Cleaner Energy Systems最新文献

{"title":"Optimizing energy expenditure in agricultural autonomous ground vehicles through a GPU-accelerated particle swarm optimization-artificial neural network framework","authors":"Ambuj,&nbsp;Rajendra Machavaram","doi":"10.1016/j.cles.2024.100130","DOIUrl":"10.1016/j.cles.2024.100130","url":null,"abstract":"<div><p>The accurate energy consumption prediction in Agricultural Ground Vehicles (AGVs) holds immense potential for optimizing operational efficiency and minimizing environmental impact. However, existing optimization methods for such prediction tasks often suffer from high computational demands, hindering their practical implementation. This paper introduces a ground-breaking approach that overcomes this limitation by leveraging the potent computational power of Graphics Processing Units (GPUs) to accelerate the optimization process dramatically. We propose a novel adaptation of the Particle Swarm Optimization (PSO) algorithm, specifically tailored to the intricate multi-objective challenges of AGV energy prediction. This framework harnesses the strengths of a multi-objective approach, enabling the simultaneous optimization of prediction accuracy and model complexity. To further enhance efficiency, we seamlessly integrate GPU parallelization techniques, significantly expediting both the optimization process and the training of Artificial Neural Networks (ANNs) employed for prediction. Preliminary results demonstrate a remarkable improvement in the accuracy of AGV energy consumption predictions, directly attributed to the synergistic effect of optimizing the ANN architecture and parameters through our proposed PSO framework. This tailored PSO adaptation distinguishes itself by its ability to tackle the complex multi-objective nature of AGV energy prediction with enhanced efficiency and precision. It thus emerges as a compelling and novel solution within the realm of Machine Learning and heuristic methods for agricultural robotics, paving the way for sustainable and optimal AGV operations.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100130"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000244/pdfft?md5=95d29beea2a66736f8e26b5d92c843c0&pid=1-s2.0-S2772783124000244-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141852367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing Wind Energy Conversion Efficiency: A Novel MPPT Approach Using P&O with ADRC Controllers versus PI Controllers with Kp and Ki Optimization via Genetic Algorithm and Ant Colony Optimization","authors":"Najoua Mrabet ,&nbsp;Chirine Benzazah ,&nbsp;Chakib Mohssine ,&nbsp;El akkary Ahmed ,&nbsp;Khouili Driss ,&nbsp;Rerhrhaye Badr ,&nbsp;Lahlouh Ilyas","doi":"10.1016/j.cles.2024.100159","DOIUrl":"10.1016/j.cles.2024.100159","url":null,"abstract":"<div><div>This manuscript introduces an innovative Maximum Power Point Tracking (MPPT) strategy to improve the efficiency of Wind Energy Conversion Systems (WECS) equipped with Permanent Magnet Synchronous Generators (PMSG) under variable wind conditions. The proposed approach integrates Active Disturbance Rejection Control (ADRC) with the Perturb and Observe (P&amp;O) algorithm, effectively addressing challenges such as external disturbances and fluctuating wind environments. By combining ADRC with P&amp;O control, the system achieves enhanced tracking performance and adaptability.To validate the added value of this approach, we compare it with a traditional P&amp;O strategy combined with Proportional Integral (PI) control. For the PI-based method, controller parameters Kp and Ki are optimized using Genetic Algorithm (GA) and Ant Colony Optimization (ACO) to enhance control precision. The Integrated Time Absolute Error (ITAE) objective function is employed to fine-tune these parameters, further optimizing system performance. Our analysis underscores the superiority of ADRC in disturbance rejection and quick adaptability over the PI approach.The proposed strategy is tested under two distinct wind speed profiles—constant and fluctuating—through time-domain simulations in MATLAB/Simulink. Simulation results confirm the superior performance of the ADRC-P&amp;O method, highlighting its effectiveness in maximizing power extraction from wind energy and proving its potential for real-world applications. This study offers a significant advancement in wind energy technology by providing a robust and efficient solution for MPPT in WECS.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100159"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing textile dyeing and finishing for improved energy efficiency and sustainability in fleece knitted fabrics","authors":"Miraduzzaman Chowdhury ,&nbsp;Mohammad Shohag Babu ,&nbsp;Shahadat Hossain ,&nbsp;Rony Mia ,&nbsp;Shekh Md. Mamun Kabir","doi":"10.1016/j.cles.2024.100154","DOIUrl":"10.1016/j.cles.2024.100154","url":null,"abstract":"<div><div>In the industrial range, optimizing dyeing and finishing energy is important to control environmental pollution. In the Dyeing stage to finishing of textiles gas, electricity, steam, and water are used 260 m³/hour, 591 kWh, 1.2 pounds/hour, and 8.69 tons/hour respectively. If textile professionals do not match the desired shade and quality of fabrics with the use of minimal resources the energy cost will be multiple times higher. This study investigates the change in the shade of fleece knitted fabrics from the dyeing unload to the finish stage and assumes a dyeing recipe adjustment, focusing on the impact of optimized dyeing and finishing processes. Also, it focuses on qualitative changes in properties across various color variations. Identical dyeing recipes for light, medium, and dark shades of red, blue, and navy. Properties such as GSM (grams per square meter), width, color strength, shade (darker/lighter, red/green, blue/yellow), shrinkage, spirality, pilling, bursting strength, and color fastness were analyzed. Dyeing to post-finishing, an increase in color strength (K/S) values was observed, with examples including minimum increases from 2.9 to 3.18 for light red and maximum from 19.3 to 22.9 for dark navy shade. Darker shades (DL*) were observed after stenter 1st pass (among all variants, red: 1.2 % to 8.1 %, blue: 4.5 % to 6.7 %, navy: 1.6 % to 2 %), while lighter shades (DL*) were observed following sueding and napping (among all variants, red: 3.1 % to 19.7 %, blue: 11.8 % to 19.7 %, navy: 14.8 % to 27.6 %). Greenish (Da*) and yellowish (Db*) tones are prominent across all colors in the finishing stages. Besides, other properties shrinkage, spirality, pilling, bursting strength, and color fastness significantly changed. These findings offer valuable guidance for dyeing professionals aiming to achieve the desired adjustment of shades that match the quality standard and produce sustainable fleece fabrics. To compensate for the shade lightening that occurs during the finishing process, it is recommended to keep the fabric shade slightly darker (5.70 % to 23.10 %) at the dyeing stage.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100154"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating energy retrofit strategies in enhancing operational performance of mosques: A case study of Al-Imam Al-Hussein Mosque","authors":"Mohamed Marzouk ,&nbsp;Maryam El-Maraghy ,&nbsp;Ahmed El-Shihy ,&nbsp;Mahmoud Metawie","doi":"10.1016/j.cles.2024.100144","DOIUrl":"10.1016/j.cles.2024.100144","url":null,"abstract":"<div><p>Mosques are unique in terms of architectural design and operational efficiency. Architectural Design, building envelope characteristics, intermittent operating schedules, and occupancy patterns all impact the performance. Managing these factors poses challenges regarding reducing energy consumption and simultaneously achieving the occupants' thermal and visual comfort, especially in hot, arid climatic conditions. Also, the potential benefits of daylighting in reducing energy consumption in mosque buildings need to be addressed. Accordingly, this study evaluates the impact of various retrofit strategies on the operational performance of Al-Imam Al-Hussein Mosque, one of the large historic mosques in Cairo, considering the energy performance, thermal comfort, and daylighting performance. The current performance of the mosque has been analyzed using energy simulation software to determine the areas that affect its performance. Hence, five retrofitting strategies have been studied to assess their impact on improving the performance of the mosque. When changes are applied to the building envelope only by changing the glazing type, the visual discomfort is improved while sufficient daylighting is maintained inside the prayer area. By adding a cooling system and applying changes to the building envelope, thermal comfort was improved, and the visual discomfort decreased. However, this has led to an increase in energy consumption. Combining different strategies (as in strategy 5) by changing the glazing type, changing the operation scheme, adding LED lamps with dimmers, and adding a cooling system has improved the defined performance metrics. It has achieved a 23% decrease in the annual energy consumption, decreasing the visual discomfort by 30% while maintaining sufficient daylighting conditions inside the space, and enhancing occupants’ thermal comfort by 65%. The proposed approach aids in evaluating the retrofit strategies of mosque buildings, considering different criteria, including daylighting performance, to be energy efficient, sustainable, and maintain occupants’ visual and thermal comfort.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100144"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000384/pdfft?md5=030940ab161a1ecd141aa1a703385593&pid=1-s2.0-S2772783124000384-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142150796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of trapezoidal ribs on the performance of solar air collector: A numerical solution with optimized rib dimensions for better performance","authors":"Mosuru Hari Krishna ,&nbsp;Shekher Sheelam ,&nbsp;Chandramohan V․P․","doi":"10.1016/j.cles.2024.100147","DOIUrl":"10.1016/j.cles.2024.100147","url":null,"abstract":"<div><p>In the present study, a 2D numerical analysis of the solar air collector (SAC) of an indirect solar dryer having trapezoidal corrugations on the absorber plate was performed. Corrugation pitch, <em>p</em> (twelve values ranged from 20 to 160 mm) and height, <em>e</em> (six values ranged from 1 to 10 mm) were varied and analyzed for six values of Reynolds numbers (<em>Re</em>). The output characteristics such as Nusselt number (<em>Nu</em>), friction factor (<em>f</em>) and thermo-hydraulic performance index (<em>T_hp</em>) were calculated for different <em>p, e</em> and <em>Re</em>. The total work was categorized into two parts (part-I for optimizing <em>p</em> and part-II for optimizing <em>e</em>). 18 domains (twelve for part-I and six for part-II simulations) were generated and 108 simulations were executed to find the optimum dimensions (<em>p, e</em> and corrugation angle, <em>α</em>) of the corrugation. ANSYS Fluent-v15 was used to solve the problem. The maximum <em>Nu</em> for the corrugated sheet was 2.663 times greater than the flat absorber plate. The maximum <em>T_hp</em> range was from 1.435 to 1.699 and obtained at the optimal values of <em>p</em> = 140 mm, <em>e</em> = 4 mm and <em>α</em> = 38.66° The numerical results were compared with the existing literature.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100147"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000414/pdfft?md5=d8114a55d794a758b0c3ac4ac4b1f596&pid=1-s2.0-S2772783124000414-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142242683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated rooftop solar PV-based residential advanced energy management system: An economic involvement of energy systems for prosumers","authors":"Abu Shufian ,&nbsp;Shaikh Anowarul Fattah","doi":"10.1016/j.cles.2024.100150","DOIUrl":"10.1016/j.cles.2024.100150","url":null,"abstract":"<div><div>The growing adoption of rooftop solar photovoltaic (PV) systems, coupled with the ability to sell surplus energy back to the national grid, presents a promising opportunity for residential energy management. This research introduces an innovative Advanced Energy Management System (AEMS) that integrates rooftop solar PV with energy-efficient appliances, offering a transformative approach to optimizing household energy consumption. By leveraging advanced demand-side management (DSM) techniques, the AEMS enables users to strategically shift energy usage away from peak hours, thereby reducing reliance on grid energy and minimizing costs. Empirical evaluations reveal that the AEMS significantly outperforms conventional energy management systems, achieving cost reductions of 28.59–35.48 %. The user-friendly interface and robust optimization strategies of the proposed model ensure operational efficiency, making it a valuable tool for maximizing energy savings and enhancing grid stability. Focusing on the specific context of Bangladesh, this study provides a comprehensive techno-economic analysis, demonstrating the practical applicability and long-term sustainability of suggested AEMS. The findings underscore the potential of the proposed model to revolutionize residential energy management, positioning it as a key enabler of both economic and environmental benefits for prosumers in emerging markets.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100150"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wind power forecasting with metaheuristic-based feature selection and neural networks","authors":"Mohd Herwan Sulaiman ,&nbsp;Zuriani Mustaffa ,&nbsp;Mohd Mawardi Saari ,&nbsp;Mohammad Fadhil Abas","doi":"10.1016/j.cles.2024.100149","DOIUrl":"10.1016/j.cles.2024.100149","url":null,"abstract":"<div><div>Accurate forecasting of wind power generation is crucial for ensuring a stable and efficient energy supply, reducing the environmental impact of energy production, and promoting a cleaner and more sustainable energy supply. Inaccurate forecasts can lead to a mismatch between wind power generation and energy demand, resulting in wasted energy, increased emissions, and reduced grid stability. Therefore, improving the accuracy of wind power generation forecasting is essential for optimizing energy storage and grid management, reducing the reliance on fossil fuels, decreasing greenhouse gas emissions, and promoting a more sustainable energy future. This study proposes an innovative approach to enhance wind power generation forecasting accuracy by leveraging the strengths of metaheuristic algorithms for feature selection and integrating them with Neural Networks (NN). Specifically, five distinct algorithms - Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Teaching-Learning-Based Optimization (TLBO), and Evolutionary Mating Algorithm (EMA) - are integrated with NN model to identify optimal feature subsets from a comprehensive dataset of 18 diverse features. The results show that the GA consistently outperforms other algorithms in selecting the most influential features, leading to improved precision in wind power predictions. Notably, the GA achieves the best root mean square error (RMSE) of 37.1837 and the best mean absolute error (MAE) of 18.6313, outperforming the other algorithms and demonstrating the importance of feature selection in improving the accuracy of wind power forecasting. This innovative framework advances the field of renewable energy forecasting and provides valuable insights into optimizing feature sets for improved predictions across diverse domains.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100149"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of prediction errors on CO2 emissions in residential smart energy management systems with hybrid thermal-electric storage","authors":"Aleksandr Zaitcev ,&nbsp;Alexander Alexandrovich Shukhobodskiy ,&nbsp;Tatiana Pogarskaia ,&nbsp;Giuseppe Colantuono","doi":"10.1016/j.cles.2024.100138","DOIUrl":"10.1016/j.cles.2024.100138","url":null,"abstract":"<div><p>Modern residential smart energy management systems allow for more efficient use of renewable energy through the application of various data-driven control strategies. Such strategies typically rely on predicting renewable power generation, domestic power demand, energy price and grid CO2 index. While the generation of such forecasts is well-researched, the impact of the associated prediction errors remains understudied.</p><p>This manuscript presents a generalised study of the effect of forecast errors on smart energy system performance. Results are obtained using multiple control optimisation techniques and real life data from residential dwellings spanning over multiple seasons.</p><p>Our analysis reveals that ideal forecasts can achieve up to 71.3% CO2 emissions savings compared to a baseline house without a smart energy system. The most significant performance decrease was caused by time lags in all three forecasts (grid CO2 index, solar power generation, and power demand). Among these, the CO2 index forecast was the most sensitive to errors, with an average performance deterioration of approximately 5% per 30 min of time lag. In contrast, errors in solar power generation and power demand forecasts had less impact, causing performance decreases of 18% and 21%, respectively, for extreme changes in forecast profile scale. This research identifies critical points in smart energy system design and offers insights to prioritise improvements in forecast models.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100138"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000323/pdfft?md5=10dd73766e68ab2d46b17caff6449113&pid=1-s2.0-S2772783124000323-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142168316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prospects and challenges of anode materials for lithium-ion batteries–A review","authors":"Md․ Helal Hossain ,&nbsp;Md․ Aminul Islam ,&nbsp;Mohammad Assaduzzaman Chowdhury ,&nbsp;Nayem Hossain","doi":"10.1016/j.cles.2024.100145","DOIUrl":"10.1016/j.cles.2024.100145","url":null,"abstract":"<div><p>This review provides a comprehensive examination of the current state and future prospects of anode materials for lithium-ion batteries (LIBs), which are critical for the ongoing advancement of energy storage technologies. The paper discusses the fundamental principles governing the operation of LIBs, with a focus on the electrochemical performance of various anode materials, including graphite, silicon, tin, and transition metal oxides. Each material's theoretical capacity, cycle life, and structural stability are analyzed, highlighting the intrinsic challenges such as volumetric expansion, formation of the solid-electrolyte interphase (SEI), and degradation mechanisms that limit their practical application. The review also explores novel materials and composite approaches aimed at overcoming these limitations, such as the incorporation of nanostructured materials, doping strategies, and the development of hybrid anode systems. The integration of advanced characterization techniques and computational modeling is emphasized as crucial for understanding the complex interactions at the nanoscale and for guiding the design of next-generation anodes with enhanced performance metrics. Despite significant progress, the paper identifies several key challenges that remain, including the need for improved safety, higher energy density, and cost-effective manufacturing processes. The discussion extends to emerging trends and potential future directions in the field, such as the exploration of non-lithium-based systems and the development of solid-state batteries. The review concludes by addressing the critical need for continued interdisciplinary research efforts to drive innovation and achieve the commercialization of high-performance anode materials for LIBs.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100145"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000396/pdfft?md5=988ecc960043e3d50df89152fab4ab43&pid=1-s2.0-S2772783124000396-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142242624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating alternative technologies to diesel generation in India using multi-criteria decision analysis","authors":"Ajit Singh ,&nbsp;Amruta Joshi ,&nbsp;Francis D. Pope ,&nbsp;Bhim Singh ,&nbsp;Mukesh Khare ,&nbsp;Sri Harsha Kota ,&nbsp;Jonathan Radcliffe","doi":"10.1016/j.cles.2024.100133","DOIUrl":"10.1016/j.cles.2024.100133","url":null,"abstract":"<div><p>Diesel generators (DGs) are widely used in India by business and domestic consumers to provide resilience against unreliable power supplies, but have serious adverse environmental and health impacts. Low carbon alternatives to DGs are becoming more widely available and affordable, though technical and non-technical barriers remain to their widespread adoption. Targeted policy and financial interventions would help accelerate the deployment of these alternatives, where such interventions should be based on local needs. To this end, we use a Multi-Criteria Decision Analysis (MCDA) approach to identify appropriate technology alternatives for DGs in residential, industrial and agricultural applications in India. Within this study, the MCDA framework facilitates evidence-based decision-making through structured discussions with local stakeholders and for evaluating the most suitable option from a variety of available alternatives. Overall, our analysis concluded that a hybrid system combining solar PV and battery storage system are considered most suitable for residential, agricultural as well as industrial applications. This study sets out a pragmatic approach for decision makers considering how to minimise the adverse impacts of DGs while recognising the intricacies of requirements of different applications at a local level. Additionally, our approach showcases how co-creation of potential solutions, and ‘transparency’ in the process, can be accomplished in policy-making, which is critical for wider acceptance of interventions.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100133"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S277278312400027X/pdfft?md5=99f45ff1a2e4fb1e7400774ff899a579&pid=1-s2.0-S277278312400027X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141998656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}