Renewable Energy Focus最新文献

{"title":"A framework for load frequency regulation in multi-area grid-connected hybrid power systems with plug-in electric vehicles","authors":"Muhammad Majid Gulzar ,&nbsp;Ahlam Jameel ,&nbsp;Salman Habib ,&nbsp;Ali Arishi ,&nbsp;Rasmia Irfan ,&nbsp;Hasnain Ahmad ,&nbsp;Huma Tehreem","doi":"10.1016/j.ref.2025.100714","DOIUrl":"10.1016/j.ref.2025.100714","url":null,"abstract":"<div><div>Due to technological advancements, the rapid expansion of renewable energy in the power sector has led to challenges with operation, security, and management. Reduced grid inertia necessitates maintaining normal operating frequency and lowering tie-line power changes to assure stability and reliability. In this article, a framework for load frequency controller (LFC) that is based on the combinations of traditional controllers is proposed. In this study, the filtered derivative proportional controller cascaded with <span><math><mi>β</mi></math></span> proportional integral, abbreviated as <span><math><mrow><msub><mrow><mi>PD</mi></mrow><mi>F</mi></msub><mo>+</mo><mrow><mo>(</mo><mi>β</mi><mo>+</mo><mi>P</mi><mi>I</mi><mo>)</mo></mrow></mrow></math></span>, is suggested for LFC applications. In addition, the optimization of the proposed controller parameters for two-area power grids is tuned using the grasshopper optimization algorithm (GOA). The contribution of aggregated model for electric vehicles (EVs) is also taken into consideration. The performance of the proposed controller is evaluated with the effectiveness of other controllers like cascaded proportional integral and derivative (PI-PD), <span><math><mrow><mn>1</mn></mrow></math></span> plus proportional integral derivative (1+PID), <span><math><mrow><mn>1</mn></mrow></math></span> plus proportional integral (1+PI), and fractional order proportional integral derivative (FOPID). The proposed GOA optimizer tuned <span><math><mrow><msub><mrow><mi>PD</mi></mrow><mi>F</mi></msub><mo>+</mo><mrow><mo>(</mo><mi>β</mi><mo>+</mo><mi>P</mi><mi>I</mi><mo>)</mo></mrow></mrow></math></span> controller is tested for reliability against variations in load, penetration of renewable energy sources, and parametric uncertainties of the grid for the time integral absolute error (ITAE) objective function. By employing the proposed controller, the system achieves rapid and efficient minimization of the objective function. Thus, the controller is highly suitable for applications requiring quick response and precise performance.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100714"},"PeriodicalIF":4.2,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143895545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing smart nano grid control strategies through virtual environment and hybrid deep learning approaches","authors":"Ibrahim Sinneh Sinneh,&nbsp;Yanxia Sun Yanxia","doi":"10.1016/j.ref.2025.100712","DOIUrl":"10.1016/j.ref.2025.100712","url":null,"abstract":"<div><div>Smart nano grids face enormous challenges stemming from variations in time demand and risks from cyber threats, which lead to their inefficiency and unstable operation. To overcome these difficulties, this study presents a novel “Federated Reinforced LSTM-Crayfish Whale Optimization Detection (FRLC-WOD)” procedure. The system proposed here integrates Reinforcement-LSTM-Crayfish Optimization Technique (RL-LSTM-CAO) and Federated Graph Whale Optimization Intrusion Detection (FG-WOA-ID) to improve adaptability, efficiency, and security. The RL-LSTM-CAO methodology employs Bi-directional Long Short-Term Memory (Bi-LSTM) for accurate forecasting, Reinforcement Learning-based Power Distribution (RL-PD) for real-time adaptability, and Crayfish Optimization Algorithm (CAO) for optimal energy management. On the other hand, FG-WOA-ID employs Federated Learning for decentralized anomaly detection, Graph Neural Networks for intrusion detection, and Whale Optimization Algorithm for cybersecurity measures adaptation. The results of the experiments achieved a grid stability improvement of 95 %, an energy efficiency improvement of 92 %, a response time of 1.5 s, and a 95 % improved cyber threat resistance, outperforming existing standard methodologies such as EMS GWO-OSA, RNN, and MPPT. This will show how the proposed method significantly upgrades the delivery of reliable and optimized operations for smart nano grids.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100712"},"PeriodicalIF":4.2,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the multiple dimensions of solar irrigation in South-Asian countries: Insights from a systematic review","authors":"Vanshika Gupta,&nbsp;S.P. Singh","doi":"10.1016/j.ref.2025.100711","DOIUrl":"10.1016/j.ref.2025.100711","url":null,"abstract":"<div><div>Solar irrigation pumps (SIP) ensure reliable, non-pollutant and cost-effective irrigation, especially in regions with high groundwater reliance and ample solar irradiance, like South Asia. Despite the various benefits of solar pumps over fossil-fuel-based pumps, their adoption remains scanty in selected South-Asian countries, i.e., India, Bangladesh, Pakistan, and Nepal. This study performs a systematic literature review to (i) Identify multiple drivers, barriers and impacts of solar irrigation that affect SIP’s scalability in South Asia. (ii) Highlights various dimensions responsible for the cross-country disparity in the number of solar pumps and investigates major challenges and complexities in the upscaling of SIP in South Asia. The review results indicate that capital subsidies, low operational costs, reliable water supply, and long life span influenced the adoption of solar irrigation systems in these countries. The major factors for the cross-country disparity in the adoption rate of solar pumps are government policy framework, geography and international aid. The paper concludes with several research gaps that could guide further studies.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100711"},"PeriodicalIF":4.2,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143855974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal planning of biogas production in a set of batch biodigesters","authors":"Arthur Barreto ,&nbsp;Sanja Petrovic ,&nbsp;Edilaine Soler ,&nbsp;Helenice Florentino ,&nbsp;Adriana Cherri","doi":"10.1016/j.ref.2025.100706","DOIUrl":"10.1016/j.ref.2025.100706","url":null,"abstract":"<div><div>The use of organic wastes from industrial, agro-industrial, and household sources has become an essential strategy for generating renewable and sustainable energy. Organic materials processed in biodigesters offer two major benefits: the production of biogas (a renewable energy source) and the creation of biofertilizers (which can enhance agricultural productivity). These benefits increased the interest from both researchers and industry leaders in finding more efficient ways to manage biomass for energy production. One area that has not been thoroughly explored is the scheduling of biogas production in batch biodigesters to meet fluctuating energy demand over time. Biodigesters typically operate in batches, where the substrate is loaded into the system and left to digest for a set period. However, the timing and amount of substrate to be processed are critical issues as the energy demand may vary, and managing production surpluses or shortages is crucial. In this context, a novel integer linear mathematical model has been proposed to address the biogas production scheduling problem. The model focuses on balancing the biogas demand with the operational constraints of biodigesters, such as their availability and production cycles. Several experimental tests have been conducted to validate the model’s effectiveness. These tests varied parameters as the biogas demand type, the length of the planning horizon, and the number of biodigesters with different production cycles.The results demonstrate that the proposed model effectively supports decision-making processes for biogas production planning, contributing to cleaner energy systems and sustainable resource management.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100706"},"PeriodicalIF":4.2,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143844650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of a geothermal-solar cooling unit based on a compressor-assisted absorption chiller","authors":"Evangelos Bellos,&nbsp;Dimitra Gonidaki,&nbsp;John K. Kaldellis","doi":"10.1016/j.ref.2025.100713","DOIUrl":"10.1016/j.ref.2025.100713","url":null,"abstract":"<div><div>The objective of this work is the design of a hybrid absorption chiller that is fed by renewable energies. A single-effect absorption chiller operating with LiBr/water working pair is the main device of this work which incorporates an extra mechanical compressor between the evaporator and the absorber. The heat input in the hybrid system is given by a geothermal heat source of 92^οC driving temperature, while the compressor is fed by electricity produced by photovoltaics. The system operates in hybrid mode only when there is available solar irradiation. The analysis is parametric, but there is also dynamic analysis through an hourly-based model. The studied period is from May to September when there is cooling demand, and the studied location is Lesbos Island in Greece. It was found that the hybrid chiller driven by geothermal and solar energy leads to 21.21 % higher cooling production during the season compared to the conventional absorption chiller driven by a geothermal field. The increase is higher in the warmest months, something that indicates the high importance of the compressor assistance in the system. However, the cooling production during the warmest months is lower compared to the other summer periods due to the rise in the system’s heat rejection efficiency and the reduction of PV output during the warmest periods of the day. The seasonal system energy efficiency was found to be 28.86% and the respective exergy efficiency at 15.41 %.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100713"},"PeriodicalIF":4.2,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial neural network-based enhanced distance protection sensitivity in microgrids","authors":"Ahmed N. Sheta ,&nbsp;Abdelfattah A. Eladl ,&nbsp;Bishoy E. Sedhom ,&nbsp;Magda I. El-Afifi ,&nbsp;Padmanaban Sanjeevikumar ,&nbsp;Mohamed Zaki","doi":"10.1016/j.ref.2025.100710","DOIUrl":"10.1016/j.ref.2025.100710","url":null,"abstract":"<div><div>The integration of distributed energy resources (DERs) into microgrids introduces dynamic operational challenges that conventional distance relays struggle to address, particularly under variable network topologies, load fluctuations, and DER intermittency. This paper proposes an artificial neural network (ANN)-enhanced distance protection scheme to improve fault detection accuracy, classification, and localization in DER-rich microgrids. A 20-layer ANN model, trained on 50 fault scenarios encompassing 11 fault types (including phase-to-phase, phase-to-ground, and high-impedance faults up to 50 Ω) and non-fault conditions, processes raw three-phase and ground impedance measurements directly. The ANN achieves a mean squared error (MSE) of 0.0143 at epoch 21, with binary outputs enabling rapid fault identification (within two power cycles) and classification. Validated under grid-connected and islanded modes with DER penetration levels of 20–80 %, the scheme demonstrates 98.7 % accuracy, 97 % noise resilience at 20 dB SNR, and precise localization of faults. Comparative analysis against traditional relays and AI-based methods (CNNs, DTs, and SVMs) reveals superior fault coverage, adaptability to DER variability, and elimination of preprocessing delays. By mitigating false tripping and DER-induced impedance errors, this ANN-based approach significantly enhances microgrid reliability, offering a robust solution for evolving power systems.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100710"},"PeriodicalIF":4.2,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Promoting photovoltaic energy: a generation model for a capacity-constrained grid","authors":"Daniel Lugo Laguna,&nbsp;Ángel Arcos Vargas,&nbsp;Fernando Núñez Hernández","doi":"10.1016/j.ref.2025.100708","DOIUrl":"10.1016/j.ref.2025.100708","url":null,"abstract":"<div><div>This study optimizes the Inverter Loading Ratio (ILR) in large-scale photovoltaic (PV) installations to maximize investment profitability and mitigate grid saturation in capacity-constrained power grids. Different ILR values have been simulated for a PV installation located in Spain, using high resolution (1-minute) energy production data. Results indicate that an ILR of 1.43 optimizes financial returns on investment, achieving an Internal Rate of Return of 9.85 % and a Net Present Value-to-Investment Ratio of 25.5 %. Our sensitivity analyses show that the optimal ILR increases slightly with increasing energy prices (PPA) and significantly with decreasing PV module costs. Furthermore, our ILR optimization process, by increasing energy output without requiring additional grid connections, offers a valuable solution in regions with limited network capacity. Our findings highlight the economic and operational benefits of PV array oversizing.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100708"},"PeriodicalIF":4.2,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distributed optimization for microgrids control and management with virtual voltage source segregation","authors":"Asad Khan,&nbsp;Muhammad Mansoor Khan,&nbsp;Jiang Chuanwen","doi":"10.1016/j.ref.2025.100709","DOIUrl":"10.1016/j.ref.2025.100709","url":null,"abstract":"<div><div>This paper proposes a distributed optimization framework for islanded microgrids (MGs) control/optimization that achieves a global optimal solution with reduced computational and communication complexity. The proposed method breaks down the global optimization problem into simple sub–optimal problems by dividing the whole network into sub–networks. This is accomplished through virtual segregation of distributed generation (DG) voltage sources. In contrast to the existing distributed schemes, where each agent solves a full–scale optimization problem, taking into account information from the entire network and requires parameter consensus, the proposed approach solves individual sub–optimal problems independently. This substantially reduces the computational complexity and communication requirements at higher speed to promptly exchange information diffusion among the agents. Moreover, this study considers a multi–feeder MG comprised of numerous load feeders and sparsely available DGs, a MG system that has received limited attention in existing literature. The proposed distributed method has been tested for power sharing and load feeder voltage restoration in a radial–type multi–feeder islanded MG network; however, it holds potential for broader applications. A comprehensive analytical formulation, MATLAB numerical simulations, and realistic experimental findings for the proposed distributed method provide a detailed understanding of its capabilities and shortcomings.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100709"},"PeriodicalIF":4.2,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143824185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Techno-economic analysis of integrated PV/Biogas/Wind/Hydrogen polygeneration energy systems for green transportation in Bangladesh context","authors":"Shemanto Saha ,&nbsp;Abu Kowsar ,&nbsp;Sumon Chandra Debnath ,&nbsp;Kawsar Ahmed ,&nbsp;Firoz Alam","doi":"10.1016/j.ref.2025.100707","DOIUrl":"10.1016/j.ref.2025.100707","url":null,"abstract":"<div><div>The global transportation system is currently experiencing a notable shift towards the prominence of fully electric, hybrid, and hydrogen-fuelled vehicles to reduce the environmental consequences of fossil fuels. Developing countries, including Bangladesh, promote renewable energy-based power generation to foster the uptake of green transportation solutions. However, the implementation of such a solution poses significant economic, technical, and affordability challenges. This study explores the techno-economic viability of four potential options (Models): photovoltaic (PV), biogas, wind, and hydrogen energy within a net-metering scheme, an area not previously well explored for developing countries. The study findings reveal that Model 1 (PV/biogas) featuring electric vehicles (EVs) bears a cost of US$ 0.0141/km and demonstrates higher economic viability than the other three models. From an environmental standpoint, Model 3 (PV/biogas-powered hydrogen refuelling stations—HRFS) emerges as the optimal choice, characterised by a CO₂ emission of 1.83 g/km and the levelized cost of hydrogen (LCOH) and hydrogen production (LCOH_P) values of US$ 13.4 and US$ 8.93, respectively. A sensitivity analysis of the PEM electrolyser price and gasification ratio estimates the LCOHp at US$ 8.63 to US$ 9.90. Environmental evaluations show that Models 3 and 4 can reduce CO₂ emissions from diesel, petrol, and CNG in Bangladesh’s transportation sector by approximately 99.5%. The study further reveals that EVs are deemed more economical than hydrogen fuel cell vehicles for green transportation for developing nations under the current cost structure.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100707"},"PeriodicalIF":4.2,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microgrids for energy access in remote and islanded communities under natural disasters – Context of Lombok Island Indonesia","authors":"Majid Ali ,&nbsp;Yajuan Guan ,&nbsp;Juan C. Vasquez ,&nbsp;Josep M. Guerrero ,&nbsp;Fransisco Danang Wijaya ,&nbsp;Adam Priyo Perdana","doi":"10.1016/j.ref.2025.100705","DOIUrl":"10.1016/j.ref.2025.100705","url":null,"abstract":"<div><div>Natural disasters (NDs) including earthquakes, floods, tsunamis, and other high-impact natural phenomena cause significant power outages that interrupt human activity and industrial output. Natural disaster mitigation in the energy sector requires sophisticated control strategies, operations, and vulnerabilities. In literature, different Microgrids (MGs) configurations are adapted in such scenarios which can endure low-probability and high-impact (LPHI) occurrences because of their compact size, manageable loads, and constrained bounds. Ad hoc MGs that are low-power, transportable, and containerized can be used in emergencies by supplying electricity for critical loads. This paper includes an overview of the history of power system resilience, resilience-enhancing techniques, and MGs as a resilience resource. This paper presents a case study of the resiliency issue of the remote MG of Lombok Island in Indonesia and then proposes potential technical solutions to cope with natural disasters. Finally, concludes by identifying gaps in the current research literature and suggesting future avenues for enhancing the methods focused on resilience-oriented operations to strengthen the resilience of MGs.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100705"},"PeriodicalIF":4.2,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}