Search Results (110)

The number of electric vehicles is constantly increasing in Europe and around the world. Providing a reliable charging infrastructure for the se vehicles is a major challenge for distribution grid operators. Off-grid microgrids have become a promising solution to this challenge, using renewable energy sources such as solar power to meet the demand in a sustainable way. This paper presents a practical study of a solar-powered microgrid operating at a university campus in Ilmenau, Germany, aimed at supporting electric vehicle (EV) charging at public workplaces. The system includes eight charging stations and utilizes renewable energy to reduce grid dependency. Statistical methods, including distribution functions, medians, and mean values, were applied to classify and evaluate the dataset to analyze energy generation and variable load patterns, as well as system performance. The results show that the Ilmenau microgrid can meet EV charging demand during the warm season but underperform during the cold season. An economic analysis determined costs of EUR 0.58/kWh based on pre-2020 component prices and EUR 0.46/kWh based on 2025 market prices. The calculated annual cost per employee is EUR 308.29 over a 20-year period. Increasing energy storage was found to be neither cost-effective nor operationally beneficial. The scalability of the microgrid to larger workplaces is investigated, and recommendations for system improvements are provided. Full article

The Union of the Comoros, located in the Indian Ocean, faces persistent energy challenges due to its geographic isolation, heavy dependence on imported fossil fuels, and underdeveloped electricity infrastructure. This study investigates the techno-economic optimization of a hybrid microgrid designed to supply electricity to a rural village in Grande Comore. The proposed system integrates photovoltaic (PV) panels, wind turbines, a diesel generator, and battery storage. Detailed modeling and simulation were conducted using HOMER Energy, accompanied by a sensitivity analysis on solar irradiance, wind speed, and diesel price. The results indicate that the optimal configuration consists solely of PV and battery storage, meeting 100% of the annual electricity demand with a competitive levelized cost of energy (LCOE) of 0.563 USD/kWh and zero greenhouse gas emissions. Solar PV contributes over 99% of the total energy production, while wind and diesel components remain unused under optimal conditions. Furthermore, the system generates a substantial energy surplus of 63.7%, which could be leveraged for community applications such as water pumping, public lighting, or future system expansion. This study highlights the technical viability, economic competitiveness, and environmental sustainability of 100% solar microgrids for non-interconnected island territories. The approach provides a practical and replicable decision-support framework for decentralized energy planning in remote and vulnerable regions. Full article

This paper introduces a reverse demand response scheme that uses electric vehicles in an isolated microgrid system, aiming to solve the renewable energy curtailment issue. We focus on an off-grid system where the system operator faces a stabilization problem due to surplus energy production, while electric vehicles seek to charge energy at a lower price. In our system model, the operator determines the incentive to encourage more charging facilities and electric vehicles to participate in the reverse demand response program. Charging facilities, acting as brokers, use a portion of these incentives to further encourage electric vehicle engagement. Electric vehicles follow the decisions made by the broker and system operator to determine their charging strategy within the system. Consequently, charging energy and incentives are allocated to the electric vehicles in proportion to their decisions. The paper investigates the economic benefits of individual participants and the contribution of power stabilization by implementing a hierarchical decision-making heterogeneous multi-leaders multi-followers Stackelberg game. By demonstrating the existence of a unique Nash Equilibrium, we show the effectiveness of the proposed model in an isolated microgrid environment. Full article

Due to the intermittent and uncertain nature of emerging renewable energy sources in the modern power grid, the level of dispatchable power sources has been reduced. The contemporary power system is attempting to address this by investing in energy storage within the context of standalone microgrids (SMGs), which can operate in an island mode and off-grid. While renewable-rich SMGs can facilitate a higher level of renewable energy penetration, they also have more reliability issues compared to conventional power systems due to the intermittency of renewables. When an SMG system needs to be upgraded for reliability improvement, the cost of that reliability improvement should be divided among diverse customer sectors. In this research, we present four distinct approaches along with comprehensive simulation outcomes to address the problem of allocating reliability costs. The central issue in this study revolves around determining whether all consumers should bear an equal share of the reliability improvement costs or if these expenses should be distributed among them differently. When an SMG system requires an upgrade to enhance its reliability, it becomes imperative to allocate the associated costs among various customer sectors as equitably as possible. In our investigation, we model an SMG through a simulation experiment, involving nine distinct customer sectors, and utilize their hourly demand profiles for an entire year. We explore how to distribute the total investment cost of reliability improvement to each customer sector using four distinct methods. The first two methods consider the annual and seasonal peak demands in each industry. The third approach involves an analysis of Loss of Load (LOL) events and determining the hourly load requirements for each sector during these events. In the fourth approach, we employ the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) technique. The annual peak demand approach resulted in the educational sector bearing the highest proportion of the reliability improvement cost, accounting for 21.90% of the total burden. Similarly, the seasonal peak demand approach identified the educational sector as the most significant contributor, though with a reduced share of 15.44%. The normalized average demand during Loss of Load (LOL) events also indicated the same sector as the highest contributor, with 12.34% of the total cost. Lastly, the TOPSIS-based approach assigned a 15.24% reliability cost burden to the educational sector. Although all four approaches consistently identify the educational sector as the most critical in terms of its impact on system reliability, they yield different cost allocations due to variations in the methodology and weighting of demand characteristics. The underlying reasons for these differences, along with the practical implications and applicability of each method, are comprehensively discussed in this research paper. Based on our case study findings, we conclude that the education sector, which contributes more to LOL events, should bear the highest amount of the Cost of Reliability Improvement (CRI), while the hotel and catering sector’s share should be the lowest percentage. This highlights the necessity for varying reliability improvement costs for different consumer sectors. Full article

The adoption of wind energy is pivotal for advancing sustainable power systems, particularly in off-grid microgrids where infrastructure limitations hinder conventional energy solutions. The inherent variability of wind generation, however, challenges grid reliability and demand–supply balance, necessitating accurate forecasting models. This study proposes a hybrid framework for short-term wind speed prediction, integrating deep learning (Long Short-Term Memory, LSTM) and ensemble methods (random forest, Extra Trees) to exploit their complementary strengths in modeling temporal dependencies. A multivariate approach is adopted using meteorological data (including wind speed, temperature, humidity, and pressure) to capture complex weather interactions through a structured time-series design. The framework also includes a feature selection stage to identify the most relevant predictors and a hyperparameter optimization process to improve model generalization. Three wind speed variables, maximum, average, and minimum, are forecasted independently to reflect intra-day variability and enhance practical usability. Validated with real-world data from Cuenca, Ecuador, the LSTM model achieves superior accuracy across all targets, demonstrating robust performance for real-world deployment. Comparative results highlight its advantage over tree-based ensemble techniques, offering actionable strategies to optimize wind energy integration, enhance grid stability, and streamline renewable resource management. These insights support the development of resilient energy systems in regions reliant on sustainable microgrid solutions. Full article

We propose a coordinated control strategy for off-grid 10 kV wind–solar–hydrogen energy storage DC microgrid systems based on hybrid energy storage and controllable loads to improve their stability and accommodation level. First, mathematical models of each unit are established based on the operating characteristics of wind turbines, photovoltaic (PV) units, alkaline electrolyzers, fuel cells, and lithium batteries. Second, on the side of the electro-hydrogen hybrid energy storage DC/DC converter, the traditional dual-loop control is improved by proposing a control scheme combining an extended state observer with adaptive backstepping control (ESO-adaptive backstepping). On the load demand side, an electric spring incorporating adaptive fuzzy control (AFC) is introduced to adjust and compensate for the voltage. Finally, an actual case analysis is conducted using data from the Ningbo Cixi hydrogen–electric coupling DC microgrid demonstration project. The results demonstrate that the control method proposed in this study significantly outperforms the traditional double closed-loop control method. Specifically, the proposed method reduces the bus voltage fluctuation range in the presence of load disturbances by 24.07% and decreases the stabilization time by 56.92%. Additionally, the efficiency of the hydrogen fuel cell is enhanced by 31.88%. This control method can be applied to 10 kV DC microgrid systems with distributed energy resources. It aims to reduce the fluctuation amplitude of the DC bus voltage and enhance the system’s ability to withstand transient impact events. Full article

Standalone wind–solar–diesel–storage microgrids serve as a crucial solution for achieving energy self-sufficiency in remote and off-grid areas, such as rural regions and islands, where conventional power grids are unavailable. Addressing scheduling optimization challenges arising from the intermittent nature of renewable energy generation and the uncertainty of load demand, this paper proposes an adaptive optimization scheduling method (DQN-PSO) that integrates Deep Q-Network (DQN) with Particle Swarm Optimization (PSO). The proposed approach leverages DQN to assess the operational state of the microgrid and dynamically adjust the key parameters of PSO. Additionally, a multi-strategy switching mechanism, incorporating global search, local adjustment, and reliability enhancement, is introduced to jointly optimize both clean energy utilization and power supply reliability. Simulation results demonstrate that, under typical daily, high-volatility, and low-load scenarios, the proposed method improves clean energy utilization by 3.2%, 4.5%, and 10.9%, respectively, compared to conventional PSO algorithms while reducing power supply reliability risks to 0.70%, 1.04%, and 0.30%, respectively. These findings validate the strong adaptability of the proposed algorithm to dynamic environments. Further, a parameter sensitivity analysis underscores the significance of the dynamic adjustment mechanism. Full article

Half-bridge converter series microgrid (HBCS-MG) is susceptible to a variety of uncertainties and disturbances during operation, and therefore, the use of the traditional integer-order models cannot accurately reflect the effects of environmental variations on internal components of the off-grid system, such as converters, filters, and loads, including factors like time delays, memory effects, and multi-scale coupling. The fractional-order control method is better equipped to deal with these disturbances, thereby enhancing the robustness and stability of the system. In the off-grid state, a fractional-order PI (FOPI) controller is employed for double-closed-loop control, and the load voltage feedforward control is utilized to offset the impact of load voltage fluctuations on the system. A new simplified equivalent circuit calculation method for the fractional-order inductor is proposed, and a complete fractional mathematical model of the system in the dq rotating coordinate system is established to obtain the transfer function between the load voltage and the input voltage. Furthermore, the impact of the fractional-order variation of the FOPI controllers and the fractional elements on system performance in the frequency domain and time domain is described in detail. The simulation results are compared with the theoretical analysis to demonstrate the accuracy of the mathematical model. The overshoot of the load voltage at the switching instant of 0.7 s is reduced by 4.2% compared with the integer-order PI controller, which proves that the fractional-order controller can improve the system control accuracy. Full article

Energy storage systems based on dual active bridge (DAB) converters are a critical component of DC microgrid systems. To address power oscillations and system stability issues caused by power deficits during the off-grid operation of DC microgrids, a control strategy for DAB energy storage systems based on voltage droop control is proposed. By analyzing the internal operational mechanisms of DAB power electronic converters and integrating voltage droop equations, a small-signal model is constructed to deeply investigate the dynamic characteristics of DAB energy storage systems under off-grid conditions. Using the Nyquist stability criterion, appropriate voltage droop coefficients are selected to enhance system stability. Finally, a DC microgrid model is built on the MATLAB/Simulink simulation platform. Through the rational design of the droop coefficients, the overshoot of the power response is reduced from 28.87% to 4.27%, and settling time is effectively shortened while oscillations are suppressed. The simulation results validate the correctness and effectiveness of the theoretical framework proposed in this study. Full article

To address the challenges of cross-city travel for different types of electric vehicles (EV) and to tackle the issue of rapid charging in regions with weak power grids, this paper presents a strategic approach for locating and sizing highway charging stations tailored to such grid limitations. Initially, considering the initial EV state of charge, a path-demand-based model for EV charging station location–allocation is proposed to optimize station numbers and enhance vehicle flow, which indicates the passing rate of vehicles. Subsequently, a capacity configuration model is formulated, integrating wind, photovoltaic, storage, and diesel generators to manage the stations’ load. This model introduces a new objective function, the annual comprehensive cost, encompassing installation, operation, maintenance, wind and solar curtailment, and diesel generation costs. Simulation examples on north-western cross-city highways validate the efficacy of this approach, showing that the proposed wind–solar storage fast-charging station site selection and capacity optimization model can effectively cater to diverse electric vehicle charging demands. Moreover, it achieves a 90% self-consistency rate during operation across various typical daily scenarios, ensuring a secure and economically viable operational performance. Full article

Current environmental challenges demand immediate action, especially in the transport sector, which is one of the largest CO₂ emitters. Vehicle electrification is considered an essential strategy for emission mitigation and combating global warming. This study presents methodologies for the modeling and energy management of microgrids (MGs) designed as charging stations for electric vehicles (EVs). Algorithms were developed to estimate daily energy generation and charging events in the MG. These data feed an energy management algorithm aimed at minimizing the costs associated with energy trading operations, as well as the charging and discharging cycles of the battery energy storage system (BESS). The problem constraints ensure the safe operation of the system, availability of backup energy for off-grid conditions, preference for reduced tariffs, and optimized management of the BESS charge and discharge rates, considering battery wear. The grid-connected MG used in our case study consists of a wind turbine (WT), photovoltaic system (PVS), BESS, and an electric vehicle fast charging station (EVFCS). Located on a highway, the MG was designed to provide fast charging, extending the range of EVs and reducing drivers’ range anxiety. The results of this study demonstrated the effectiveness of the proposed energy management approach, with the optimization algorithm efficiently managing energy flows within the MG while prioritizing lower operational costs. The inclusion of the battery wear model makes the optimizer more selective in terms of battery usage, operating it in cycles that minimize BESS wear and effectively prolong its lifespan. Full article

At present, the Colombian government is faced with the challenge of guaranteeing access to energy services for all its inhabitants. However, as there are isolated populations or populations with difficult access to conventional electricity grids in the country, it is necessary to seek innovative and appropriate solutions to the conditions and needs of the so-called non-interconnected zones (NIZs), which allow the generation and consumption of energy in a local, efficient, and safe way for all users. For this reason, this research consisted of studying and proposing technological solutions that use distributed energy resources, making the most of the energy potential in each area, as a proposed solution to the problems faced by NIZs with energy shortages. As a result, a series of proposals with microgrids are obtained, taking advantage of their flexible characteristics and using NRES as energy sources, mitigating pollution and contributing to the energy transition sought by the Colombian government. Full article

With the widespread integration of renewable energy into distribution networks, energy storage systems are playing an increasingly critical role in maintaining grid stability and sustainability. Hydrogen, as a key zero-carbon energy carrier, offers unique advantages in the transition to low-carbon energy systems. To facilitate the coordination between hydrogen and renewables, this paper proposes a flexible on-grid and off-grid control method for an electric–hydrogen hybrid AC-DC microgrid which integrates photovoltaic panels, battery energy storage, electrolysers, a hydrogen storage tank, and fuel cells. The flexible control method proposed here employs a hierarchical structure. The upper level adopts a power management strategy (PMS) that allocates power to each component based on the states of energy storage. The lower level utilises the master–slave control where master and slave converters are regulated by virtual synchronous generator (VSG) and active and reactive power (PQ) control, respectively. In addition, a pre-synchronisation control strategy which does not rely on traditional phase-locked loops is introduced to enable a smooth transition from the off-grid to on-grid mode. The electric–hydrogen microgrid along with the proposed control method is modelled and tested under various operating modes and scenarios. The simulation results demonstrate that the proposed control method achieves an effective power dispatch within microgrid and maintains microgrid stability in on- and off-grid modes as well as in the transition between the two modes. Full article

Renewable energy has high volatility in the traditional off-grid AC hydrogen (H₂) production system, which leads to low reliability of the system operation. To address this issue, this paper designs the topology scheme of wind-photovoltaic generation powered off-grid H₂ production system. Firstly, a DC off-grid system topology scheme with the wind turbine (WT) and photovoltaic (PV) is connected to the medium voltage DC bus by two-stage conversion is proposed. The power fluctuation of WT and PV generation systems and the power-adjustable characteristics of electrolyzers are taken into consideration. Meanwhile, the scheme of distributed access of energy storage (ES) to the WT side and PV side to provide the voltage support for the system is proposed. Secondly, the operating characteristics of DC microgrids and AC microgrids under abnormal operating conditions, such as the fault of the source side, the fault of the load side, and communication interruption, are analyzed in this paper. Finally, the electromagnetic transient simulation model of the DC off-grid H₂ production system and the traditional AC off-grid H₂ production system is established. The effectiveness of the proposed topology scheme is verified by simulation of typical operating conditions. Full article

As a global community our use of data is increasing exponentially with emerging technologies such as artificial intelligence (AI), leading to a vast increase in the energy demand for data centres worldwide. Delivering this increased energy demand is a global challenge, which the rapid growth of renewable generation deployment could solve. For many data centre giants such as Google, Amazon, and Microsoft this has been the solution to date via power purchase agreements (PPAs). However, insufficient investment in grid infrastructure globally has both renewable generation developers and data centre developers facing challenges to connect to the grid. This paper considers the costs and carbon emissions associated with stand-alone hybrid renewable and gas generation microgrids that could be deployed either before a grid connection is available, or to allow the data centre to operate entirely off-grid. WindPRO 4.0 software is used to find optimal configurations with wind and solar generation, backed up by battery storage and onsite gas generation. The results show that off-grid generation could provide lower cost and carbon emissions for each of Europe’s data centre hotspots in Frankfurt, London, Amsterdam, Paris, and Dublin. This paper compares each generation configuration to grid equivalent systems and an onsite gas-only generation solution. The results showed that each hybrid renewable generation configuration had a reduced levelized cost of energy (LCOE) and reduced CO₂eq emissions compared to that of its grid and gas-only equivalent. Previous literature does not consider the economic implications caused by a mismatch between generation and consumption. Therefore, this paper introduces a new metric to evaluate and compare the economic performance of each microgrid, the levelized cost of energy utilised (LCOEu) which gives the levelized cost of energy for a given microgrid considering only the energy which is consumed by the data centre. The LCOEu across all sites was found to be between 70 and 102 GBP/MWh with emissions between 0.021 and 0.074 tCO₂eq/MWh. Full article