. Pressure vessels in these systems are subject to rigorous inspection regimes because of their potential risks to safety and performance. Traditional Time-Based Inspection, while effective, can be costly and inefficient. This paper investigates the application of Risk-Based Inspection methodologies to optimise inspection planning, reduce costs, and maintain safety in Pumped Energy Storage Scheme pressure vessels. The study presents a structured framework for implementing Risk-Based Inspection, demonstrates the potential for cost savings through comparative analysis, and highlights its alignment with regulatory requirements in South Africa. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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16 pages, 2402 KB

Open AccessProceeding Paper

Eigenvalue-Based Stability Assessment of DFIG Wind Turbines Under Operating-Point Variations

by Christophe Basila Tambwe and Akshay Kumar Saha

Eng. Proc. 2026, 140(1), 51; https://doi.org/10.3390/engproc2026140051 - 5 Jun 2026

Viewed by 336

Abstract

This paper presents detailed small-signal modeling and modal analysis of a 1.5 MW grid-connected doubly fed induction generator (DFIG) wind turbine. A full nonlinear model capturing stator, rotor, and grid-side converter dynamics, DC-link voltage behavior, and the wind-turbine electromechanical subsystem is developed in [...] Read more.

This paper presents detailed small-signal modeling and modal analysis of a 1.5 MW grid-connected doubly fed induction generator (DFIG) wind turbine. A full nonlinear model capturing stator, rotor, and grid-side converter dynamics, DC-link voltage behavior, and the wind-turbine electromechanical subsystem is developed in the synchronously rotating d-q frame and linearized around a realistic steady-state operating point. The resulting state-space representation is utilized to investigate the intrinsic dynamic characteristics of the DFIG through eigenvalue analysis, modal classification, and participation factor evaluation. The results show that the open-loop DFIG contains a weakly damped electrical mode, a slowly growing unstable mode, and a near-integrator mode linked to the DC-link voltage, all of which strongly influence system behavior under disturbances. Parameter-sensitivity studies reveal how rotor speed, stator voltage, and rotor resistance affect the dominant modes, highlighting significant deterioration under low-voltage and low-speed operating conditions. Time-domain small-signal responses to temporary voltage sags further expose the vulnerability of DC-link voltage and power outputs when no coordinated control is applied. Overall, the study establishes a rigorous dynamic baseline for DFIG systems and provides the foundational insight needed for a follow-up paper focused on advanced damping and robustness-enhancing controllers. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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8 pages, 6586 KB

Open AccessProceeding Paper

Power Energy Management for a Hybrid Renewable System Using Artificial and Computational Intelligence

by Musawenkosi Lethumcebo Thanduxolo Zulu, Rudiren Sarma and Remy Tiako

Eng. Proc. 2026, 140(1), 52; https://doi.org/10.3390/engproc2026140052 - 5 Jun 2026

Viewed by 424

Abstract

There are significant difficulties with power quality and stability as a result of active cooperation between renewable energy sources and load demand. To maintain power stability between renewable energy supplies and the microgrid/utility grid, novel solutions must be implemented. By using an artificial [...] Read more.

There are significant difficulties with power quality and stability as a result of active cooperation between renewable energy sources and load demand. To maintain power stability between renewable energy supplies and the microgrid/utility grid, novel solutions must be implemented. By using an artificial and computational intelligence controller to schedule power from multiple sources (photovoltaic, wind, grid, and battery) under a set of constraints, such as weather, load-shedding hours, and peak pricing hours, this paper introduces a novel approach for power management in grid-connected hybrid renewable systems with PV–wind and energy storage systems. The approach involves using an artificial neural network (ANN) to process all of the inputs and creating an ANN rule set from a modelled hybrid renewable system. A rule-based power scheduler is developed, and simulations are run for a full day. The suggested fuzzy control approach can detect ongoing variations in grid load-shedding patterns, PV–wind power generation, load demands, and battery state-of-charge to enable prompt and accurate decision-making. The proposed ANN rule-based scheduler can handle nonlinearity by integrating metaheuristics into computer-assisted decision-making and can function effectively with imprecise inputs, negating the need for an exact numerical model. The MATLAB/Simulink R2023a software was used for simulation, and the system operated as efficiently as possible. The simulation results suggested that an ANN offers a foundation for extension to handle numerous particular scenarios. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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11 pages, 1340 KB

Open AccessProceeding Paper

Voltage Stability in a Weak Grid with Hybrid Renewable Generation Plants

by Naniki Letta Nzuza, David Oyedokun and Mkhutazi Mditshwa

Eng. Proc. 2026, 140(1), 53; https://doi.org/10.3390/engproc2026140053 - 5 Jun 2026

Viewed by 485

Abstract

This paper presents a comprehensive review of voltage stability challenges in South Africa’s constrained power grid, particularly in the context of rising hybrid renewable energy integration. With the growing deployment of inverter-based resources (IBRs) like solar PV, wind, and battery energy storage systems [...] Read more.

This paper presents a comprehensive review of voltage stability challenges in South Africa’s constrained power grid, particularly in the context of rising hybrid renewable energy integration. With the growing deployment of inverter-based resources (IBRs) like solar PV, wind, and battery energy storage systems (BESS), especially under programmes through the Independent Power Procurement Office, voltage stability has emerged as a key concern, particularly in weak grid areas like the Northern Cape Province. We highlight how weak grids characterized by low short-circuit capacity, long transmission lines, and limited reactive power support are more susceptible to voltage instability, especially with high penetration of non-synchronous generation. Using a modified IEEE 14-bus system with hybrid generation, the study simulates a weak grid scenario. Findings point to significant reactive power losses and capacitive over-voltages in long and lightly loaded lines, mirroring some of the weak-grid-transmission challenges experiences in an area of the South African power grid. The study underscores the importance of dynamic load modelling (e.g., ZIP and exponential models) and inverter behaviour in stability analysis. It concludes that hybrid systems, when optimally designed and integrated with storage, can help support grid stability. However, proactive planning, advanced modelling, and compliance with evolving grid codes remain essential for securing reliable renewable integration. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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11 pages, 2694 KB

Open AccessProceeding Paper

Solar Photovoltaic Power Forecasting

by Lusindiso Gwadiso, Refiloe Shabalala, Khanyisa Shirinda, Willy Siti and Nsilulu Mbungu

Eng. Proc. 2026, 140(1), 54; https://doi.org/10.3390/engproc2026140054 - 5 Jun 2026

Viewed by 407

Abstract

The intermittent nature of renewable energy sources such as solar and wind power poses significant challenges for grid stability and energy management. Accurate forecasting is crucial for mitigating these challenges, as traditional models such as Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive [...] Read more.

The intermittent nature of renewable energy sources such as solar and wind power poses significant challenges for grid stability and energy management. Accurate forecasting is crucial for mitigating these challenges, as traditional models such as Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive Integrated Moving Average (SARIMA) often fail to capture the non-linear relationships between weather patterns and energy generation. To address this limitation, this research proposes a machine learning framework leveraging Convolutional Neural Networks (CNNs) for spatial pattern recognition and Recurrent Neural Networks (RNNs) for time-series forecasting. By integrating system design parameters with meteorological data, the framework aims to enhance prediction accuracy. The potential outcomes of this framework are not just improved grid stability, optimized energy storage utilization, and reduced operational costs, but also a significant step towards the efficient integration of renewable energy into the power system, fostering a sense of optimism for the future of renewable energy forecasting. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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12 pages, 863 KB

Open AccessProceeding Paper

An Optimization Approach for Demand-Side Scheduling in Microgrid Energy Management System

by Kayode Ebenezer Ojo, Akshay Kumar Saha and Viranjay M. Srivastava

Eng. Proc. 2026, 140(1), 55; https://doi.org/10.3390/engproc2026140055 - 5 Jun 2026

Viewed by 457

Abstract

In this work, a multi-objective quantum particle swarm optimization (QPSO) algorithm is proposed to address the optimal scheduling of non-dispatchable sources in a microgrid energy management system (MGEMS) for residential areas under utility-induced demand-side management (DSM) programs. While taking economic and environmental aspects [...] Read more.

In this work, a multi-objective quantum particle swarm optimization (QPSO) algorithm is proposed to address the optimal scheduling of non-dispatchable sources in a microgrid energy management system (MGEMS) for residential areas under utility-induced demand-side management (DSM) programs. While taking economic and environmental aspects into account, the goal is to maximize energy management by integrating a variety of distributed generation (DG) units with an energy storage device. Using real-time meteorological data, two case studies were analyzed and simulated using MATLAB/Simulink R2025b. The simulation results reveal that the optimum optimization outcome among the case studies is obtained at a higher DSM load participation level of 10%. Without the involvement of DSM, MG’s producing units in the first case had the highest carbon emissions of 797.110 kg and an overall operating cost of 267.10 €. Similarly, with the involvement of DSM, the second case had the lowest overall operating cost of 155.01 € and the lowest carbon emissions of 748.731 kg. The second case, which has optimal DG scheduling, is the suggested way to improve microgrid efficiency and provide a dependable power supply with low operating costs and emission reduction. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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9 pages, 1097 KB

Open AccessProceeding Paper

A Reinforcement Learning-Based Adaptive Voltage Regulation Strategy for Wind Energy Integrated Distribution Networks

by Ramesh Kumar Behara and Akshay Kumar Saha

Eng. Proc. 2026, 140(1), 56; https://doi.org/10.3390/engproc2026140056 - 5 Jun 2026

Viewed by 382

Abstract

The inherent variability of wind power generation poses major challenges for maintaining voltage stability and power quality in modern distribution networks. Conventional rule-based and optimisation-driven control strategies often fail to respond effectively to these rapid fluctuations. To address this limitation, this paper introduces [...] Read more.

The inherent variability of wind power generation poses major challenges for maintaining voltage stability and power quality in modern distribution networks. Conventional rule-based and optimisation-driven control strategies often fail to respond effectively to these rapid fluctuations. To address this limitation, this paper introduces an adaptive reinforcement learning (RL) framework that autonomously optimises reactive power compensation and on-load tap changer (OLTC) operations in real time. The proposed deep Q-network (DQN) agent learns optimal control policies through continuous interaction with the grid environment, minimising voltage deviations and network losses under dynamic wind conditions. Using the IEEE 33-bus distribution test system, the trained DQN achieved a substantial improvement in voltage regulation, reducing the average deviation from 0.041 p.u. (rule-based) to 0.014 p.u. and lowered power losses by 24.6/5 compared to traditional optimisation techniques such as Particle Swarm Optimisation (PSO) and static rule-based control. Furthermore, the DQN controller demonstrated the fastest learning convergence within 120 episodes, validating its potential for real-time adaptive voltage control. Overall, the study highlights RL as a promising, scalable solution for autonomous voltage regulation in smart grids integrated with renewables. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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9 pages, 1488 KB

Open AccessProceeding Paper

Adaptive Owl Search Optimisation for Real-Time Fault-Resilient Control of DFIG-Integrated Wind Energy Systems

by Ramesh Kumar Behara and Akshay Kumar Saha

Eng. Proc. 2026, 140(1), 57; https://doi.org/10.3390/engproc2026140057 - 5 Jun 2026

Viewed by 258

Abstract

The rapid global deployment of wind energy requires robust and efficient control strategies for doubly fed induction generator (DFIG)-based systems. Conventional proportional–integral (PI) controllers tuned by classical or metaheuristic methods often exhibit poor adaptability to turbulence, parameter drift, and grid disturbances. This paper [...] Read more.

The rapid global deployment of wind energy requires robust and efficient control strategies for doubly fed induction generator (DFIG)-based systems. Conventional proportional–integral (PI) controllers tuned by classical or metaheuristic methods often exhibit poor adaptability to turbulence, parameter drift, and grid disturbances. This paper introduces an adaptive owl search optimisation (A-OSO) algorithm for the real-time tuning of PI controllers in DFIG back-to-back converters. Unlike traditional OSO, the adaptive variant dynamically adjusts its exploration–exploitation balance based on the severity of system disturbances, enabling faster convergence and improved resilience. The study benchmarks the proposed method against particle swarm optimisation (PSO), genetic algorithm (GA), simulated annealing (SA), and owl search optimisation (OSO) simulation studies in MATLAB/Simulink, coupled with hardware-in-the-loop (HIL) tests on an FPGA platform, demonstrating that A-OSO achieves superior efficiency (97.1%), lower power losses (35 kW), faster low voltage ride-through (LVRT) recovery (less than 150 ms), and reduced total harmonic distortion (THD) (2.4%). These findings establish A-OSO as a practical, grid-compliant optimisation strategy for next-generation smart wind farms. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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10 pages, 2349 KB

Open AccessProceeding Paper

NSGA-II-Based Multi-Objective Optimisation of Solar–Battery Systems for Cost and Reliability

by Raphael I. Areola, Abayomi A. Adebiyi and Dwayne J. Reddy

Eng. Proc. 2026, 140(1), 58; https://doi.org/10.3390/engproc2026140058 - 5 Jun 2026

Viewed by 428

Abstract

Increasing grid instability and rising electricity prices highlight the need for reliable photovoltaic–battery energy storage systems (PV–BESS). This study presents a constraint-aware multi-objective optimisation framework using NSGA-II that integrates economic performance, reliability, curtailment, and battery ageing. Applied under realistic South African conditions, the [...] Read more.

Increasing grid instability and rising electricity prices highlight the need for reliable photovoltaic–battery energy storage systems (PV–BESS). This study presents a constraint-aware multi-objective optimisation framework using NSGA-II that integrates economic performance, reliability, curtailment, and battery ageing. Applied under realistic South African conditions, the optimal system achieved a levelised cost of $0.06/kWh, 97.9% reliability, 1.6% annual degradation, a net present value of $367,000, and an internal rate of return over 15%. Across regional scenarios, the framework maintained 87–91% performance consistency and improved convergence. Results demonstrate that integrating degradation and operational constraints produces more reliable, cost-effective PV–BESS designs for volatile electricity markets. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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12 pages, 2493 KB

Open AccessProceeding Paper

Enhanced Harmonic Mitigation and Reactive Power Support in Photovoltaic-Connected Power Filters Using a Robust Control Approach

by Julius Omorodion Uwagboe and Akshay Kumar Saha

Eng. Proc. 2026, 140(1), 59; https://doi.org/10.3390/engproc2026140059 - 5 Jun 2026

Viewed by 425

Abstract

The increasing integration of photovoltaic (PV) systems and nonlinear loads intensifies harmonic distortion and reactive power imbalance in modern power networks. Conventional shunt active power filters (SAPFs) often employ control strategies that perform poorly under uncertain and dynamic grid conditions. This paper develops [...] Read more.

The increasing integration of photovoltaic (PV) systems and nonlinear loads intensifies harmonic distortion and reactive power imbalance in modern power networks. Conventional shunt active power filters (SAPFs) often employ control strategies that perform poorly under uncertain and dynamic grid conditions. This paper develops a hybrid sliding mode control with disturbance observer (SMC+DOB) technique for a PV-integrated SAPF to achieve effective harmonic mitigation, reactive power compensation, and enhanced system robustness. The study models the PV-SAPF system in MATLAB/Simulink (R2025b), where the SMC ensures robust current tracking, while the DOB estimates and suppresses unknown disturbances in real-time. The controller’s performance is evaluated under varying nonlinear and reactive load conditions, as per IEEE 519-2014 standards. Simulation results show that the proposed SMC+DOB scheme reduces total harmonic distortion (THD) by 96.7%—from 31.45% to 1.05%—while maintaining DC-link voltage stability and unity power factor. The integrated control architecture enhances the dynamic performance of SAPF, providing superior harmonic suppression, fast transient recovery, and improved grid stability for PV-connected systems. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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10 pages, 1669 KB

Open AccessProceeding Paper

Comprehensive Power Park Design and Analysis of a Wind Farm Using Monte Carlo Simulation

by Nomihla Ndlela, Katleho Moloi and Musasa Kabeya

Eng. Proc. 2026, 140(1), 60; https://doi.org/10.3390/engproc2026140060 - 3 Jun 2026

Viewed by 251

Abstract

The accelerating worldwide shift toward renewable energy sources (RES) has increased the demand for reliable, efficient, and financially sound wind farm implementation. With the ongoing expansion of wind power within contemporary energy systems, the design and analysis of wind farms, frequently referred to [...] Read more.

The accelerating worldwide shift toward renewable energy sources (RES) has increased the demand for reliable, efficient, and financially sound wind farm implementation. With the ongoing expansion of wind power within contemporary energy systems, the design and analysis of wind farms, frequently referred to as Power Parks, have become progressively intricate. This study employs probabilistic analysis using Monte Carlo simulation (MCS) to analyze the network in terms of losses, energy output, and profit to ensure the network’s economic stability before it is incorporated into the grid. The results indicate that the system will maintain its reliability throughout the year, as demonstrated in the Simulation Results section where the network operates within permissible values. Furthermore, the system is deemed economically viable, as illustrated in the conclusion, which presents the profit and loss figures. This study is significant as it employs effective techniques necessary for analyzing the entire power park in terms of losses, stability, profitability, and energy output over a specified period, taking into account the variability and uncertainty of wind conditions. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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13 pages, 3323 KB

Open AccessProceeding Paper

Medium Voltage Underground Cables ANN Real-Time Detection and Classification Technique

by Sifiso Zikhali, Nomihla Ndlela, Ntombenhle Mazibuko and Kabulo Loji

Eng. Proc. 2026, 140(1), 61; https://doi.org/10.3390/engproc2026140061 - 11 Jun 2026

Viewed by 390

Abstract

This paper introduces a cutting-edge, real-time fault detection and classification method powered by artificial neural networks (ANNs), designed to significantly boost the reliability and sustainability of medium voltage (MV) underground cable distribution systems. The research analyzes the electrical and physical properties of MV [...] Read more.

This paper introduces a cutting-edge, real-time fault detection and classification method powered by artificial neural networks (ANNs), designed to significantly boost the reliability and sustainability of medium voltage (MV) underground cable distribution systems. The research analyzes the electrical and physical properties of MV underground cables and common fault types, including line-to-line, line-to-ground, and double line-to-ground faults. A simulation model is developed using MATLAB/Simulink R2025b to generate fault scenarios under various operating conditions. Raw data in the form of Voltage and current signals are generated and processed to extract significant features, which are then fed into the ANN model. The ANN is trained using a supervised learning approach, using a dataset of labeled fault instances. Key parameters like hidden layers, activation functions, and learning rates are optimized to improve the model’s performance. The results show that the proposed ANN-based fault detection technique achieves over 95% accuracy in detecting and classifying faults in real-time, with minimal computational delay. Comparative analysis with conventional fault classification techniques demonstrates the superiority of the ANN model in handling noisy and non-linear data. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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11 pages, 5539 KB

Open AccessProceeding Paper

Electrical Properties of Old Gold Mine Tailings and Their Suitability as Conductive Backfill for Earthing Applications

by Sithole Lungelo Phinda and Chandima Gomes

Eng. Proc. 2026, 140(1), 62; https://doi.org/10.3390/engproc2026140062 - 11 Jun 2026

Viewed by 398

Abstract

This study investigates the electrical properties of gold mine tailings from the Soweto mining region to assess their potential as a low-cost and sustainable backfill material for grounding systems. Samples were collected from historical mine dumps, oven-dried at 70 °C for 24 h [...] Read more.

This study investigates the electrical properties of gold mine tailings from the Soweto mining region to assess their potential as a low-cost and sustainable backfill material for grounding systems. Samples were collected from historical mine dumps, oven-dried at 70 °C for 24 h to determine dry density and baseline moisture content, and reconstituted to controlled moisture levels of 5–25% by mass. Bulk electrical resistivity was measured using the Wenner four-electrode method in accordance with ASTM G57-06. The results reveal a strong inverse correlation between moisture content and resistivity. At low moisture content (≈5%), resistivity exceeded measurable limits, indicating poor ionic conduction, whereas increasing moisture content led to a substantial reduction in resistivity, reaching an average value of approximately 10 Ω at 25% moisture due to improved pore water continuity and ionic mobility. These findings demonstrate that moisture-conditioned gold mine tailings can achieve electrical performance comparable to that of conventional grounding enhancement materials while offering notable economic and environmental benefits. Owing to their local availability and waste re-utilisation potential, the tailings present a technically feasible and environmentally responsible solution for improving earthing performance in high-resistivity soils. Further work should examine long-term field performance, corrosion effects, and leaching behaviour. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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8 pages, 1018 KB

Open AccessProceeding Paper

Frequency Enhancement for Distributed Wind Generators Using Energy Storage Systems

by Sydeny Madenga, Thapelo Mosetlhe and Adedayo Ademola Yusuff

Eng. Proc. 2026, 140(1), 63; https://doi.org/10.3390/engproc2026140063 - 12 Jun 2026

Viewed by 211

Abstract

Power system operators globally face an ongoing challenge of maintaining a balance between electricity supply and load demand. This is a task which has been made increasingly complex by variability inherent in both generation sources and consumer loads. The balancing act is resource [...] Read more.

Power system operators globally face an ongoing challenge of maintaining a balance between electricity supply and load demand. This is a task which has been made increasingly complex by variability inherent in both generation sources and consumer loads. The balancing act is resource intensive, costly, and is critical for preventing frequency deviations that could destabilize the entire network, which can lead to blackouts and equipment damage. The intermittent nature caused by unpredictable wind speeds adds more challenges by introducing rapid fluctuations that system operators may struggle to mitigate. Energy storage systems (ESSs) have shown potential in addressing these challenges by offering flexible buffering capabilities to smooth out imbalances and enhance frequency stability. In this research, the impact of fluctuating wind speeds on power system frequency stability was analyzed. Subsequently, a hybrid energy storage system that integrates batteries for sustained energy discharge and super capacitors for rapid high-power responses was added. This enabled the system to handle mismatches effectively. The results show a 66% reduction in frequency deviations during wind fluctuations compared to baseline scenarios without storage. This improvement facilitates improved integration of renewable energy sources by allowing higher penetration levels without compromising stability. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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7 pages, 195 KB

Open AccessProceeding Paper

A Review of Emerging Dielectric Fluids for Sustainable and Resilient Power Transformers

by Vusumuzi Sibeko

Eng. Proc. 2026, 140(1), 64; https://doi.org/10.3390/engproc2026140064 - 12 Jun 2026

Viewed by 282

Abstract

This paper reviews emerging dielectric fluids for power transformers, including natural and synthetic esters, silicone oils, gas-to-liquid oils, and nanofluids, driven by environmental regulations, fire safety concerns, and the need for extended asset life. The review synthesizes technical data from standards and field [...] Read more.

This paper reviews emerging dielectric fluids for power transformers, including natural and synthetic esters, silicone oils, gas-to-liquid oils, and nanofluids, driven by environmental regulations, fire safety concerns, and the need for extended asset life. The review synthesizes technical data from standards and field experience, including a case study of an Eskom transformer energized in 2016 with natural ester fluid. Analysis confirms these fluids offer significant benefits in fire safety, biodegradability, and dielectric performance, with the case study demonstrating natural esters’ effectiveness in preserving solid insulation. However, trade-offs involving cost, material compatibility, and operational protocols require careful management. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

10 pages, 1309 KB

Open AccessProceeding Paper

Design and Efficiency Analysis of Flywheel Energy Storage Systems Employing PMSM and AC-BLDC Machines

by Willy Stephane Ngaha, John Van Coller and Chandima Gomes

Eng. Proc. 2026, 140(1), 65; https://doi.org/10.3390/engproc2026140065 - 15 Jun 2026

Viewed by 344

Abstract

This paper presents a comparative analysis of Flywheel Energy Storage Systems (FESS) employing Permanent Magnet Synchronous Machines (PMSMs) and AC Brushless DC (AC-BLDC) machines for fast and efficient frequency regulation. The study examines their electromechanical behavior during the key operational stages of charging, [...] Read more.

This paper presents a comparative analysis of Flywheel Energy Storage Systems (FESS) employing Permanent Magnet Synchronous Machines (PMSMs) and AC Brushless DC (AC-BLDC) machines for fast and efficient frequency regulation. The study examines their electromechanical behavior during the key operational stages of charging, standby, and discharging, with a focus on mitigating inrush current and enhancing overall system efficiency. MATLAB/Simulink models were developed to evaluate machine dynamics, electromagnetic behavior, and harmonic distortion during their operation. The results show that electromagnetic effects, particularly inrush current, commutation harmonics, and inverter limitations, significantly influence torque smoothness, efficiency, and overall system performance. PMSMs demonstrate superior torque quality, lower Total Harmonic Distortion (THD), and more stable energy conversion under Field-oriented Control (FOC), making it well suited for high-performance FESS applications. In contrast, the AC-BLDC machine exhibits higher torque ripple and elevated THD due to six-step commutation but offers a simpler drive topology and cost advantages. The findings offer practical insights for selecting machines and controllers in high-speed FESS designs and emphasize the importance of mitigating transient electromagnetic effects to enhance efficiency and reliability in modern grid support applications. Improved modeling incorporating magnetic saturation, frequency-dependent iron losses, and inverter constraints is essential for accurate performance prediction. Future work includes Hardware-In-the-Loop (HIL), Power-HIL validation, and DlgSILENT PowerFactory co-simulation to confirm dynamic performance under grid-connected operation. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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13 pages, 2483 KB

Open AccessProceeding Paper

Using Tan Delta and Dielectric Constant as Criterion for the Selection of Suitable Insulation Materials for HV Cable Joints

by Noluthando Ntshangase, Bonginkosi Mpinga, Salman Minhas and Cuthbert Nyamupangedengu

Eng. Proc. 2026, 140(1), 66; https://doi.org/10.3390/engproc2026140066 - 15 Jun 2026

Viewed by 365

Abstract

High-voltage cable joints are critical components where electric stress concentration often leads to insulation failure. This study evaluated three materials to find optimal configurations for controlling stress in 33 kV applications: PVC tape, stress-grading mastic, and semiconductive rubber tape, with initial relative permittivities [...] Read more.

High-voltage cable joints are critical components where electric stress concentration often leads to insulation failure. This study evaluated three materials to find optimal configurations for controlling stress in 33 kV applications: PVC tape, stress-grading mastic, and semiconductive rubber tape, with initial relative permittivities of 2.96, 2.66, and 5.07, respectively. Dielectric measurements using a Schering Bridge at voltages of up to 3700 V determined material properties and breakdown characteristics. Semiconductive rubber withstood the highest voltage of 3700 V, while mastic failed at 1350 V. Finite element simulations showed that baseline configurations without proper insulation had a peak stress of 4.3 kV/mm. Simulations of individual materials identified non-linear resistive compounds, such as ZnO-based materials and carbon-black-filled polymers, as the most effective for stress control at conductor interfaces. A three-layer graded design, arranging materials by decreasing permittivity from the conductor outward, reduced the peak stress by 33% to 2.9 kV/mm. These results demonstrate that strategic permittivity grading combined with appropriate material selection ensures uniform field distribution and improved reliability in HV cable joints. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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15 pages, 4622 KB

Open AccessProceeding Paper

Saline Water Batteries as a Possibility for Accessible Energy

by Ruth Mc Cormick, Zvikomborero Chirozvi and James Braid

Eng. Proc. 2026, 140(1), 67; https://doi.org/10.3390/engproc2026140067 - 15 Jun 2026

Viewed by 512

Abstract

Saltwater batteries can be made using brine from the desalination of seawater for low-cost energy storage. This study investigates the performance characteristics of saltwater batteries for potential off-grid energy applications. The systematic investigation of 15 electrode pairings from six electrodes (copper, iron, zinc, [...] Read more.

Saltwater batteries can be made using brine from the desalination of seawater for low-cost energy storage. This study investigates the performance characteristics of saltwater batteries for potential off-grid energy applications. The systematic investigation of 15 electrode pairings from six electrodes (copper, iron, zinc, graphite, aluminium, and tin) across eleven concentration levels, combined with studies on electrode geometry, spacing, and volume, provides comprehensive insights into galvanic cell behaviour for saltwater batteries. Results indicate that the open-circuit voltage (OCV) is primarily determined by electrode potential differences rather than salt concentration, with zinc-carbon and aluminium-carbon pairings producing the highest voltages (1.1–1.2 V). Short circuit current increases with salt concentration up to approximately 30% (0.3 M), which is the saturation point, beyond which ion mobility decreases. This study demonstrates that electrode geometry and surface area significantly affect current density and internal resistance, while increased electrode spacing raises internal resistance and reduces maximum current output. These findings contribute to understanding the feasibility and performance characteristics of saltwater batteries as accessible energy sources using recyclable materials. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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8 pages, 5530 KB

Open AccessProceeding Paper

Implementation of an IEC 61850 Sampled-Value-Based Line Protection Scheme for a 132 kV System

by Mathias Natangwe Shimwetheleni and Senthil Krishnamurthy

Eng. Proc. 2026, 140(1), 68; https://doi.org/10.3390/engproc2026140068 - 16 Jun 2026

Viewed by 435

Abstract

The paper details the implementation and experimental validation of an IEC 61850-9-2 sampled value (SV)-based distance protection scheme for a 132 kV transmission line. Instead of conventional analog interfaces, we propose a scheme that uses a digital process bus to stream time-synchronized voltage [...] Read more.

The paper details the implementation and experimental validation of an IEC 61850-9-2 sampled value (SV)-based distance protection scheme for a 132 kV transmission line. Instead of conventional analog interfaces, we propose a scheme that uses a digital process bus to stream time-synchronized voltage and current measurements from instrument transformers to protection relays. A laboratory-scale setup was developed, in which an SEL 401 merging unit samples currents and voltages injected by an OMICRON CMC 356 and publishes them as SV messages to an SEL 421 distance relay. This work demonstrates how IEC 61850-9-2 can be practically applied to modernize transmission line protection and enhance overall grid reliability and resilience. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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11 pages, 1890 KB

Open AccessProceeding Paper

The Effect of Dissolved Gasses on the Insulating Properties of Natural Ester and Mineral Insulating Oils

by Thandokuhle Mathonsi, Bandile Hlatshwayo, Salman Minhas and Chandima Gomes

Eng. Proc. 2026, 140(1), 69; https://doi.org/10.3390/engproc2026140069 - 16 Jun 2026

Viewed by 302

Abstract

This paper presents an investigation into the effect of dissolved gases (DGs) on the insulating properties, such as breakdown strength, of Midel EN 1204 natural ester oil and Poweroil TO 1020 60U mineral oils. The gasses were generated by simulating thermal fault/s at [...] Read more.

This paper presents an investigation into the effect of dissolved gases (DGs) on the insulating properties, such as breakdown strength, of Midel EN 1204 natural ester oil and Poweroil TO 1020 60U mineral oils. The gasses were generated by simulating thermal fault/s at 130 °C, 210 °C, 340 °C, 400 °C, and 450 °C. Dissolved gas analysis (DGA) was conducted according to IEC 60567 to determine the concentrations of H₂, CH₄, C₂H₆, C₂H₄, C₂H₂, and CO in each of the twelve oil samples. Moisture was measured using the Karl Fischer Method according to IEC 60814. The breakdown voltage (BDV) was measured according to IEC 60156. The results show that total dissolved gas concentration and rate of rise increased with fault temperature in both oils. For this relatively short time experiment, the rise in concentration of DGs had minimal effect. The overall BDV 73.7 kV (virgin ester oil BDV) increased to 76.3 kV at 450 °C for natural ester oil, whereas the BDV of mineral oil decreased from 68.7 kV to 63.1 kV. These findings showed that natural ester oil has better insulation stability under thermal stress. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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9 pages, 206 KB

Open AccessProceeding Paper

Reimagining Grid Flexibility in a Constrained Power System: A Techno-Economic Evaluation of Battery Storage, Coal Performance, and Transmission Bottlenecks in South Africa

by Keith Katyora and Komla Folly

Eng. Proc. 2026, 140(1), 70; https://doi.org/10.3390/engproc2026140070 - 17 Jun 2026

Viewed by 513

Abstract

South Africa’s power system has been characterised in recent years by declining coal fleet performance, accelerated renewable energy deployment because of system unreliability, and persistent delays in transmission expansion to replace ageing infrastructure (and enable new generation). These structural pressures have created a [...] Read more.

South Africa’s power system has been characterised in recent years by declining coal fleet performance, accelerated renewable energy deployment because of system unreliability, and persistent delays in transmission expansion to replace ageing infrastructure (and enable new generation). These structural pressures have created a growing need for grid flexibility, particularly as renewable energy becomes the dominant source of new generation. This paper presents a techno-economic assessment of battery energy systems (BESSs) within a constrained national context, using three scenarios: a policy-aligned baseline (0), high-demand/moderate renewable growth (1), and a constrained transition pathway (2). They were modelled using a validated least-cost capacity expansion and dispatch framework incorporating updated assumptions on coal availability, transmission delivery constraints, renewable build caps, and demand trajectories. The results show that each scenario produces a distinct system stress mechanism. In Scenario 1, rapid renewable expansion leads to surplus-driven curtailment and increased flexibility requirements, with BESS delivering substantial operational value. In Scenario 2, coal fleet underperformance, procurement limits, and transmission congestion create energy-deficit conditions despite low demand, resulting in the highest unserved energy and congestion-driven curtailment. However, Scenario 0 is comparatively less stressed, but displays minor energy adequacy shortfalls after 2030, indicating that the baseline is not fully adequate under strict planning criteria. Ultimately, across all scenarios, storage and transmission expansions are shown to be complementary investments, which are jointly required to mitigate system-wide inefficiencies. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

9 pages, 1146 KB

Open AccessProceeding Paper

Unit Commitment Dispatch Problem with Wind Energy Resources Using Mixed-Integer Linear Programming Method

by Nombini Sarah Mafilika and Senthil Krishnamurthy

Eng. Proc. 2026, 140(1), 71; https://doi.org/10.3390/engproc2026140071 - 18 Jun 2026

Viewed by 439

Abstract

This paper presents a two-stage stochastic unit commitment model to mitigate the costs and reliability effects of high wind energy penetration into the power system. Wind energy variability/uncertainty is explored through this system. Mixed-integer linear programming (MILP) is used to solve the model [...] Read more.

This paper presents a two-stage stochastic unit commitment model to mitigate the costs and reliability effects of high wind energy penetration into the power system. Wind energy variability/uncertainty is explored through this system. Mixed-integer linear programming (MILP) is used to solve the model and find optimal unit commitment and dispatch variables under uncertainty in wind conditions. The model champions reduced reliance on deterministic approaches, lowered costs, increased wind utilization, and provides reliable systems that can sustain 24 h. Wind energy is expected to constitute a significant share of future electricity generation portfolios; however, its inherent intermittency and variability often lead to mismatches between energy supply and demand. This uncertainty complicates generation scheduling decisions, particularly in determining which power plants to commit, their operating durations, and the optimal dispatch timing. Consequently, advanced optimization strategies are required to ensure efficient and reliable system operation. The proposed approach provides a structured, robust framework for optimal generation scheduling and resource allocation, even under limited wind availability. By enhancing the integration of wind energy into the power system, the method minimizes operational costs, improves resource utilization, and maintains system reliability and stability. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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11 pages, 1767 KB

Open AccessProceeding Paper

Data-Driven ANN Model Development for Maximum Power Point Estimation in PV Panel Under Partial Shading Conditions

by Mog Akeem Isaacs and Senthil Krishnamurthy

Eng. Proc. 2026, 140(1), 72; https://doi.org/10.3390/engproc2026140072 - 25 Jun 2026

Viewed by 256

Abstract

This paper presents a novel approach to designing and implementing an Artificial Neural Network (ANN) for maximum power point tracking (MPPT), trained solely on unshaded photovoltaic (PV) manufacturer datasheets and capable of tracking and predicting the maximum power point (MPP) under changing shading [...] Read more.

This paper presents a novel approach to designing and implementing an Artificial Neural Network (ANN) for maximum power point tracking (MPPT), trained solely on unshaded photovoltaic (PV) manufacturer datasheets and capable of tracking and predicting the maximum power point (MPP) under changing shading conditions. This is also known as partial shading conditions (PSC). PSC arises when shade covers sections of the PV panel due to clouds, trees, dust, or man-made objects such as tall buildings. The proposed ANN-based MPPT technique addresses a common issue faced by conventional MPPT methods under PSC: inaccurate MPPT. PSC induces oscillations on the power-to-voltage curve, resulting in multiple local maxima (LMPPs). However, existing ANN-based MPPT methods are developed and trained on shaded PV datasets. This Neural Network (NN) tracking method complicates the training, development, and implementation processes. It increases the cost of development and requires physical, real-world data collection that requires hardware and a lot of time. All this can be avoided with unshaded PV datasheets. The input parameters used to train the model are temperature (T) and irradiance (G), and the output parameters are maximum power (Pmp) and maximum voltage (Vmp). The ANN-based MPPT technique demonstrated strong performance, accurately predicting the global MPP (GMPP) under PSC with high correlation and low prediction error. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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12 pages, 1628 KB

Open AccessProceeding Paper

Evaluating Artificial Intelligence-Based Models for Personal Protective Equipment Usage Detection in Powerline and Renewable Energy Construction Environments

by Isabelle Makembe, Riaz Vajeth, Nishanth Parus, Steve Apps, Emeil Pillay, Siyabonga Mchunu and Chandima Gomes

Eng. Proc. 2026, 140(1), 73; https://doi.org/10.3390/engproc2026140073 - 29 Jun 2026

Viewed by 255

Abstract

Personal Protective Equipment (PPE) compliance is critical in powerline and renewable energy construction projects, yet non-adherence remains common and difficult to monitor manually. This paper presents an automated PPE detection system using an Artificial Intelligence based object detection model applied to actual site [...] Read more.

Personal Protective Equipment (PPE) compliance is critical in powerline and renewable energy construction projects, yet non-adherence remains common and difficult to monitor manually. This paper presents an automated PPE detection system using an Artificial Intelligence based object detection model applied to actual site overhead drone imagery. The aim was to identify key non-compliance categories such as the non-use of hardhats, reflective vests, long pants, T-shirts and long sleeve shirts. A custom dataset was developed from aerial and ground footage and enhanced through standard annotation and augmentation techniques. Model performance was evaluated using mAP, precision, recall, and confidence-based metrics, demonstrating reliable detection across most PPE classes despite environmental and distance-related challenges. The study shows the potential of AI-assisted, drone-based monitoring to enhance safety oversight on powerline and renewable energy construction sites. It further outlines future work to improve dataset diversity, resolution, and real-time deployment. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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12 pages, 2039 KB

Open AccessProceeding Paper

Review of Hybrid MPPT Algorithms for Improved Solar Energy Extraction in Low Earth Orbit

by Khumbulani Masinga, Musasa Kabeya and Welcome Khulekani Ntuli

Eng. Proc. 2026, 140(1), 74; https://doi.org/10.3390/engproc2026140074 - 29 Jun 2026

Viewed by 323

Abstract

The solar energy generation in Low Earth Orbit is experiencing rapid periodic fluctuations in irradiance and temperature due to orbital motion, eclipse transitions, and thermal cycling. All these conditions significantly affect the efficiency of conventional system algorithms. The hybrid MPPT strategies that combine [...] Read more.

The solar energy generation in Low Earth Orbit is experiencing rapid periodic fluctuations in irradiance and temperature due to orbital motion, eclipse transitions, and thermal cycling. All these conditions significantly affect the efficiency of conventional system algorithms. The hybrid MPPT strategies that combine classical methods and intelligent controllers have promised a good solution for improving tracking speeds, reducing steady-state oscillations, and increasing energy extraction under high variation conditions. This paper presents a structured review of hybrid MPPT algorithms suitable for LEO applications under these control strategies, Incremental-Artificial Neural Network (INC-ANN) and Perturb & Observe-Fuzzy Logic Control (P&O-FLC). The review highlights their advantages, limitations, computational specifications, and suitability for LEO solar power subsystems. This work forms an ongoing study since the simulation of this subsystem is not yet available. This paper aims to establish the technical foundation and methodology direction for the future implementation and evaluation of hybrid MPPT techniques under simulated LEO conditions. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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12 pages, 630 KB

Open AccessProceeding Paper

A Utility-Driven Assessment of LoRaWAN Application for Secure Remote Monitoring in Smart Grid Systems

by Zephania Philani Khumalo and Resham Singh

Eng. Proc. 2026, 140(1), 75; https://doi.org/10.3390/engproc2026140075 - 9 Jul 2026

Viewed by 288

Abstract

Low Power Wide Area Networks (LPWANs) are essential for enabling Internet-of-Things (IoT) technologies in utility environments. Utilities can leverage these networks to monitor critical remote assets, especially where mobile technologies are unsuitable due to poor power efficiency or insufficient coverage. This paper investigates [...] Read more.

Low Power Wide Area Networks (LPWANs) are essential for enabling Internet-of-Things (IoT) technologies in utility environments. Utilities can leverage these networks to monitor critical remote assets, especially where mobile technologies are unsuitable due to poor power efficiency or insufficient coverage. This paper investigates the use of Long Range (LoRa) Wide Area Network (LoRaWAN) technology as an LPWAN solution for remote grid monitoring within the eThekwini Municipal Area. In addition to evaluating range performance (distance) and the packet reception ratio (PRR) across configurable parameters, such as spreading factor and transmit power, this paper introduces a data-packet security extension for LoRaWAN using NTRU post-quantum cryptography (PQC). The proposed security enhancement provides quantum-resistant encryption for application-layer payloads without violating LoRaWAN duty-cycle constraints or significantly increasing energy consumption. Field tests were performed at 11 geographically dispersed substations using a handheld LoRa device. Test signals were transmitted at four power levels (2 dBm, 8 dBm, 14 dBm, and 20 dBm) and spreading factors (SF7–SF12). Results show that the public LoRaWAN network can achieve communication distances of approximately 30 km in an urban environment, with PRR strongly dependent on SFs and transmit power. The integration of lightweight NTRU-protected payloads was found to be feasible for typical smart grid use cases involving small data packets (1–13 bytes). Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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18 pages, 3968 KB

Open AccessProceeding Paper

Design and Modeling of a Shunt Capacitor-Boosted Z-Source Inverter (SCB-ZSI)

by Mbulelo S. P. Ngongoma and Zephania Philani Khumalo

Eng. Proc. 2026, 140(1), 76; https://doi.org/10.3390/engproc2026140076 - 27 Jul 2026

Viewed by 24

Abstract

Various inverter applications such as electronic vehicles, renewable energy systems, and uninterrupted power supplies have been the motive behind the increasing focus on the DC-AC inverters field. Therefore, DC-AC inverters have been evolving with the recent topology being the Z-source inverters (ZSIs). Though [...] Read more.

Various inverter applications such as electronic vehicles, renewable energy systems, and uninterrupted power supplies have been the motive behind the increasing focus on the DC-AC inverters field. Therefore, DC-AC inverters have been evolving with the recent topology being the Z-source inverters (ZSIs). Though the ZSI overcame most of the limitations faced by the previous topologies such as the Voltage-Source Inverters (VSIs) and Current-Source Inverters (CSIs), they had shortcomings such as the increase in switching devices’ voltage stress and hence the deterioration of power quality with the increase in the boost factor. As a result, several ZSI-based topologies have been proposed in the literature to further improve the performance of a ZSI. This paper also proposes a different Z-source inverter topology called the Shunt Capacitor-Boosted Z-Source Inverter (SCB-ZSI) which seeks to improve the boost factor and lower the voltage stress. This inverter strategically adds two shunt capacitors on the impedance network of a traditional Z-source inverter, hence the Shunt Capacitor-Boosted-ZSI. The SCB-ZSI was mathematically modeled and simulated on MATLAB Simulink R2024a version. The SCB-ZSI was found to have a high boost factor compared to the ZSI for the same input DC voltage and modulation index. The SCB-ZSI was also found to incur less switching voltage stress across the switching devices compared to the ZSI for the same input DC voltage and modulation index. The simulation test results showed that the selection of shunt capacitors of a ZSI at 1% of those of the original ZSI improves the boost factor by 56% and reduces the switch voltage stress ration by 40% on an SCB-ZSI for the same set of input parameters. Though the SCB-ZSI is one of the promising ZSI-based inverter topologies, more work still has to be done before they can be industrially applied, such as developing an algorithm to design the shunt capacitors. Full article

(This article belongs to the Proceedings of The 34th Southern African Universities Power Engineering Conference (SAUPEC 2026))

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