Search Results (744)

Weak grid infrastructure and the absence of flexible storage are among the principal barriers to reliable, low-carbon energy access in sub-Saharan transmission systems. This paper proposes a hierarchical multi-objective framework for the optimal siting and sizing of battery energy storage systems (BESSs), applied to the 130-bus Mali transmission network within the EMERGE project. The upper level employs NSGA-II to simultaneously maximize daily price arbitrage revenue and minimize active power losses; the lower level solves a network-constrained DC optimal power flow with thermal branch limits enforced as hard linear inequalities via the Power Transfer Distribution Factor (PTDF) matrix. Over 500 generations, the framework identifies Bus 91 (SIRAKORO II, 150 kV) as the dominant storage location, achieving a maximum daily revenue of approximately €10,033 at a marginal loss increment of $6.7\times {10}^{-3}$ MWh. The resulting Pareto front gives Mali system planners a quantitative tool for trading off private investment returns against grid-level environmental impact, demonstrating that rigorous network-constrained BESS planning is technically tractable and economically viable in the resource-constrained context of sub-Saharan energy transitions. Full article

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

The increasing penetration of wind generation into autonomous and weakly coupled industrial microgrids requires control strategies that can maintain power-supply reliability under stochastic generation and sharply variable loads. This paper proposes an adaptive corridor-based supervisory control algorithm for a lithium-ion battery energy storage system (BESS) integrated with a wind-turbine generator. The novelty of the method is not the general use of battery storage for power smoothing but a control law that maintains the generator within a predefined active-power corridor while transferring fast and medium-duration imbalances to the battery under state-of-charge, power-limit, and response-delay constraints. Unlike PI-based smoothing, model predictive control, or fixed rule-based switching, the proposed approach uses corridor retention as the primary operating criterion and relies only on directly measurable variables. The model was implemented in MATLAB/Simulink for a 2 MW wind-turbine generator coupled with a 444 kWh/1776 kW lithium-ion battery energy storage system. Field-measurement-based simulation validation was performed in MATLAB/Simulink using industrial load data measured at an autonomous oilfield power plant; the validation scenarios included extracted step disturbances, a real multi-peak load profile, prolonged deficit operation, and a scaled configuration scenario. The algorithm compensated for 86.3–87.4% of short-term load peaks, reduced the standard deviation of generator power from 467 to 98 kW, and decreased recovery time from 6.8 to 1.6 s. Full article

Hybrid renewable energy systems are regarded as one of the most promising solutions for the autonomous power supply of remote and weakly electrified sites, where diesel generation remains a costly and carbon-intensive energy source. This study presents the optimization of an off-grid PV/BESS/DGU microgrid for three representative regions of Kazakhstan—North, Central/East, and South/South-West—under different environmental scenarios. The aim of the study was to determine the optimal installed photovoltaic capacity, battery storage capacity, diesel generator rated power, and annual load coverage balance using the Generalized Reduced Gradient (GRG) method. The optimization was carried out using two objective functions: the conventional levelized cost of electricity, $LCOE$, and the environmentally adjusted cost of electricity, ${LCOE}_{\mathrm{e}\mathrm{n}\mathrm{v}}$, which includes the monetized cost of emissions associated with diesel generator operation. The model was formulated as a constrained nonlinear programming problem incorporating hourly energy balance, battery state-of-charge constraints, diesel generator operating constraints, and carbon price scenarios of 0, 25, 50, and 100 USD/tCO₂. The results show that an increase in the carbon price systematically shifts the optimum toward a higher share of photovoltaic generation and reduced diesel generator use in all regions. The strongest response is observed in the South/South-West region, followed by Central/East, whereas the North exhibits the lowest sensitivity due to the more pronounced seasonality of solar generation. Under the considered scenarios, the optimal PV capacity increases by approximately 24–28%, while the share of diesel generation in annual load coverage decreases by approximately 28% in the North, 44% in Central/East, and 61% in the South/South-West. At the same time, the rated diesel generator capacity remains unchanged in most scenarios, indicating the persistence of its backup function. The results confirm that the PV/BESS/DGU configuration constitutes a technically and economically justified baseline architecture for autonomous power supply under Kazakhstan’s conditions, while the inclusion of environmental costs supports the cost-effective displacement of diesel generation. The GRG method proved to be suitable for the transparent and efficient optimization of hybrid microgrid parameters. Full article

Grid-scale battery energy storage systems (BESSs) are becoming central flexibility assets in electricity systems with rising renewable penetration, changing demand profiles, and increasing system security requirements. This review examines BESS development in Australia, Singapore, China, and New Zealand, comparing strategic policy drivers, market access arrangements, revenue mechanisms, bankability conditions, support instruments, regulatory frameworks, and key deployment risks. Across all four jurisdictions, BESSs are moving from demonstration assets to core infrastructure for renewable integration, frequency control, reserve provision, congestion management, and short-duration energy shifting. The comparison shows that no single business model dominates. Australia relies heavily on volatile wholesale arbitrage, ancillary services, and government underwriting; Singapore emphasises grid resilience, dispatch precision, safety, and space-efficient deployment; China combines national strategic direction with province-specific market implementation; and New Zealand is developing a market-led, location-specific storage model within a high-renewables, hydro-dominated system. The review finds that bankable BESS deployment depends on revenue stacking, fit-for-purpose market rules, clear bidirectional asset classification, robust grid-connection processes, lifecycle safety management, and credible degradation and augmentation strategies. It concludes that BESSs are essential but not sufficient for deep decarbonisation, since long-duration flexibility and wider system reform remain necessary. Full article

Institutional shuttle fleets with fixed routes and predictable terminal parking are well-suited to charging photovoltaic–battery energy storage system (PV–BESS) charging for sustainable campus mobility. However, siting and sizing are often solved numerically without identifying the physical constraints that determine the optimum. This study develops a sustainability-oriented framework for converting a 10-van diesel shuttle fleet at Rajamangala University of Technology Lanna into an electric fleet supported by distributed PV–BESS charging stations. A centralized one-station layout is compared with a distributed two-station layout, and a closed-form active-constraint sizing rule is derived using Karush–Kuhn–Tucker (KKT) analysis. Results show that the distributed configuration eliminates dead-run travel and provides higher lifecycle value than the centralized case. KKT analysis identifies two binding constraints: the PV rooftop-area limit and the BESS one-day autonomy requirement. Under base-case assumptions, the transition achieves positive lifecycle value and substantial CO₂ reduction relative to the diesel baseline. Monte Carlo analysis confirms financial robustness within the uncertainty ranges, while deterministic stress tests show sensitivity to diesel prices, PV electricity credit values, discount rate, and fleet utilization. The framework provides an interpretable decision-support method for institutional fleet electrification in solar-rich campus settings, contributing to SDGs 7, 11, and 13 through clean-energy adoption, sustainable transportation, and CO₂-emission reduction. Full article

As power grids transition towards highly renewable generation on a global scale, maintaining dynamic stability is becoming a major challenge. Replacing traditional synchronous generators with inverter-based renewables strips the grid of rotational inertia, leaving active distribution networks highly vulnerable to frequency deviations and voltage spikes. To avoid expensive poles and wires upgrades, Battery Energy Storage Systems (BESS) are increasingly being deployed as Non-Network Solutions (NNS). However, the current literature reveals a distinct gap between the macro-scale economic planning of these storage assets and the micro-scale dynamic control actually required to keep the grid resilient. To address this gap, this review proposes a multi-layer deterministic synthesis framework that links physical renewable modelling, degradation-aware techno-economic planning, deterministic forecasting, and EMS dispatch through offline time-domain control validation for AC-microgrid energy storage integration. The research examines how advanced central control units within battery management systems can rigorously and jointly estimate State of Charge (SoC) and State of Energy (SoE) to ensure accurate grid-aware dispatch. Furthermore, the study explores the integration of degradation-aware economic modelling in HOMER Pro with dynamic transient control in MATLAB/Simulink R2025b, driven by hybrid metaheuristic optimization algorithms like Grey Wolf Optimizer (GWO) and Particle Swarm Optimization (PSO). This analysis demonstrates that integrating energy storage must be treated as a tightly coupled multidimensional optimization problem to successfully deliver the secure and sustainable infrastructure needed to solve the modern energy trilemma. Full article

In this paper, we propose a self-learning digital twin (SLDT) architecture that incorporates real-time battery degradation modeling and optimum operational management for grid-scale lithium-ion battery energy storage systems (BESS). This work extends the Adaptive Real-Time Degradation Model (ARDM) framework to allow real-time updates of the parameters based only on live operational data without pre-cycling experiments and further improves its robustness under various depth-of-discharge (DoD), charging/discharging current (C-rate), and temperature conditions. The ARDM is incorporated in a real-time digital twin that maintains synchronized health, state of charge (SoC), and degradation cost predictions. The digital twin is linked to an Optimization and Control Layer (OCL), which plans the charge/discharge day-ahead in advance based on dynamic power rates. The Musical Chairs Algorithm (MCA) is used for parameter identification and scheduling due to its better convergence characteristics compared to swarm-reduction forms of benchmark optimization algorithms. Experimental validation is carried out on two commercial 48 V Li-ion modules with various cycling patterns, and sub-millipercent root-mean-square error (RMSE) is achieved in capacity-fade tracking. The economic analysis for a 5-MW/10-MWh system indicates that dynamic tariff scheduling results in about nine times greater arbitrage revenue compared to fixed rates, 41–58% higher yearly net income, and lower degradation costs. The results confirm that the SLDT is a practical and accurate platform for degradation-aware operational planning in modern smart-grid environments. Full article

This study presents a novel iterative dual-loop methodology for the technical sizing of DC-coupled PV-BESS systems. The method was implemented for a commercial broiler farm characterized by a highly variable electricity demand profile (annual consumption: 7.6 MWh; coefficient of variation: 53%). The methodology introduces two original energy utilization indicators—the photovoltaic-to-converter matching factor (W_{PV_S}) and the photovoltaic-to-BESS matching factor (W_{PV_B})—enabling purely technical optimization independent of economic conditions. Minimization of the radius of curvature of the WPVB characteristic curve is applied as a rigorous mathematical criterion for determining the optimal BESS capacity. Simulation results indicate that the optimal configuration consists of a 9.7 kWp photovoltaic system, a 7 kW DC converter, and a 15 kWh battery storage system. The integration of an optimally sized energy storage system increased the self-consumption coverage ratio from 38% to 59% and improved the photovoltaic energy utilization factor from 35% to 54%. Additional economic analysis demonstrates that the PV-only subsystem achieves a simple payback period ranging from 8 to 18 years, depending on the selected pricing scenario. Consequently, the technically optimal configuration identified using the proposed methodology represents a practically feasible investment for broiler production facilities operating under Polish net-billing conditions. The proposed methodology provides a reproducible, economically independent framework for the design of DC-coupled PV-BESS systems in agricultural prosumer facilities, addressing a critical gap in the optimization literature and offering practical sizing guidelines applicable to similarly high-variability load profiles. Full article

This study presents an Ant Colony Optimization (ACO)-based methodology for the optimal placement of lithium-ion battery energy storage systems (BESSs) in radial electrical distribution networks. The proposed framework integrates base-case power-flow assessment, critical-bus identification, discrete BESS siting, technical–economic objective evaluation, and post-optimization validation. The methodology is applied to the IEEE 33-bus radial distribution test system, where the initial operating condition is characterized in terms of nodal voltage profile, voltage deviation, voltage-stability index, active-power losses, and annual loss cost. The optimization process identifies buses 13 and 31 as the most suitable locations for two identical BESS units, with the reported validation case evaluating each unit at upper admissible capacity limits of $1000\mathrm{kW}$ and $4000\mathrm{kWh}$. The obtained results show that the optimized BESS allocation increases the minimum voltage profile to values above $0.94\mathrm{p}.\mathrm{u}.$, raises the voltage-stability index to more than 0.88, reduces active-power losses to approximately $0.0166\mathrm{p}.\mathrm{u}.$, and decreases the annual cost associated with active-power losses by more than $66\%$ relative to the base case. Additional validation through sensitivity analysis, repeated stochastic runs, operating-mode evaluation, and comparison against a genetic algorithm confirms the consistency and robustness of the proposed ACO-based methodology. The results demonstrate that the proposed framework provides a technically consistent and computationally accessible solution for improving voltage regulation, reducing feeder losses, and lowering loss-related operating costs in radial distribution systems. Full article

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 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

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 paper presents a multi-period formulation of alternating current optimal power flow for active networks with conventional generation, photovoltaic generation, battery energy storage systems, renewable curtailment, and hourly electricity prices. The model is implemented on the IEEE 14-bus system over a 24 h horizon and solved as a nonlinear optimization problem to minimize total operating cost while preserving electrical feasibility. The formulation includes nodal active and reactive power balances, generator operating limits, photovoltaic inverter constraints, BESS charging and discharging dynamics, state of charge, voltage limits, and branch flow constraints. The results show a total demand of 5796.42 MWh, conventional generation of 5412.56 MWh, photovoltaic generation of 562.40 MWh, and active losses of 167.07 MWh, equivalent to 2.88% of the supplied energy. No photovoltaic curtailment was required, and the BESS exhibited a clear energy arbitrage pattern, charging during low-price hours and discharging during periods of higher economic value. In addition, a supplementary IEEE 39-bus assessment confirmed the computational applicability of the proposed formulation on a larger benchmark system. Furthermore, the optimal solutions enabled the construction of a supervised dataset to support the future development of machine learning-based warm-start strategies. Full article

The intermittent nature of renewable energy systems and the mismatch between power generation and load demand necessitate the integration of efficient energy storage systems (ESSs). Among large-scale energy storage technologies, pumped hydro-energy storage systems (PHESs) are widely recognized as one of the most cost-effective and longest-lifetime storage solutions under favorable geographical conditions. This study proposes and optimizes a hybrid renewable energy system (HRES) for the Wadi Baish region in Saudi Arabia as a real case study, where the significant elevation difference between the nearby mountains and the existing lake provides favorable conditions for PHES implementation. A nested optimization framework is developed to determine the optimal sizing and operation of the HRES components. The external optimization loop employs the non-dominated sorting genetic algorithm II (NSGA-II) to optimize system sizing, while the internal optimization loop uses mixed-integer linear programming (MILP) to optimally dispatch the PHES, battery energy storage system (BESS), and hydrogen energy storage system (HESS). In addition, demand-side management (DSM) is coordinated with the MILP dispatch strategy to improve system performance and reliability. The results show that the optimized system can supply a 10 MW average load with a renewable energy penetration of 98.7%. The proposed configuration achieves a total lifecycle cost of USD 231.37 million and avoids approximately 898.58 kt of CO₂ emissions over the project lifetime. PHES operates as the primary bulk energy storage technology due to its high storage capacity and low degradation characteristics. Furthermore, the degradation-aware model predicts battery replacement every 12 years and HESS replacement every 5 years. Compared with rule-based control, the MILP-based dispatch strategy reduces grid dependency by 87%. The coordinated DSM and MILP operation also reduces the levelized cost of energy to USD 0.066/kWh while improving overall system reliability. These findings demonstrate the importance of coordinated energy management and accurate degradation modeling in the optimal design and operation of renewable-based HRES configurations. Full article