Hybrid Renewable Energy System Research Articles

Suitability and Socio-Economic Analysis of Hybrid Renewable Energy Systems Deployment in Rural Areas of Abuja, Nigeria

Access to sustainable and reliable electricity remains a pressing challenge in rural areas of Abuja, Nigeria, where grid extension is economically unviable and energy poverty persists. Hybrid Renewable Energy Systems (HRES), combining multiple renewable sources such as solar and wind with backup systems like biogas generators or batteries, have emerged as a viable solution to bridge this gap. This study conducts a geospatial suitability analysis to identify optimal locations for deploying HRES in rural communities of Abuja using Geographic Information Systems (GIS). By integrating environmental, topographic, and socio-economic criteria such as solar irradiance, wind speed, and land use, the study aims to guide stakeholders in prioritizing investment and planning. Data were sourced from satellite imagery, meteorological datasets, and national geographic databases, and analyzed using weighted overlay techniques suitability analysis in ArcGIS. This study successfully conducted a suitability analysis combining solar, wind, and biomass resource layers to identify Bwari (including Kurudu, Shere, Igu, and Kawu), Gwagwalada (Gawu), and Abuja Municipal Area Council (Karu, Orozo, Garki 1, and Nyanya) as the most promising locations for hybrid energy system deployment. The socio-economic analysis shows that energy access in rural FCT is limited, with 43.5% of respondents having limited access to electricity for 0-2 hours daily. Primary energy sources are traditional and polluting, with 35% using firewood, 32% relying on diesel generators, and 1.4% using solar energy. Most respondents are aware of renewable energy, with 86.4% believing it could benefit their community. Biomass resources, such as poultry waste and agricultural residues, are prevalent, with 91.2% willing to contribute financially.

Multi-Objective Optimization of Hybrid Energy Systems

Renewable energy generation can help countries achieve the Sustainable Development Goals by providing clean, safe, reliable and affordable energy. Conventional energy production is impractical due to shortages, high fuel prices and harmful emissions from fossil fuels. Convergence is the best way to address renewable energy issues, because it combines multiple renewable sources simultaneously. This research proposed a hybrid renewable energy system that combines energy from two or more locally accessible sources to meet demand in remote locations. A hybrid solar, wind and biogas grid system has been proposed, evaluated using the homer Pro software and an artificial intelligence technique called the genetic algorithm. The proposed strategy provided low cost, optimal volume, reduced emissions, high reliability. Comparing the results of GA-based optimization and Homer Pro, a clear trend emerged: GA-based optimization showed better performance stability and lower energy costs, which indicates a more economically efficient system. The GA-based optimization also proposed smaller sizes for Homer components, which reduced the net current cost and proved that a system with the same efficiency and reliability could effectively meet the energy requirements of the site.

Solving Optimal Power Flow Problem in Hybrid Renewable Energy Systems Through Hybrid Optimization Algorithm

Solving Optimal Power Flow Problem in Hybrid Renewable Energy Systems Through Hybrid Optimization Algorithm

Optimizing DC-DC converter topologies for enhanced efficiency in hybrid renewable energy systems using hybrid techniques

This paper proposes an innovative hybrid optimization approach to enhance the efficiency of DC-DC converters in hybrid renewable energy systems (HRESs). The method combines Artificial Rabbits Optimization (ARO) for optimal converter design with pseudo-Hamiltonian neural networks (PHNNs) for accurate parameter prediction. Together, ARO and PHNN significantly improve energy utilization and system performance. Implemented in MATLAB, the ARO-PHNN method was benchmarked against Jellyfish Search with Random Decision Forest (JS-RDF), Improved Non-Dominated Sorting Genetic Algorithm II (INSGA-II), Earthquake Algorithm (EA), Particle Swarm Optimization (PSO) with Lightning Attachment Procedure Optimization (PSO-LAPO), and Galactic Swarm Optimization (GSO). Experimental results show that ARO-PHNN outperforms all competitors, achieving a peak efficiency of 98.1%. It also demonstrates strong statistical performance, with a mean of 0.9421, a median of 0.8612, and a low standard deviation (SD) of 0.0065, indicating high accuracy, stability, and consistency. These results validate the ARO-PHNN method as a robust solution for efficient and reliable energy conversion in HRES.

Improvement of the Hybrid Renewable Energy System for a Sustainable Power Supply of Transportation Infrastructure Objects

This paper shows that using renewable energy sources in the power supply of transportation infrastructure is gradually becoming a new trend. Renewable energy systems are already valuable for railway and automotive infrastructure in various countries; however, this use is limited. This paper examines the improvement of control in a grid-connected, hybrid renewable energy system to meet the needs of a railway transportation infrastructure object by utilizing an additional diesel generator in autonomous mode. The aim is to reduce the depth of battery discharge and limit energy consumption from the grid during peak demand hours, considering the wide fluctuations in power consumption of the object and deviations in renewable energy generation relative to the forecast. Additionally, the task of ensuring long-term autonomous operation of the system is addressed. A control system is proposed based on the deviation of the battery’s state of charge relative to a set schedule, which is determined according to the forecast using an additional variable that sets the power consumption limit. This ensures the minimum possible depth of discharge and peak consumption, taking into account the generation of renewable energy sources, with a power-increase factor ranging from 1 to 1.5 relative to the calculated value. In autonomous mode, the task of minimizing energy consumption by the diesel generator is addressed. Solutions have been developed to implement control in grid and autonomous modes with the corresponding calculation algorithm. The system is not sensitive to the load schedule, and the battery’s depth of discharge limitations are maintained even when renewable energy generation is below the forecast by up to 20%. When generating renewable energy sources below the average monthly value in summer, it is possible to maintain a DoD of no less than 60%.

Modeling and Simulation of Grid-Connected Hybrid Renewable Energy Systems Using HOMER Pro Software

This paper presents a techno-economic evaluation of three hybrid renewable energy configurations for the electrification of Khadva village in the Kutch district of Gujarat, India. Using HOMER Pro software, the study analyzes three scenarios: Case 1 (PV + Grid + Battery), Case 2 (Wind + Grid + Battery), and Case 3 (PV + Wind + Grid + Battery), assessing their performance based on Total Net Present Cost (NPC), Levelized Cost of Energy (COE), capital and operating expenditures, renewable fraction, and grid dependency. Among the evaluated options, Case 3 emerged as the most optimal configuration, offering the lowest NPC (₹1.23 Cr) and COE (₹7.18/kWh), along with the highest renewable fraction (63.4%), indicating effective integration of solar and wind resources with minimal reliance on grid electricity. Case 2 also showed competitive performance with considerable renewable contribution (58.3%) and moderate costs, while Case 1, though simpler in design, resulted in the highest COE and the lowest renewable contribution (9.4%). The results underscore the value of combining diverse renewable sources to enhance system reliability, sustainability, and economic viability in rural electrification. This analysis provides a practical framework for optimizing decentralized hybrid energy systems in off-grid or weak-grid regions, promoting clean energy access in remote areas.

Sustainable rural electrification: Energy-economic feasibility analysis of autonomous hydrogen-based hybrid energy system

Sustainable rural electrification: Energy-economic feasibility analysis of autonomous hydrogen-based hybrid energy system

Hybrid renewable energy systems towards sustainable development in Bangladesh: Configurations, optimizations, applications, challenges and future pathways

Hybrid renewable energy systems towards sustainable development in Bangladesh: Configurations, optimizations, applications, challenges and future pathways

Systematic review of hydrogen, biomass, biogas, and solar photovoltaics in hybrid renewable energy systems: Advancements, challenges, and future directions

Systematic review of hydrogen, biomass, biogas, and solar photovoltaics in hybrid renewable energy systems: Advancements, challenges, and future directions

Cost determination of water production in a nanofiltration desalination plant powered by a hybrid renewable energy system. Case study of Cobquecura, Chile

Cost determination of water production in a nanofiltration desalination plant powered by a hybrid renewable energy system. Case study of Cobquecura, Chile

Optimizing Hybrid Renewable Energy Systems for Isolated Applications: A Modified Smell Agent Approach

This paper presents the optimal sizing of a hybrid renewable energy system (HRES) for an isolated residential building using modified smell agent optimization (mSAO). The paper introduces a time-dependent approach that adapts the selection of the original SAO control parameters as the algorithm progresses through the optimization hyperspace. This modification addresses issues of poor convergence and suboptimal search in the original algorithm. Both the modified and standard algorithms were employed to design an HRES system comprising photovoltaic panels, wind turbines, fuel cells, batteries, and hydrogen storage, all connected via a DC-bus microgrid. The components were integrated with the microgrid using DC-DC power converters and supplied a designated load through a DC-AC inverter. Multiple operational scenarios and multi-objective criteria, including techno-economic metrics such as levelized cost of energy (LCOE) and loss of power supply probability (LPSP), were evaluated. Comparative analysis demonstrated that mSAO outperforms the standard SAO and the honey badger algorithm (HBA) used for the purpose of comparison only. Our simulation results highlighted that the PV–wind turbine–battery system achieved the best economic performance. In this case, the mSAO reduced the LPSP by approximately 38.89% and 87.50% over SAO and the HBA, respectively. Similarly, the mSAO also recorded LCOE performance superiority of 4.05% and 28.44% over SAO and the HBA, respectively. These results underscore the superiority of the mSAO in solving optimization problems.

Evaluating the feasibility of a photovoltaic-wind-diesel-battery hybrid microgrid for sustainable off-grid electrification in Dakhla, Morocco

Hybrid renewable energy systems (HRES) present a promising solution for improving energy reliability and reducing costs in remote, off-grid areas. This study explores the feasibility of implementing an HRES in Dakhla, Morocco, where conventional electrical infrastructure is lacking. By integrating photovoltaic (PV) panels, wind turbines, diesel generators, and battery storage, this study aims to optimize energy resource management while balancing technical performance and economic viability. Using real- world data on energy consumption, climatic conditions, and installation constraints, advanced simulation tools such as HOMER were employed to evaluate both technical and economic parameters. The objective was to minimize the cost of energy (COE) while ensuring reliability, availability, and a high renewable fraction. The results, compared with optimization algorithms like genetic algorithm (GA), particle swarm optimization (PSO), and simulated annealing (SA), revealed the PV-wind-diesel-battery configuration as the most cost-effective solution. This configuration resulted in a net present cost (NPC) of $829,380, a COE of $0.160/kWh, and minimal CO2 emissions of 54.9 kg/year. The findings highlight the viability of this hybrid microgrid as a sustainable off-grid electrification solution and emphasize the role of renewable energy in addressing global energy challenges.

In-depth evaluation and enhancement of a PV-wind combined system: A case study at the Engineering Faculty of Wahid Hasyim University

Energy sustainability is crucial for mitigating climate change and reducing dependence on fossil fuels. This research evaluates a hybrid renewable energy system combining photovoltaic (PV) technology and wind turbines to meet the electricity demand of Wahid Hasyim University's Faculty of Engineering, totalling 555,000 VA. Using HOMER Pro software, the study identifies the optimal configuration based on technical, economic, and environmental aspects. The hybrid system integrating PV, wind turbines, batteries, and converters achieves the lowest Net Present Cost (NPC) of $214,877 and a Levelized Cost of Energy (LCOE) of $0.0185/kWh, outperforming grid-only systems. Environmentally, the system significantly reduces carbon dioxide (CO2) emissions, from 559,226 kg/yr in conventional systems to 62,452 kg/yr. Solar energy contributes 56% of electricity generation, leveraging stable solar radiation of 4.28–5.54 kWh/m²/day. Additionally, an annual surplus of 156,350 kWh can be sold back to the grid, enhancing operational efficiency. This study demonstrates that hybrid renewable energy systems deliver long-term cost efficiency and significantly mitigate climate impacts. It provides a sustainable energy model for campuses in Indonesia and worldwide, particularly in regions with abundant solar resources.

Evaluating the feasibility and sustainability of hybrid renewable energy systems (HRES) for electric vessel charging applications: A case study in Donsol, Sorsogon, Philippines

Evaluating the feasibility and sustainability of hybrid renewable energy systems (HRES) for electric vessel charging applications: A case study in Donsol, Sorsogon, Philippines

Assessment using MCDM approach of renewable hybrid energy system with hydrogen production capability

Assessment using MCDM approach of renewable hybrid energy system with hydrogen production capability

Retraction notice to “Power generation cost minimization of the grid-connected hybrid renewable energy system through optimal sizing using the modified seagull optimization technique” [Energy Rep. 6 (2020) 3365–3376

Retraction notice to “Power generation cost minimization of the grid-connected hybrid renewable energy system through optimal sizing using the modified seagull optimization technique” [Energy Rep. 6 (2020) 3365–3376

Multi-objective optimization of hybrid renewable energy systems with green hydrogen integration and hybrid storage strategies

Multi-objective optimization of hybrid renewable energy systems with green hydrogen integration and hybrid storage strategies

Analysis of Hybrid Renewable Energy Systems for European islands: Market Dynamics, Opportunities and Challenges

Analysis of Hybrid Renewable Energy Systems for European islands: Market Dynamics, Opportunities and Challenges

Predictive analytics for sustainable energy: An in-depth assessment of novel Stacking Regressor model in the off-grid hybrid renewable energy systems

Predictive analytics for sustainable energy: An in-depth assessment of novel Stacking Regressor model in the off-grid hybrid renewable energy systems

Optimal planning and feasibility analysis of a grid-connected PV-biomass hybrid renewable energy system for rural electrification with electric vehicles: A case study of Hainan, China

Optimal planning and feasibility analysis of a grid-connected PV-biomass hybrid renewable energy system for rural electrification with electric vehicles: A case study of Hainan, China