Search Results (33)

This work uses battery-coupled power electronic converter systems and distributed backstepping controllers to improve the reliability of electrical distribution networks. The motivation is to prevent blackouts such as the 28 April 2025 outage in Spain, Portugal, and the south of France. It is now accepted that a rapid rise in solar power injections caused AC overvoltage above grid code limits, triggering photovoltaic (PV) park disconnections as overvoltage self-protection. This case study considers near-Zero-Energy Buildings (nZEBs) connected to the Madeira Island isolated microgrid, where PV power installation is increasing excessively. The main university facility will be upgraded as an nZEB, using roughly 3000 m² of unshaded rooftops plus coverable parking areas to install PV panels. Optimizing the profits/energy cost ratio, a PV power system of around 560 kW can be planned, and the Battery Storage System (BSS) energy capacity can be estimated. The BSS is connected to the university nZEB via backstepping-controlled multilevel converters to manage PV and BSS, enabling the building to contribute to voltage and frequency regulation. Distributed multilevel converters inject renewable energy into the medium-voltage network, regulating active and reactive power to prevent overvoltages shutting down the PV inverters. This removes sustained overvoltage and maximizes PV penetration while augmenting AC grid reliability and resilience. When there is excess solar power and reactive power is insufficient to reduce voltage, controllers slightly curtail PV active power to eliminate overvoltage, maintaining operation with minimal revenue loss while preventing long interruptions, thereby improving grid reliability and power quality. Full article

The accelerated integration of photovoltaic (PV) systems, particularly within Hybrid PV–Battery Storage Systems (PV-BSS), establishes a compelling need for advanced control strategies that are fundamental to achieving effective Energy Saving Management. However, conventional proportional–integral (PI) controllers demonstrate limited adaptability and necessitate tedious, manual parameter tuning, frequently resulting in suboptimal dynamic performance, especially under load transients. To specifically address these constraints within the domain of high-power electronics, this paper introduces a novel Artificial Neural Network (ANN)-based current controller tailored for the 1500 VDC Three-Level Hybrid Active Neutral Point Clamped (3L-HANPC) inverter, which is a widely accepted PV-BSS topology. The optimal Multi-Layer Perceptron (MLP) architecture was identified using a multi-criteria methodology, which strategically balanced Total Harmonic Distortion (THD) performance against training efficiency. Simulation results affirm that the proposed ANN controller achieves superior harmonic mitigation and demonstrates faster dynamic responses compared to the PI counterpart. Moreover, the controller fundamentally ensures stable operation while eliminating the necessity for complex PI parameter tuning. Its dependable performance across both trained and unseen operating points strongly validates its robust adaptability. This self-tuning ANN approach thus provides a viable pathway for enhancing the reliability of future hybrid energy storage systems. Full article

The growing penetration of renewable energy sources requires resilient microgrids capable of providing stable and continuous operation. Hybrid energy storage systems (HESS), which integrate hydrogen-based storage systems (HBSS), battery storage systems (BSS), and supercapacitor banks (SCB), are essential to ensuring the flexibility and robustness of these microgrids. Accurate modelling of these microgrids is crucial for analysis, controller design, and performance optimization, but the complexity of HESS poses a significant challenge: simplified linear models fail to capture the inherent nonlinear dynamics, while nonlinear approaches often require excessive computational effort for real-time control applications. To address this challenge, this study presents a novel state space model with linear variable parameters (LPV), which effectively balances accuracy in capturing the nonlinear dynamics of the microgrid and computational efficiency. The research focuses on a high-voltage DC bus microgrid architecture, in which the BSS and SCB are connected directly in parallel to provide passive DC bus stabilization, a configuration that improves system resilience but has received limited attention in the existing literature. The proposed LPV framework employs recursive linearisation around variable operating points, generating a time-varying linear representation that accurately captures the nonlinear behaviour of the system. By relying exclusively on directly measurable state variables, the model eliminates the need for observers, facilitating its practical implementation. The developed model has been compared with a reference model validated in the literature, and the results have been excellent, with average errors, MAE, RAE and RMSE values remaining below 1.2% for all critical variables, including state-of-charge, DC bus voltage, and hydrogen level. At the same time, the model maintains remarkable computational efficiency, completing a 24-h simulation in just 1.49 s, more than twice as fast as its benchmark counterpart. This optimal combination of precision and efficiency makes the developed LPV model particularly suitable for advanced model-based control strategies, including real-time energy management systems (EMS) that use model predictive control (MPC). The developed model represents a significant advance in microgrid modelling, as it provides a general control-oriented approach that enables the design and operation of more resilient, efficient, and scalable renewable energy microgrids. Full article

The use of renewable energy sources (RESs) is increasing every day to meet increasing energy demands and reduce dependence on fossil fuels. When designing hybrid renewable energy systems (HRESs), it is necessary to examine their technical, economic, and environmental feasibility. In this study, a new strategy is proposed using the HOMER Matlab Link (ML) connection for an HRES model consisting of a photovoltaic (PV) system, a wind turbine (WT), a biogas generator (BGG), and a battery storage system (BSS) designed to meet the electrical energy needs of Doğanevler village located in the rural area of Bingöl province. The data obtained as a result of the proposed strategy (PS) are compared with HOMER’s loop charging (CC) and load following (LF) optimization results. According to the PS, the optimum capacity values for the HRES components are 10 kW for WT, 10 kW for PV, 8 kW for BGG, 12 kWh for BSS, and 12 kW for the converter. According to the optimum design, 16,205 kWh of the annual energy produced was generated by PV systems, 22,927 kWh by WTs, and 22,817 kWh by BGGs. This strategy’s NPC and LCOE (Levelized Cost of Energy) values are calculated as USD 130,673.91 and USD 0.207/kWh, respectively. For the CC dispatch strategy, the NPC and LCOE values are calculated as USD 141,892.28 and USD 0.240/kWh, while for the LF dispatch strategy, these values are USD 152,456.89 and USD 0.257/kWh. The CO₂ emission value for the system using a BGG was calculated as 480 kg/year, while for the system using a DG, this value increased approximately 57 times and was calculated to be 27,709 kg/year. The results show that the PS is more economical than the other two strategies. The PS provides energy security, reduces costs, and increases environmental sustainability. Finally, a sensitivity analysis was conducted based on the availability of renewable resources, fuel cost, and inflation parameters, and the results were analyzed. Full article

As maritime technology advances, exploration of the oceans has progressively moved from surface exploration to underwater ventures. Unmanned underwater vehicles (UUVs), now prevalent for such exploration, effectively reduce human labor and lower operational costs. These vehicles rely on an internal Battery Storage System (BSS) that sustains device operation by extending operational duration and providing stable voltage. Typically arranged in series, BSSs face challenges due to differences in the chemical characteristics of individual batteries, which lead to discrepancies in battery voltages and cause imbalances during charge and discharge cycles. This results in varied utilization rates among the batteries and uneven aging of the battery pack, potentially decreasing operational efficiency and increasing failure rates, thus reducing reliability and safety. Considering the harsh environmental conditions and maintenance difficulties associated with underwater operations, this paper proposes a robust solution: a balancing system featuring a modular switch with electrical isolation. Through theoretical analysis and circuit simulation, this study constructs and tests a novel prototype of a capacitor-based equalizer circuit with electrical isolation, verifying its feasibility. Full article

The increasing use of renewable energies places new challenges on the balance of the electricity system between demand and supply, due to the intermittent nature of renewable energy resources. However, through frequency regulation (FR) services, owners of battery storage systems can become an essential part of the future smart grids. We propose a thorough first study on the use of batteries associated with base stations (BSs) of a cellular network, to participate in ancillary services with respect to FR services, via an auction system. Trade-offs must be made among the number of participating BSs, the degradation of their batteries and the revenues generated by FR participation. We propose a large-scale mathematical programming model to identify the best participation periods from the perspective of a cellular network operator. The objective is to maximize profit while considering the aging of the batteries following their usage to stabilize the electrical grid. Experiments are conducted with data sets from different real data sources. They not only demonstrate the effectiveness of the optimization model in terms of the selection of BSs participating in ancillary services and providing extra revenues to cellular network operators, but also show the feasibility of ancillary services being provided to cellular network operators. Full article

The mutual optimization of a multi-microgrid integrated energy system (MMIES) can effectively improve the overall economic and environmental benefits, contributing to sustainability. Targeting a scenario in which an MMIES is connected to the same node, an energy storage coordination control strategy and carbon emissions management strategy are proposed, and an adaptive step-size method is applied to improve the distributed optimization of MMIESs based on the alternating direction multiplier method (ADMM). Firstly, the basic framework of MMIESs is established, and a coordinated control strategy limiting the time of charge and the discharge of the battery storage system (BSS) is proposed. Then a multi-objective optimization model based on operating and environmental cost is formulated. Considering that different microgrids may be managed by different operators and a different convergence speed of multi-objective optimization iteration, an adaptive step-size distributed iterative optimization method based on ADMM is used, which can effectively reduce the cost and protect the privacy of each microgrid. Finally, a system composed of three microgrids is taken as an example for simulation analysis. The results of distributed optimization are accurate, and the proposed coordinated control strategy can effectively enhance the revenue of ESS, which verifies the effectiveness of the proposed method. Full article

Amidst a growing global focus on sustainable energy, this study investigates the underutilization of renewable resources in the southern region of Saudi Arabia, with a specific emphasis on the Najran Secondary Industrial Institute (NSII). This research presents an in-depth analysis of installing a hybrid microgrid (MG) system on the roofs of NSII buildings, exploring six cases with varying tilt and azimuth angles. The study innovatively integrates architectural design and system administration, a novel approach for this location, and benchmarks the optimal angles against Hybrid Optimization of Multiple Energy Resources (HOMER) software defaults. The proposed system consists of solar photovoltaic (PV) panels, a battery storage system (BSS), a converter, a diesel generator (DG), and a grid. The selected model balances technological and economic viability with environmental considerations, ensuring a reliable power supply within the NSII’s roof area constraints. An extensive sensitivity analysis evaluates the system’s resilience across different scenarios. The current system, which is grid-only, has an estimated Net Present Cost (NPC) of about USD 7.02M and emits 1.81M kg/yr of CO₂. The findings point to installing a microgrid with a 20.97° tilt and 50° azimuth angle as optimal, demonstrating 54.69% lower NPC and 92% lower CO₂ emissions, along with zero kWh/year unmet electrical load when applying the resilience assessments. This outcome highlights Saudi Arabia’s southern region’s renewable energy potential, aligning with national mega-projects and energy initiatives. Full article

For increased penetration of energy production from renewable energy sources at a utility scale, battery storage systems (BSSs) are a must. Their levelized cost of electricity (LCOE) has drastically decreased over the last decade. Residential battery storage, mostly combined with photovoltaic (PV) panels, also follow this falling prices trend. The combined effect of the COVID-19 pandemic and the war in Ukraine has caused such a dramatic increase in electricity prices that many consumers have adjusted their strategies to become prosumers and self-sufficient as feed-in subsidies continue to drop. In this study, an investigation is conducted to determine how profitable it is to install BSSs in homes with regards to battery health and the levelized cost of total managed energy. This is performed using mixed-integer linear programming (MILP) in MATLAB, along with its embedded solver Intlinprog. The results show that a reasonable optimized yearly cycling rate of the BSS can be reached by simply considering a non-zero cost for energy cycling through the batteries. This cost is simply added to the electricity cost equation of standard optimization problems and ensures a very good usage rate of the batteries. The proposed control does not overreact to small electricity price variations until it is financially worth it. The trio composed of feed-in tariffs (FITs), electricity costs, and the LCOE of BSSs represents the most significant factors. Ancillary grid service provision can represent a substantial source of revenue for BSSs, besides FITs and avoided costs. Full article

Growing Electric vehicle (EV) ownership leads to an increase in charging stations, which raises load demand and causes grid outages during peak hours. Microgrids can significantly resolve these issues in the electrical distribution system by implementing an effective energy management approach. The suggested hybrid optimization approach aims to provide constant power regardless of the generation discrepancy and should prevent the early deterioration of the storage devices. This study suggests using a dynamic control system based on the Fuzzy-Sparrow Search Algorithm (SSA) to provide a reliable power balance for microgrid (MG) operation. The proposed DC microgrid integrating renewable energy sources (RES) and battery storage system (BSS) as sources are designed and evaluated, and the findings are further validated using MATLAB Simulink simulation. In comparing the hybrid SSA strategy with the most widely used Particle Swarm Optimization (PSO)-based power management, it was observed that the hybrid SSA approach was superior in terms of convergence speed and stability. The effectiveness of the given energy management system is evaluated using two distinct modes, the variation of solar irradiation and the variation of battery state of charge, ensuring the microgrid’s cost-effective operation. The enhanced response characteristics indicate that the Fuzzy-SSA can optimise power management of the DC microgrid, making better use of energy resources. These results show the relevance of algorithm configuration for cost-effective power management in DC microgrids, as it saves approximately 7.776% in electricity expenses over a year compared to PSO. Full article

Via the analysis of a set of parking and journey information for vehicles traveling to the parking site at the University of Brescia (Italy), we evaluated the possibility of managing the electric recharging of these vehicles, which are hypothesized to be electric. The paper investigates charging optimization techniques that can limit the charge power peaks and distribute the energy demand throughout the day. A cost assessment for an auxiliary system consisting of a photovoltaic energy source (PV) and battery stationary storage (BSS) is also carried out. Optimal power management at the station with PV and BSS is introduced, and the performance of two feedback controllers based on the optimized results is compared with that of a real-time management algorithm in the presence of randomness in charging requests and insolation. The results show that the BSS degradation cost plays a primary role in determining the strategy to adopt to minimize the operating expenditure of a charging station. Full article

For national energy capacity improvement and CO₂ emission reductions, Mongolia has focused its attention on grid-connected residential PV systems. Due to the feed-in tariff (FIT), the aggregated residential PV systems are expected to increase with the PV penetration level. Currently, there is no power injection limitation in Mongolia. A new policy for the PV penetration level of residential PV systems needs to be developed. This study analyzed the techno-economic performances of distributed PV-battery systems, considering PV generation, the historical load demand, and the tariff structure. We studied the performances of 40 combinations of PV sizes (2 kW–9 kW) and battery capacities (4.4 kWh, 6.6 kWh, 10 kWh, 12 kWh, and 15 kWh) to find feasible system sizes. The aggregated PV-battery systems in a low-voltage (LV) distribution system located in Ulaanbaatar, Mongolia, are also discussed. The results show that six combinations satisfied the technical and economic requirements. The maximum profit was determined to be an NPV of 1650 USD with a 9-year payback period using combination 3 (6 kW PV and 6.6 kWh battery capacity). Combination 6 (8 kW PV and 15 kWh battery capacity) shows that the energy management strategy for residential houses with battery storage has the potential to increase the installed capacity of PV systems without voltage violence in the LV network. For the distributed PV-battery storage system (BSS), the environmental analysis indicates that CO₂ and SO₂ emissions were reduced by 3929 t/year and 49 t/year, respectively. The findings obtained from this analysis will be used for power system planning. Full article

The momentous deployment of photovoltaic (PV) installations in modern times converted schemes utilised to support behind-the-meter systems to compensation mechanisms promoting self-consumption for all prosumer types. Moreover, their incorporation with battery storage systems (BSS) is expected to remove technical counter effects and assist in more self-sufficient prosumer sites. As electricity prices are continuously rising, negatively impacting consumers, we intend for this study to serve as a guideline for residential PV-BSS sizing. Additionally, its objective is to provide an operational and economic evaluation of PV-BSS by considering relevant schemes and concentrating on the most effective parameters. This study contributes to the literature with a holistic methodology for sizing and techno-economically evaluating residential systems in the Mediterranean area that is replicable for any state or consumption class. Simulations addressing PV-BSS performance were exploited with the use of real (high-resolution) data, estimating particular sizing, operational, and techno-economic indicators during the entire system lifetime within the framework of a techno-economic analysis. The simulations calculated the initial expenditure, the yearly revenues from the PV-BSS operation, and the corresponding expenses, contrasting them on a year-to-year basis. The results demonstrate that for the five countries addressed as case studies, PV-BSS sizing is significantly impacted by the supporting scheme regarding maximum financial gains. A likeness amid the ideal power-to-energy ratio (PER) indicator of every addressed state for the examined parameters (electricity price and consumption class) was demonstrated for the full self-consumption scheme, whereas for net billing, intercountry discrepancies and generally higher optimal PER values were observed. Finally, an increase in electricity prices or consumption generally decreases optimal PER; therefore, a recommendation is provided for the avoidance of inessential expenditures in surplus system component sizes. Full article

The systematic transition of conventional automobiles to their electrified counterparts is an imperative step toward successful decarbonization. Crucial advances in battery storage systems (BSS) and related technologies will enable this transition to proceed smoothly. This requires equivalent developments in several interconnected areas, such as complete battery cycles and battery management systems (BMS). In this context, this article critically examines state-of-the-art battery technologies from the perspective of automakers, provides insightful discussions, and poses open questions with possible answers. The generations of BSS (traditional, current, and futuristic) are first reviewed and analyzed via two distinct qualitative factors (DQFs): key design markers and performance indicators. Based on the introduced DQFs, major development trends and probable evolutions are forecasted. Thereafter, recent modeling and state estimation methods are comprehensively reviewed in relation to high-performance BMS. Accordingly, promising modeling methods are identified as futuristic solutions, leading to an accurate and timely decision for reliable and safer user experience. This article is concluded by presenting a techno-economic assessment of what to expect, as well as highlighting future challenges and opportunities for industry, academia, and policy makers. Full article

The heterogeneous network (HetNet) is a specified cellular platform to tackle the rapidly growing anticipated data traffic. From a communications perspective, data loads can be mapped to energy loads that are generally placed on the operator networks. Meanwhile, renewable energy-aided networks offer to curtailed fossil fuel consumption, so to reduce the environmental pollution. This paper proposes a renewable energy based power supply architecture for the off-grid HetNet using a novel energy sharing model. Solar photovoltaics (PV) along with sufficient energy storage devices are used for each macro, micro, pico, or femto base station (BS). Additionally, a biomass generator (BG) is used for macro and micro BSs. The collocated macro and micro BSs are connected through end-to-end resistive lines. A novel-weighted proportional-fair resource-scheduling algorithm with sleep mechanisms is proposed for non-real time (NRT) applications by trading-off the power consumption and communication delays. Furthermore, the proposed algorithm with an extended discontinuous reception (eDRX) and power saving mode (PSM) for narrowband internet of things (IoT) applications extends the battery lifetime for IoT devices. HOMER optimization software is used to perform optimal system architecture, economic, and carbon footprint analyses while the Monte-Carlo simulation tool is used for evaluating the throughput and energy efficiency performances. The proposed algorithms are validated through the practical data of the rural areas of Bangladesh from which it is evident that the proposed power supply architecture is energy-efficient, cost-effective, reliable, and eco-friendly. Full article