Search Results (235)

Accurate short-term forecasting of renewable energy sources is essential for stable and efficient microgrid operation. Existing models primarily focus on either solar or wind prediction, often neglecting their combined stochastic behavior within isolated systems. This study presents a comparative evaluation of three machine-learning models—Random Forest, ANN, and LSTM—for short-term solar and wind forecasting in microgrid environments. Historical meteorological data and power generation records are used to train and validate three ML models: Random Forest, Long Short-Term Memory, and Artificial Neural Networks. Each model is optimized to capture nonlinear and rapidly fluctuating weather dynamics. Forecasting performance is quantitatively evaluated using Mean Absolute Error, Root Mean Square Error, and Mean Percentage Error. The predicted values are integrated into a microgrid energy management system to enhance operational decisions such as battery storage scheduling, diesel generator coordination, and load balancing. Among the evaluated models, the ANN achieved the lowest prediction error with an MAE of 64.72 kW on the one-year dataset, outperforming both LSTM and Random Forest. The novelty of this study lies in integrating multi-source data into a unified ML-based predictive framework, enabling improved reliability, reduced fossil fuel usage, and enhanced energy resilience in remote microgrids. This research used Orange 3.40 software and Python 3.12 code for prediction. By enhancing forecasting accuracy, the project seeks to reduce reliance on fossil fuels, lower operational costs, and improve grid stability. Outcomes will provide scalable insights for remote microgrids transitioning to renewables. Full article

Decarbonizing industry, improving urban sustainability, and expanding clean energy use are key global priorities. This study presents a techno-economic analysis (TEA) and life-cycle assessment (LCA) of green hydrogen (GH₂) production via water electrolysis for low-carbon applications in the Central Asian region, with Uzbekistan considered as a representative case study. Solar PV and wind power are used as renewable electricity sources for a 44 MW electrolyzer. The assessment also incorporates recent advances in alkaline water electrolyzers (AWE) enhanced with metal–organic framework (MOF) materials, reflecting improvements in efficiency and hydrogen output. The LCA, performed using SimaPro, evaluates the global warming potential (GWP) across the full hydrogen production chain. Results show that the MOF-enhanced AWE system achieves a lower levelized cost of hydrogen (LCOH) at 5.18 $/kg H₂, compared with 5.90 $/kg H₂ for conventional AWE, with electricity procurement remaining the dominant cost driver. Environmentally, green hydrogen pathways reduce GWP by 80–83% relative to steam methane reforming (SMR), with AWE–MOF delivering the lowest footprint at 1.97 kg CO₂/kg H₂. In transport applications, fuel cell vehicles powered by hydrogen derived from AWE–MOF emit 89% less CO₂ per 100 km than diesel vehicles and 83% less than using SMR-based hydrogen, demonstrating the substantial climate benefits of advanced electrolysis. Overall, the findings confirm that MOF-integrated AWE offers a strong balance of economic viability and environmental performance. The study highlights green hydrogen’s strategic role in the Central Asian region, represented by Uzbekistan’s energy transition, and provides evidence-based insights for guiding low-carbon hydrogen deployment. Full article

To address the heat transfer degradation caused by fouling and dust accumulation on the stator windings of marine diesel generators, this study proposes a health condition assessment method based on the convective heat transfer coefficient. A numerical analysis model was developed using the Ansys Fluent platform to systematically investigate the effects of ambient temperature, load power, and fouling layer thickness on the stator winding temperature and convective heat transfer coefficient. The results demonstrate that the convective heat transfer coefficient is highly sensitive to variations in fouling layer thickness. On this basis, a health assessment model centered on the convective heat transfer coefficient was established and validated using experimental data from diesel generator tests. The results show that the proposed model accurately captures the performance degradation process and enables quantitative classification of operating states, including healthy, sub-healthy, degraded, and abnormal conditions. This research provides a feasible theoretical foundation and technical approach for the intelligent monitoring and condition evaluation of marine diesel generators, offering significant engineering value for enhancing the efficiency and reliability of marine power systems. Full article

The use of non-renewable energy resources is one of the main drivers of climate change. In response, the United Nations established the seventh Sustainable Development Goal, “Affordable and clean energy”, which promotes the transition toward renewable and environmentally friendly sources such as wind and solar energy. However, the intermittent nature of these resources poses challenges for maintaining a stable, continuous power supply, highlighting the need for hybrid technology approaches, such as Hybrid Renewable Energy Systems (HRES), which integrate complementary renewable sources with energy storage. In this context, this study applies a Particle Swarm Optimisation (PSO)-based approach to determine the optimal sizing and operating strategy for a hybrid system comprising photovoltaic, wind, battery storage, and diesel backup units under various synthetic load profiles. The results indicate that diesel-assisted configurations achieve lower levelized costs of energy (0.23–0.35 USD/kWh) and maintain high reliability (LPSP < 0.25%), although at the expense of higher fuel consumption and CO₂ emissions. Conversely, fully renewable configurations present higher energy costs (0.29–0.44 USD/kWh), but reduce annual CO₂ emissions by up to 50% and create more employment opportunities, particularly in regions with abundant wind resources such as La Guajira, Colombia. Full article

The “double-high” characteristics of power systems—namely, the high penetration of renewable energy and the widespread use of power electronic devices—have significantly increased operational complexity. This underscores the necessity of adopting coordinated energy storage systems and wind-storage hybrid microgrids to support the black start restoration of thermal power plants. This paper addresses two critical challenges in the black start process of a wind–storage–diesel microgrid: dynamic power coordination and state of charge (SOC) balancing of the energy storage system. A coordinated control strategy is proposed for the entire black start sequence, incorporating SOC equilibrium management. A novel hybrid control architecture is introduced, which effectively integrates grid-forming virtual synchronous generator (VSG)-based energy storage units with grid-following P/Q-controlled storage units, while leveraging the dynamic reactive power support capability of diesel generators. By coordinating SOC balancing among storage units and combining diesel generation with wind power maximum power point tracking (MPPT) control, the strategy enables wind power output to effectively track microgrid load demand. It also ensures reliable reactive power support to prevent black start failure. During periods of power imbalance between wind generation and black start loads, the energy storage system compensates for active power discrepancies. Furthermore, control schemes for both grid-forming and grid-following storage units are enhanced to achieve SOC-based active power distribution, ensuring balanced SOC levels across all units. Finally, a simulation model for the wind–storage–diesel black start is developed in PSCAD/EMTDC, validating the effectiveness and robustness of the proposed control strategy. Full article

Under the environment of globalized energy restructuring and achieving the goal of “peak carbon and carbon neutrality”, this paper proposes an optimal scheduling method based on the improved cosine algorithm for island microgrids, which relies on diesel generators, resulting in high carbon emissions and high operating costs. First, an optimal scheduling model for island microgrids is established with the objective of minimizing the system operating cost, which comprehensively considers the carbon emission penalty, power balance constraints, equipment operation constraints, and the volatility of renewable energy sources. Secondly, the traditional sine–cosine algorithm is improved by introducing an adaptive adjustment factor, elite retention strategy and chaotic mapping initialization population in order to solve its shortcomings of falling into local optimums and insufficient convergence accuracy when solving high-dimensional complex problems. Finally, the effectiveness of the proposed method is verified by simulation experiments. The results show that the method in this paper reduces the total system cost to 2994.2 yuan (6.5% lower than the baseline scenario), reduces the carbon emission to 968.8 kg (55.1% lower), and improves the wind and light consumption rate to 98.84%, which is an obvious advantage and provides a theoretical basis and technical support for the realization of the low-carbon and economic operation of island microgrids. Full article

The maritime industry is under increasing pressure to reduce greenhouse gas emissions, especially in countries such as Saudi Arabia that are actively working to transition to cleaner energy. In this paper, a new hybrid shipboard power system, which incorporates wind turbines, solar photovoltaic (PV) panels, proton-exchange membrane fuel cells (PEMFCs), and a battery energy storage system (BESS) together for propulsion and hotel load services, is proposed. A multi-loop Energy Management System (EMS) based on proportional–integral control (PI) is developed to coordinate the interconnections of the power sources in real time. In contrast to the widely reported model predictive or artificial intelligence optimization schemes, the PI-derived EMS achieves similar power stability and hydrogen utilization efficiency with significantly reduced computational overhead and full marine suitability. By taking advantage of the high solar irradiance and coastal wind resources in Saudi Arabia, the proposed configuration provides continuous near-zero-emission operation. Simulation results show that the PEMFC accounts for about 90% of the total energy demand, the BESS (±0.4 MW, 2 MWh) accounts for about 3%, and the stationary renewables account for about 7%, which reduces the demand for hydro-gas to about 160 kg. The DC-bus voltage is kept within ±5% of its nominal value of 750 V, and the battery state of charge (SOC) is kept within 20% to 80%. Sensitivity analyses show that by varying renewable input by ±20%, diesel consumption is ±5%. These results demonstrate the system’s ability to meet International Maritime Organization (IMO) emission targets by delivering stable near-zero-emission operation, while achieving high hydrogen efficiency and grid stability with minimal computational cost. Consequently, the proposed system presents a realistic, certifiable, and regionally optimized roadmap for next-generation hybrid PEMFC–battery–renewable marine power systems in Saudi Arabian coastal operations. Full article

Remote northern regions face unique energy challenges due to geographic isolation, harsh climates, and limited access to centralized power grids. In response to growing environmental and economic pressures, there is a rising interest in hybrid energy systems that integrate renewable and conventional sources. This study investigates sustainable and cost-effective energy supply strategies for off-grid northern communities through the modeling and simulation of multi-energy microgrids. Focusing on case studies from Yakutia (Russia), Hordaland (Norway), and Alaska (United States), the research employs a comprehensive methodology that combines a critical literature review, system design using HOMER Pro software (version 3.16.2), and a comparative analysis of simulation outcomes. Three distinct microgrid configurations are proposed, incorporating various combinations of solar photovoltaic (PV), wind energy, diesel generators, and battery storage systems. The findings reveal that integrating solar PV significantly enhances economic efficiency, particularly in regions with high solar irradiance, underscoring its pivotal role in shaping resilient, sustainable energy systems for remote northern areas. This study is innovative in its cross-regional comparative approach, linking techno-economic simulation with climatic variability analysis to identify context-specific energy strategies. The key findings highlight how hybrid microgrids combining PV, wind, and storage systems can reduce both costs and emissions by up to 35% compared to diesel-only systems, offering practical pathways toward sustainable electrification in high-latitude regions. Full article

The rural community of L’Anse au Loup in southern Labrador depends on a long-distance transmission link to Hydro-Québec for its electricity supply, with diesel generation as backup during outages. This dependence raises electricity costs, exposes the community to supply disruptions, and limits control over local energy security. This study evaluates the feasibility of a solar–wind hybrid energy system to reduce imported electricity and improve supply reliability. A detailed site assessment identified a 50-hectare area north of the community as suitable for system installation, offering adequate space and minimal land-use conflict. Using Hybrid Optimization of Multiple Energy Resources (HOMER Pro 3.18.3) software, the analysis modeled local load data, renewable resource profiles, and financial parameters to determine the optimal grid-connected configuration. The optimized design installs 19.25 MW of photovoltaic (PV) and 4.62 MW of wind capacity, supported by inverters and maximum power point tracking (MPPT) to ensure stable operation. Simulations show that the hybrid system supplies about 70% of annual demand, cuts greenhouse gas emissions by more than 95% compared with conventional generation, and lowers long-term energy costs. The results confirm that the proposed configuration can strengthen local energy security and provide a replicable framework for other remote and coastal communities in Newfoundland and Labrador pursuing decarbonization. Full article

Vertical-Axis Wind Turbines (VAWTs) are efficient solutions for renewable energy generation, especially in regions with variable wind conditions. This study presents an optimized design of a small-scale H-type VAWT through the integration of Design of Experiments (DOE) and Computational Fluid Dynamics (CFD), using a fractional factorial 2^k−p approach to evaluate the influence of geometric and operational parameters on power output and power coefficient (Cp), which ranged from 0.15 to 0.35. The research began with a comprehensive assessment of renewable resources in Isla Fuerte, Colombia. Solar analysis revealed an average of 5.13 Peak Sun Hours (PSHs), supporting the existing 175 kWp photovoltaic system. Wind modeling, based on meteorological data and Weibull distribution, showed speeds between 2.79 m/s and 5.36 m/s, predominantly from northeast to northwest. Under these conditions, the NACA S1046 airfoil was selected for its aerodynamic suitability. The turbine achieved power outputs from 0.46 W to 37.59 W, with stabilization times analyzed to assess dynamic performance. This initiative promotes environmental sustainability by reducing reliance on Diesel Generators (DGs) and empowering local communities through participatory design and technical training. The DOE-CFD methodology offers a replicable model for energy transition in insular regions of developing countries, linking technical innovation with social development and education. Full article

This report evaluates the role of Hybrid Renewable Energy Systems (HRESs) in supporting South Africa’s energy transition amidst persistent power shortages, coal dependency, and growing decarbonisation imperatives. Drawing on national policy frameworks including the Integrated Resource Plan (IRP 2019), the Just Energy Transition (JET) strategy, and Net Zero 2050 targets, this study analyses five major HRES configurations: PV–Battery, PV–Diesel–Battery, PV–Wind–Battery, PV–Hydrogen, and Multi-Source EMS. Through technical modelling, lifecycle cost estimation, and trade-off analysis, the report demonstrates how hybrid systems can decentralise energy supply, improve grid resilience, and align with socio-economic development goals. Geographic application, cost-performance metrics, and policy alignment are assessed to inform region-specific deployment strategies. Despite enabling technologies and proven field performance, the scale-up of HRESs is constrained by financial, regulatory, and institutional barriers. The report concludes with targeted policy recommendations to support inclusive and regionally adaptive HRES investment in South Africa. Full article

Energy is a vital component of life today, and providing reliable power access remains a significant global challenge, particularly in remote areas. In Egypt, several isolated regions, including parts of South Sinai, suffer from limited electricity access. This study presents an enhanced environmental and techno-economic modeling of an off-grid hybrid renewable energy microgrid (HREM) tailored for such regions. A proposed configuration combining photovoltaic (PV) panels, wind turbines (WTs), a converter (CONV), and battery energy storage is evaluated to meet the residential energy demand of an isolated community in South Sinai. Four feasible system models, PV/CONV/BAT, WT/CONV/BAT, PV/WT/CONV/BAT, and a standalone diesel generator, were simulated using hybrid optimization of multiple energy resources. The cost of energy was analyzed under different scenarios. The results show that the combination of a 1109 kW PV system, 16 × 25 kW WTs, 439 kW converter, and 353 batteries is the best configuration that leads to the lowest values of Net Present Cost (NPC) and Levelized Cost of Energy (COE), and zero unmet load, making it the most economically and environmentally viable configuration. Full article

Islanded microgrids face significant frequency stability challenges due to limited system capacity, low inertia levels, and the strong variability in renewable energy sources. Traditional reliability assessment methods, often based on static power balance, struggle to comprehensively reflect frequency dynamic characteristics and their impact on power supply reliability. To address this issue, this paper proposes a sequential Monte Carlo reliability assessment method integrated with a system frequency response model. First, an SFR model for the isolated microgrid, incorporating diesel generators, gas turbines, energy storage, and wind turbines, is established. For synchronous units, a frequency deviation-based failure rate correction mechanism is introduced to characterize the impact of frequency fluctuations on equipment reliability. State transitions are achieved by integrating failure and repair rates to reach threshold values. Second, sequential Monte Carlo simulation is employed to conduct time-series simulations of annual operation. Random sampling of unit failure and repair times is used to calculate reliability metrics. MATLAB/Simulink simulation results demonstrate that system frequency fluctuations caused by power imbalance worsen unit failure rates, leading to microgrid reliability values lower than static calculations. This provides reference for planning, design, and operational scheduling of isolated microgrids. Full article

This study models different hybrid systems based on renewable energies that can be supported by diesel generators to meet the energy needs of isolated homes in the Canary Islands. The research will cover the energy requirements of a residential house, including the production of fresh water using a reverse osmosis desalination plant. The system is designed to operate independently of the electrical grid. The HOMER software package was used to model and optimize the hybrid systems. The model was fed with data on the electrical demands of residential homes (including the consumption by the small reverse osmosis desalination plant) as well as the technical specifications of the various devices and renewable energy sources, such as solar radiation and wind speed potentials. The software considers various configurations to optimize hybrid systems, selecting the most suitable one based on the available renewable energy sources at the selected location. The data used in the research were collected on the eastern islands of the Canary Islands (Gran Canaria, Lanzarote and Fuerteventura). Based on the system input parameters, the simulation and optimization performed in HOMER, taking into account the lowest “Levelized Cost of Energy”, it can be concluded that the preferred hybrid renewable energy system for this region is a small wind turbine with a nominal power of 1.9 kW, eight batteries, and a small diesel generator with a nominal power of 1.0 kW. The knowledge from this research could be applied to other geographical areas of the world that have similar conditions, namely a shortage of water and plentiful renewable energy sources. Full article

To address the severe damage and outage risks to distribution networks caused by extreme weather, this paper proposes a coordinated optimization strategy for distribution network repair sequencing and rapid restoration, which considers multi-source collaboration and incomplete fault information. In response to the challenge of incomplete fault information after a disaster, a two-layer robust optimization model is constructed. The upper-layer model aims to minimize the completion time of repairs for all faults under the most unfavorable fault scenario to obtain a robust repair time for potential faulty lines, providing a reliable basis for the restoration decisions of the lower-layer model. The lower-layer model’s objective is to maximize the weighted restored load quantity by comprehensively coordinating mobile diesel generators (MDGs), distributed generators (DGs), photovoltaics (PVs), wind turbines (WTs), and energy storage systems (ESSs) to achieve the optimal restoration strategy. The proposed service restoration strategy is validated through simulation on a modified IEEE 33-bus power system, and the results demonstrate that the strategy can efficiently and comprehensively utilize multi-source collaborative resources and improve the resilience of the distribution network. Full article