Search Results (311)

Renewable energy systems dominated by powered electronic devices generally exhibit weak disturbance tolerance and limited grid-support capability. Following the blocking of a flexible DC transmission system, emergency load shedding in renewable-rich grid regions may induce overvoltage or undervoltage at the point of common coupling, forcing renewable energy units into a voltage ride-through state. This, in turn, reduces their active power output and threatens the frequency stability of the power system. To address this issue, this paper proposes an emergency load-shedding decision model based on a constrained Markov decision process (CMDP). First, an emergency frequency control model for AC–DC hybrid power systems is established within the Markov decision process framework, thereby formulating power system frequency stability control as a Markov decision problem. Second, Lagrange multipliers are introduced into the CMDP framework to transform the constrained optimization problem with security constraints into an unconstrained objective optimization problem. Finally, the Proximal Policy Optimization (PPO) algorithm is adopted to accelerate the training process and improve the decision accuracy of the intelligent agent. The simulation results, based on the modified IEEE 39-bus system, demonstrate that, compared with the traditional contingency strategy and the conventional Markov decision algorithm, the proposed load-shedding strategy can satisfy system frequency stability requirements, effectively avoid voltage violations at renewable energy grid-connection points, and minimize the total load shedding amount. Full article

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

In response to issues such as the strong output power fluctuations of photovoltaic units caused by external environmental factors like solar irradiance, and the susceptibility of traditional control methods to grid disconnection incidents under significant system disturbances, a control strategy based on cascaded linear-nonlinear Extended State Observer (ESO) Active Disturbance Rejection Control (ADRC) is proposed for photovoltaic-storage hybrid systems. A model of the photovoltaic-storage hybrid system is constructed to achieve high- and low-frequency power distribution among energy storage units. The cascaded linear-nonlinear ESO-based ADRC is employed to estimate and compensate for system disturbances in real-time. Simulation results verify the effectiveness of the proposed control strategy, demonstrating a reduction in frequency deviation by 0.08 Hz under normal frequency dips. More critically, during severe AC bus voltage sags, the proposed strategy prevents the system frequency from falling below 49.0 Hz, thereby avoiding the under-frequency load shedding (UFLS) that occurs with conventional PI control. Additionally, the DC bus voltage fluctuation is limited to within 8 V under grid disturbances, and unlike the severe oscillations exhibited by PI control during system recovery, the proposed cascade strategy ensures an immediate and smooth transient response. Full article

The increasing penetration of converter-interfaced renewable energy resources is accelerating the transition of conventional distribution networks toward hybrid AC/DC architectures, where photovoltaic generation, battery energy storage, electric mobility, and mixed AC/DC loads are coupled through multiple power electronic interfaces. While these architectures offer important advantages in flexibility and integration efficiency, they also introduce tighter interactions between AC-side and DC-side operating behavior, making coordinated assessment increasingly important under variable operating conditions. Despite growing interest in hybrid AC/DC systems, comparative studies that jointly examine system-level stability and voltage-quality-related behavior across renewable penetration levels and stressed operating scenarios remain limited. This paper proposes a reduced-order comparative screening framework for renewable-rich hybrid AC/DC distribution systems, using stability- and voltage-quality-related indicators based on a representative reduced-order benchmark model. The adopted framework combines scenario-based simulation with unified AC-side, DC-side, transient, and composite performance indicators to evaluate how different converter coordination strategies influence operating robustness under renewable intermittency, abrupt load changes, converter operating-point variations, and different renewable penetration levels. The considered indicators include voltage deviation, overshoot, violation duration, transient fluctuation, converter utilization, and composite operating-robustness measures; they are intended as system-level voltage-dynamics proxies rather than as a complete harmonic or standards-based power-quality assessment. The results indicate that adaptive coordinated control provides the strongest DC-side robustness under stressed conditions, whereas droop-based coordination often offers a favorable practical compromise between AC-side and DC-side performance. The analysis also reveals a clear trade-off between DC-side regulation and AC-side voltage-quality-related behavior, highlighting the need for joint multi-domain evaluation. In particular, the improved DC-side robustness obtained with adaptive coordination is accompanied by slightly higher AC-side voltage-quality-related deviations in several scenarios. Within the scope of the adopted reduced-order benchmark, the proposed framework provides a practical and reproducible basis for identifying critical operating regions and for supporting higher-fidelity future studies on robust renewable integration in hybrid AC/DC distribution networks. Full article

Building electrical systems are becoming increasingly complex as designers evaluate AC, DC, and hybrid distribution architectures, integrate distributed energy resources, and maintain alignment with evolving performance and reliability goals. Existing design tools are typically limited, non-interoperable, and unable to support continuous modeling across design phases, resulting in fragmented workflows and significant manual effort. This paper presents a template-based workflow that automates the generation of high-fidelity Modelica simulation models of building electrical systems from semantic models. The workflow supports both basic safety analysis and the power-flow simulation of AC, DC, and hybrid system architectures. A Python-based middleware (RDF2EMO) was developed to automate data extraction, template instantiation, and parametric model generation, enabling rapid and consistent iteration through schematic design, design development, and construction documentation phases. Verification of the middleware automation (RDF2EMO) using a reference medium-sized office building demonstrates that the generated Modelica model is internally consistent with the Building Information Model. A case study demonstrates how the workflow supports design decisions, including system architecture selection, equipment sizing impacts and optimization, and reliability analysis. Full article

This study presents a comprehensive techno-economic and environmental evaluation of ten standalone solar-powered mobile charging station configurations for mini electric vehicles (MEVs) in Kuwait, simulated using HOMER Pro (v3.18.4). The configurations span DC–AC and pure DC-bus architectures, fixed and tracking photovoltaic (PV) systems, hybrid designs incorporating diesel generator backup, and fully renewable zero-emission systems. All configurations were evaluated under identical load demand (6460 kWh/year), solar resource, and economic assumptions derived from Kuwait’s desert climate at Al-Wafra farms (28°33′52.7″ N, 48°03′45.8″ E, annual average GHI = 5.49 kWh·m⁻²·day⁻¹). Performance was assessed using Net Present Cost (NPC), Levelised Cost of Energy (LCOE), annual PV energy production, CO₂ emissions, Energy Production Density (EPD), Renewable Fraction (RF), and the PV Energy Production-to-Load Ratio (PV-EPTLR). The results demonstrate that two-axis tracking on a DC-bank architecture without a generator (System 8) achieves the highest annual PV output of 13,635 kWh/year, representing a 36% increase over a fixed-tilt DC-bank system while eliminating 100% of operational CO₂ emissions. Among the hybrid configurations, vertical single-axis tracking on a DC-bank architecture with generator backup (System 6) yields the lowest lifecycle cost (NPC = USD 6271.8; LCOE = 0.0751 USD/kWh), representing a 57% reduction relative to the fixed-tilt DC–AC baseline. EPD analysis confirms that tracking-based systems improve structural energy efficiency by up to 36%, making them particularly suitable for mobile and weight-constrained deployments. The findings provide actionable guidance for deploying sustainable off-grid MEV charging infrastructure in regions with limited grid access, offering a scalable pathway toward zero-emission rural transportation in solar-rich arid environments. The study further provides a systematic comparison between DC–AC and pure DC-bank charging architectures under identical operating conditions. Full article

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

With the advancement of carbon peaking and carbon neutrality goals, the increasing penetration of renewable energy sources such as wind and photovoltaic power poses severe challenges to the power supply reliability of AC/DC hybrid distribution networks due to their fluctuating, intermittent, and stochastic outputs. This paper proposes a reliability assessment method for AC/DC hybrid distribution networks under large-scale renewable energy integration based on clustering of typical operating scenarios. The net load duration curve is adopted as the feature variable to characterize typical operating scenarios. An improved t-distributed Stochastic Neighbor Embedding (t-SNE) nonlinear dimensionality reduction method with Kullback–Leibler (KL) divergence elbow correction is proposed for effective reduction of high-dimensional time-series data. An adaptive Density-Based Spatial Clustering of Applications with Noise (DBSCAN) parameter optimization method based on the k-nearest-neighbor curve and a secondary K-means clustering method based on entropy-weighted multi-objective optimization are further developed, forming a hybrid t-SNE-DBSCAN–K-means clustering algorithm. The power supply reliability is then assessed based on the clustered typical operating scenarios. A typical AC/DC hybrid distribution network is used as the test system. Results show that the DB index of the proposed clustering method improves by at least 22% compared with conventional methods, the maximum relative error between the typical-day-based and full time-series simulation results is less than 6%, and the computational efficiency improves by about 8.8 times, achieving a good balance between accuracy and efficiency. Full article

The growing integration of solar, wind and battery energy storage (BES) of the microgrids (MGs) has increased the necessity of real-time energy management, especially in the multi-microgrid (multi-MG) setting, where the generation and the load change stochastically. This paper presents a Java Agent DEvelopment (JADE)-based Multi-Agent System (MAS) for real-time energy management of a low-voltage hybrid multi-MG system incorporating solar photovoltaic (PV), wind generation, and battery energy storage (BES). The proposed framework’s novelty lies in its physical campus-scale hardware deployment—validated across four operating scenarios (single MG off-grid, single MG on-grid, dual MG off-grid, and dual MG on-grid)—combined with autonomous inter-MG power sharing, which distinguishes it from existing simulation-only MAS-based microgrid studies. The suggested framework facilitates decentralized communication between interconnected MGs and the utility AC grid to facilitate the proper management of power flow, its exchange, and the reliability of the system. The intelligent agents are used to coordinate solar, wind, BES, and load changes in order to adjust to changing demand conditions. The system is physically implemented on a campus rooftop with two 1 kW solar PV arrays and two 1.5 kW wind turbine generators, each paired with a 24 V, 150 Ah battery bank, operating on a 24 V DC bus. Results across 24 h real operational profiles demonstrate effective power balance maintenance, renewable energy maximization, and constraint-compliant battery operation (SOC is bounded within 20–90%). A direct comparison with a conventional centralized JavaScript-based EMS confirms equivalent dispatch accuracy while demonstrating superior scalability, fault tolerance, and modularity of the proposed JADE MAS architecture. Full article

To address the insufficient frequency-support capability, the difficulty of multi-terminal power coordination, and the constraints on DC-voltage fluctuations in flexible DC transmission systems under weak-grid interconnection, this paper conducts a simulation-based control strategy study. First, based on the coupling relationship between AC frequency and DC voltage, an inertia-enhanced grid-forming/VSG control method is proposed, enabling converter stations to use DC-link capacitor energy to provide transient frequency support during the initial stage of a disturbance. Second, for multi-terminal flexible DC systems, an adaptive U-P-f dual-droop distributed control strategy is designed to coordinate unbalanced power sharing among multiple converter stations and to limit the DC-voltage deviation generated during frequency support. In this paper, a hybrid half-bridge/full-bridge MMC is adopted as a fixed-converter simulation platform, rather than being treated as an object of systematic topology optimization. Finally, a four-terminal MMC-HVDC simulation model is established in MATLAB/Simulink, and the proposed control strategy is evaluated under weak-grid step-load disturbances, different short-circuit-ratio conditions, and continuous pseudo-random load disturbance scenarios. Simulation results show that, under the tested operating conditions, the proposed method can reduce the maximum frequency deviation, suppress DC-voltage fluctuations, and improve the power-sharing process among multi-terminal converter stations compared with conventional VSG control and fixed-droop control. Full article

High-voltage direct current (HVDC) transmission systems are increasingly used for long-distance power transmission and the integration of renewable energy sources. In such systems, outdoor insulators are exposed to combined electrical stresses, including steady DC voltage, transient overvoltages, and environmental contamination, which can significantly influence leakage current behaviour and insulation performance. This work presents an experimental and numerical investigation of leakage currents on artificially contaminated polymer insulators under two application-relevant HVDC operating scenarios. The first scenario considers superimposed HVDC voltage with switching impulses and very slow front overvoltages, which may occur during fault conditions in converter-based HVDC systems. The second scenario investigates electromagnetic coupling effects in a hybrid HVDC/HVAC transmission line configuration, where AC and DC conductors are installed on the same tower. Artificial contamination layers with different morphologies and conductivities are applied to the insulator surface to reproduce realistic pollution conditions. Leakage currents are measured using a high-resolution acquisition system, and the results are supported with numerical simulations based on finite-element modelling. The results show that transient overvoltages significantly increase leakage current amplitude and duration, leading to increased electrical stress on contaminated insulators. In the hybrid transmission configuration, electromagnetic coupling between AC and DC paths induces additional current components in the DC leakage current. The presented results contribute to a better understanding of leakage current behaviour under realistic HVDC operating conditions and provide useful information for insulation assessment and condition monitoring of outdoor insulators in modern HVDC transmission systems. Full article

The growing use of electrochemical batteries in renewable energy systems has intensified the need for storage architectures that can sustain power delivery while limiting transient electrical stress and voltage instability challenges. This study addresses the research gap in experimentally establishing a physically interpretable framework that links battery-centered hybrid storage behavior at the DC bus to AC-side inverter performance under load and source disturbances. A laboratory-scale renewable microgrid integrating photovoltaic and wind generation, programmable load variation, inverter-based AC delivery, and hybrid battery–supercapacitor storage is experimentally implemented and evaluated against a battery-only baseline, supported by a unified analytical framework that quantifies how transient buffering improvements propagate through the power conversion chain. The results show that the hybrid configuration reduces DC-bus voltage droop from about 1.1 V to 0.6 V under heavy-load transitions, and from approximately 0.85 V to 0.44 V during source-side variability (e.g., photovoltaic and wind turbine variations). The hybrid system also improves AC-side behavior, yielding unified stabilization indices of 103.03% for the root-mean-square voltage and 79.51% for the peak-to-peak voltage. These findings demonstrate that the experimentally implemented lab-scale renewable microgrid with hybrid battery–supercapacitor storage provides an effective pathway for improving battery-supported microgrid stability, waveform quality, and transient resilience. Full article

Smart power management practices are needed for a sustainable EV charging infrastructure due to the fast use of renewable energy resources. An innovative power management structure for a small grid-connected solar PV system-based AC and DC charging station, combined with a backup purpose battery energy system (BESS), is demonstrated in this paper’s study. The sustainability transition is associated with integrating renewable energy resources with a battery storage system, providing a helpful solution for managing large power-demanding entities (EV, microgrid, etc.). In this study, a solar PV system takes 500 datasets (based on data availability or to prevent overfitting) of PV voltage, solar irradiance, and air temperature, and the performance of controlling for the maximum power point tracker by training these datasets using Levenberg–Marquardt (LM), which was implemented in the ANN toolbox and created this technique in MATLAB 2016 or Simulink. Also, using this technique for the estimation and forecasting of the datasets of solar PV systems and EVs obtains better results for achieving further targets. To enhance decision-making capability through optimized technique, we have to find it before forecasting PV power generation and EV datasets throughout the day (24 h). The optimized power flows among solar PV power generation, EV charging demand (including AC charging and DC fast charging), the BESS, and the utility/small grid under several priority operating scenarios. A famous technique for optimization, mixed-integer linear programming (MILP), is applied. In this technique, the objective function is used for the solution of problem formation and compliance with system constraints such as the power balancing equation, charging/discharging limits, SOC limits, and grid export/import exchange limits: basically, equality, inequality, and bounds limits. Optimized results show that the coordinated power flow operations are consented to by EV users, by prioritizing some key points, such as solar PV use at the maximum, reducing the grid power dependency, and the first power flow towards EV charging demand. The verified MILP-based solutions boost the maximum utilization of renewable energy resources, feasible EV charging demand, and scaling power flow among these entities. The key contribution of this study is suitable for different powered EV charging stations based on both AC and DC, with different ratings of EVs (including fast and slow charging). Most solar PV-based generation supports the EVCS and backup for ranking-wise BESS, and grid support for the EVCS. Also, the key contribution of hybrid techniques in this article is divided into two stages: in the first stage, an artificial neural network (ANN) is utilized for estimating the PV voltage at the maximum point and forecasting, while in the second stage, mixed-integer linear programming (MILP) employs optimal power management. Full article

In the context of the coordinated development of high-proportion renewable energy integration and alternating current/direct current (AC/DC) hybrid transmission, the sending-end power grid faces challenges such as decreased system strength, contracted stability boundaries, and difficulties in covering high-risk operating conditions. This paper proposes a new renewable energy scale impact analysis method that integrates “typical scenario construction-scale ladder comparison–prediction-driven time series injection” in response to the operational constraints of AC/DC transmission. In terms of method implementation, firstly, a two-layer typical scenario system is constructed under unified transmission constraints and fixed grid boundaries: A regular benchmark scenario covers the main operating range, and a set of high-risk scenarios near the boundaries is obtained through multi-objective intelligent search, which is then refined through clustering to form a computable stress-test scenario library. Here, the boundary scenarios are generated by a multi-objective search that simultaneously drives multiple key section load rates towards their limits, subject to AC power-flow feasibility and operational constraints, and the resulting Pareto candidates are reduced into a compact stress-test library by clustering. Secondly, a ladder scenario with increasing renewable energy scale is constructed, and cross-scale comparisons are carried out within the same scenario system to extract the scale effect and critical laws of key safety indicators. Finally, data resampling and Gated Recurrent Unit multi-step prediction are introduced to generate wind power output time series, enabling the temporal mapping of prediction results to scenario injection quantities, and constructing a closed-loop input interface of “prediction–scenario–grid indicators”. The results demonstrate that the proposed hierarchical framework, under unified AC/DC export constraints, can effectively construct a compact stress-test scenario library with enhanced boundary-risk coverage and can reveal how transient voltage security evolves across renewable expansion scales. By coupling boundary-oriented scenario construction, cross-scale comparable assessment, and forecasting-driven time series injection, the framework improves engineering interpretability and practical applicability compared with conventional scenario sampling/reduction workflows. For the forecasting module, the Gated Recurrent Unit (GRU) model achieves MAPE = 8.58% and RMSE = 104.32 kW on the test set, outperforming Linear Regression (LR)/Random Forest (RF)/Support Vector Regression (SVR) in multi-step ahead prediction. Full article

Power system blackouts remain a major concern for modern electricity networks, as they often result from cascading failures that lead to substantial load shedding and widespread service disruptions. This paper presents a dynamic resilience assessment of hybrid AC/DC power systems and investigates the effectiveness of voltage-source-converter-based high-voltage direct current (VSC-HVDC) technology in enhancing system resilience under outage contingencies. The study contributes by integrating protection devices and their settings into the analysis and by providing a quantitative evaluation of the system response to N-2 and N-3 contingencies using PSS^®E simulations. The demand not served index is used as a measure of resilience, and its cumulative distribution functions are computed to compare the performance of AC and DC interconnections. The results underscore the importance of VSC-HVDC links in mitigating cascading failures, highlighting their potential as a resilience-enhancing component in modern power grids. Full article