Cleaner Energy Systems最新文献

{"title":"Techno-economic analysis of green hydrogen production and electric vehicle charging using redundant energy on a solar photovoltaic mini-grid","authors":"Gidphil Mensah ,&nbsp;Richard Opoku ,&nbsp;Francis Davis ,&nbsp;George Yaw Obeng","doi":"10.1016/j.cles.2024.100165","DOIUrl":"10.1016/j.cles.2024.100165","url":null,"abstract":"<div><div>The trajectory of the world's energy use has moved towards the use of renewable energy to increase energy access. Solar energy's pace of growth as a result of its low cost has resulted in it being used to generate electricity for areas that do not have access to grid electricity. Thus, solar photovoltaic mini-grid systems have been deployed in several areas. Over time, it has been found that these systems generate a significant amount of redundant energy, which translates to low profitability for the mini-grid operators, as only a fraction of the system's capacity is used. This study seeks to investigate the economic feasibility of using this redundant energy for green hydrogen production and electric vehicle charging. The results revealed that both the green hydrogen production and electric vehicle charging are economically viable. Net Present Value, Internal Rate of Return and Simple Payback Period obtained for green hydrogen production are $20,000, 24.6 %, 9 years, while those of the electric vehicle charging are $109,625, 28.41 %, 4 years respectively. Over the projects’ lifetime, levelised cost of hydrogen and levelised cost of energy for charging are $6.88/kg and $0.23/kWh respectively. Furthermore, a sensitivity analysis revealed that the levelised costs for both projects are most sensitive to the plant capacity factor and capital expenditure. The study also shows that the wasted energy of the PV mini-grid could be reduced from as high as 69.95 % to nearly 0 %. This research underscores the potential of other clean energy technologies to reduce the wasted energy on existing PV systems, whiles improving the economic state of mini-grid communities.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100165"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143103040","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":"Joint Design and Pricing Problem for Symbiotic Bioethanol Supply Chain Network: Model and Resolution Approach","authors":"Houssem Bouazizi ,&nbsp;Maha Benali ,&nbsp;Jean-Marc Frayret ,&nbsp;Rim Larbi","doi":"10.1016/j.cles.2024.100163","DOIUrl":"10.1016/j.cles.2024.100163","url":null,"abstract":"<div><div>To fight climate change, the Province of Quebec, Canada, has set targets to reduce greenhouse gas emissions by reducing fossil fuel consumption and integrating biofuel content into gasoline and diesel fuel. Motivated by a real-world case study, this paper presents a novel distributed decision model for designing a symbiotic supply chain network and supporting pricing decisions. A distributed decision-making problem is formulated as a game theoretic approach considering a Stackelberg–Nash equilibrium. A novel mathematical model is proposed to support the decisions of four actors: corn farms, processing depots, pig farms, and biorefineries. In addition to the configuration of a biofuel-based industrial symbiosis, the model offers the possibility of setting purchase prices and supply levels for biomass (corn stover supplied by farms), as well as determining sales prices and production levels for the main product (the cellulosic sugar used for the bioethanol production) and a coproduct (pig feed sold to pig farmers). A three-step optimization process involving the user is proposed to address the computational challenges posed by large design problem instances. The case study of the Province of Quebec is used to evaluate the performance of the proposed resolution approach.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100163"},"PeriodicalIF":0.0,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142721549","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":"Economic and environmental impact assessment of renewable energy integration: A review and future research directions","authors":"Md Tasbirul Islam ,&nbsp;Sikandar Abdul Qadir ,&nbsp;Amjad Ali ,&nbsp;Muhammad Waseem Khan","doi":"10.1016/j.cles.2024.100162","DOIUrl":"10.1016/j.cles.2024.100162","url":null,"abstract":"<div><div>This review article critically examines papers on renewable energy integration (REI), with a specific focus on the economic and environmental impact assessments across multiple sectors, including agriculture, transportation, electricity production, buildings, and biofuel production. A total of 111 articles from the Web of Science Core Collection database were reviewed using a systematic literature review methodology and content analysis techniques. The results indicate that evaluation-type studies, particularly those employing optimization and simulation-based methods, such as techno-economic analysis (TEA) (28 papers) and life cycle assessment (LCA) (20 papers), were the most prominent approaches used for economic and environmental analyses. Optimization techniques such as mixed-integer linear programming (6 papers), genetic algorithms (GA) (5 papers), and particle swarm optimization (PSO) (4 papers) were widely applied. The quantitative analysis of impact assessment indicators shows that REI has yielded significant long-term positive results across multiple RE sources, sectors, and regions. A detailed examination of mathematical models (e.g., optimization techniques) and simulation modeling combined with LCA will assist future researchers in optimizing energy systems and enhancing sustainability in sectors such as agriculture and water desalination. The conceptual inclusion of circular economy within the research field needs to be more present among researchers, and most of the studies focused on technical aspects of RE integration and assessing impacts rather than identifying a systemic change across the sectors. Several future research directions have been identified across sectors, offering opportunities to advance the field. Policymakers will find this paper valuable for informed decision-making and the development of robust policy frameworks.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100162"},"PeriodicalIF":0.0,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142707013","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":"Simulation of a system to simultaneously recover CO2 and sweet carbon-neutral natural gas from wet natural gas: A delve into process inputs and units performances","authors":"Abdulhalim Musa Abubakar ,&nbsp;Lukman Buba Umdagas ,&nbsp;Moses NyoTonglo Arowo ,&nbsp;Marwea Al-Hedrewy ,&nbsp;Mahlon Kida Marvin ,&nbsp;Noureddine Elboughdiri ,&nbsp;Aminullah Zakariyya Abdul ,&nbsp;Jenisus O. Dejarlo ,&nbsp;Rezkallah Chafika","doi":"10.1016/j.cles.2024.100156","DOIUrl":"10.1016/j.cles.2024.100156","url":null,"abstract":"<div><div>The growing need for carbon-neutral energy solutions necessitates the development of efficient systems for carbon dioxide (CO₂) recovery and the production of sweet carbon-neutral natural gas (CNNG) from wet natural gas. Despite existing approaches, limitations in process optimization, solvent efficiency, and output purity persist. This study aims to address these gaps by simulating a system for simultaneous recovery of CO₂ and CNNG using an integrated three-stage process, modeled in Aspen Plus V8.8. The unique aspect of this work lies in employing the ENRTL-RK base model, coupled with sensitivity analyses to optimize input parameters across 13 interconnected process units, including compressors, heat exchangers, and extraction columns. Key innovations include the novel configuration of units, yielding a recovery efficiency of 95.94% for CNNG and a CO₂ purity of 93.185% at optimal conditions, surpassing conventional methods. The performance of the monoethanolamine (MEA) solvent was enhanced by careful adjustment of input parameters, improving its absorption efficiency by 12% compared to standard operational settings. Sensitivity analysis revealed critical parameters such as feed pressure and solvent flow rate as primary drivers for maximizing output efficiency. This study also provides a detailed quantitative assessment of power requirements, with a compressor brake horsepower (BHP) of 18,2605 watts at 110 bar discharge pressure. It addresses the existing research gap by introducing a systematic approach to process optimization, significantly improving the purity and recovery of CNNG and CO₂ while minimizing energy consumption. The results not only demonstrate the viability of this process but also provide a foundation for further refinement in sustainable gas processing technologies.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100156"},"PeriodicalIF":0.0,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142664330","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 a hybrid wind-solar-biomass system with battery and hydrogen storage using generic algorithm-particle swarm optimization for performance assessment","authors":"Shree Om Bade,&nbsp;Olusegun Stanley Tomomewo","doi":"10.1016/j.cles.2024.100157","DOIUrl":"10.1016/j.cles.2024.100157","url":null,"abstract":"<div><div>This paper investigates the optimal design of a hybrid renewable energy system, integrating wind turbines, solar photovoltaic systems, biomass, and battery and hydrogen storage to ensure a reliable energy supply at the lowest annual cost for a residential load in Kern County, USA. The hybrid generic algorithm particle swarm optimization (GAPSO) algorithm was adopted to determine the optimal configuration of parameters and cost-effectiveness, considering technical, economic, environmental, and social performance indicators. The generic algorithm (GA) and particle swarm optimization (PSO) validate the effectiveness of the proposed technique, showcasing its efficiency in system optimization. The findings indicate that GAPSO outperforms GA and PSO due to its rapid convergence, lowest final fitness value, and stable optimization process. The hybrid GAPSO's performance, combined with the different capacities of wind turbines (4,561 kW), solar PV (8,480 kW), biomass (2,261 kW), battery banks (8,000 kWh), and fuel cells (2,392 kW), resulted in an annual cost of $6,239,193; energy cost and net present value of $0.48/kWh and $101,333,937. The system maintained a supply loss of 0.8 %, achieved an availability index of 99.2 %, a renewable energy fraction of 88.87 %, GHGs emission of 953,615 kg, land use of 3,842,875 m², and water consumption 528,678 L respectively. GAPSO achieved a 2.17 % and 0.01 % improvement in cost-effectiveness and 11.11 % increase in reliability compared to GA and PSO.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100157"},"PeriodicalIF":0.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573530","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":"Design and implementation of a control system for multifunctional applications of a Battery Energy Storage System (BESS) in a power system network","authors":"Chukwuemeka Emmanuel Okafor,&nbsp;Komla Agbenyo Folly","doi":"10.1016/j.cles.2024.100153","DOIUrl":"10.1016/j.cles.2024.100153","url":null,"abstract":"<div><div>This work proposes a design and implementation of a control system for the multifunctional applications of a Battery Energy Storage System in an electric network. Simulation results revealed that through the suggested control approach, a frequency support of 50.24 Hz for the 53-bus system during a load decrease contingency of 350MW was achieved. Without the control system, the frequency was 50 .38Hz. Such a high frequency if not addressed, may result in a loss of synchronization among interconnected synchronous machines which could result in a decrease in voltage stability of the studied network. Besides, a reduction of about 2.05 MW in the active power losses was accomplished and a reactive power support of 3.63Mvar was realised. Thus, through the proposed strategy, Battery energy storage system has been enabled for frequency regulation, power loss minimization and voltage deviation mitigation resulting in an overall enhancement of the power quality of the electric power delivered in the studied networks.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100153"},"PeriodicalIF":0.0,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553028","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":"Techno economic study of floating solar photovoltaic project in Indonesia using RETscreen","authors":"Muhammad Rifansyah,&nbsp;Dzikri Firmansyah Hakam","doi":"10.1016/j.cles.2024.100155","DOIUrl":"10.1016/j.cles.2024.100155","url":null,"abstract":"<div><div>The utilization of solar energy is crucial for the advancement of sustainable power generation on a worldwide scale, driven by environmental concerns and the depletion of fossil fuels. Indonesia's goal is to achieve carbon neutrality by 2060 and it is aggressively advocating for solar energy, which includes the implementation of new methods such as floating photovoltaic (PV) systems. This study evaluates the Techno-Economic Feasibility of Indonesia's Cirata 145 MW floating solar PV project by employing RETScreen technology. The objective is to improve the long-term financial stability, decrease greenhouse gas emissions, and suggest viable choices for improvement. Examining three scenarios that involve alterations in carbon emissions, energy pricing, and loan interest rates demonstrates different levels of project feasibility. The introduction of carbon tax emission pricing has a substantial impact on the feasibility of projects. This study provides useful insights into doing techno-economic feasibility assessments using RETScreen for floating photovoltaic (PV) systems. It demonstrates how modifying parameters can effectively mitigate project risks.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100155"},"PeriodicalIF":0.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553029","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":"2024-10-10","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":"Exploring the substitution within clean energy: Evidence from China's top 14 hydropower provinces","authors":"Yubao Wang,&nbsp;Huiyuan Pan,&nbsp;Junjie Zhen,&nbsp;Boyang Xu","doi":"10.1016/j.cles.2024.100152","DOIUrl":"10.1016/j.cles.2024.100152","url":null,"abstract":"<div><div>This paper quantitatively examines the substitution effects within China's clean energy sector, focusing on the hydropower and new energy generation sectors across the top 14 hydropower-producing provinces, which collectively contribute to over 80 % of the country's total hydropower output. To provide a comprehensive analysis of regions that significantly influence national trends, the study utilizes the Cross-Price Elasticity (CPE) and Morishima Elasticity of Substitution (MES). CPE measures how the quantity demanded of one energy source responds to a change in the price of another, while MES assesses the sensitivity of the ratio between two energy inputs to price changes. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model is employed to forecast energy substitution dynamics, offering robust predictive accuracy. The average MES between clean energy and thermal power is 0.663, indicating a moderate substitution relationship, with the effect more pronounced in summer. Additionally, the mean MES between hydropower and new energy generation is 2.067, reflecting a strong substitution effect between these two clean energy forms. Furthermore, the SARIMA model shows a mean squared error (MSE) as low as 0.0006 in some cases, demonstrating its robust predictive accuracy in forecasting energy substitution dynamics. These results offer empirical support for policies aimed at reducing reliance on thermal power and promoting clean energy development in key provinces.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100152"},"PeriodicalIF":0.0,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419860","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":"Battery remaining useful life estimation based on particle swarm optimization-neural network","authors":"Zuriani Mustaffa ,&nbsp;Mohd Herwan Sulaiman","doi":"10.1016/j.cles.2024.100151","DOIUrl":"10.1016/j.cles.2024.100151","url":null,"abstract":"<div><div>Determining the Remaining Useful Life (RUL) of a battery is essential for several purposes, including proactive maintenance planning, optimizing resource allocation, preventing unforeseen failures, improving safety, extending battery lifespan, and achieving accurate cost savings. Concerning that matter, this study proposed hybrid Particle Swarm Optimization–Neural Network (PSO<img>NN) for estimating battery RUL. In the evaluation of the proposed method, the effectiveness is assessed using the metrics of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The dataset employed for this investigation comprises eight input parameters and one output variable, representing the battery RUL. In conducting an analysis, the performance of the PSO<img>NN model is compared with hybrid NN with Cultural Algorithm (CA-NN) and Harmony Search Algorithm (HSA-NN), as well as the standalone Autoregressive Integrated Moving Average (ARIMA). Upon examination of the findings, it becomes evident that the PSO<img>NN model outperforms the alternatives with an MAE of 2.7708 and an RMSE of 4.3468, significantly lower than HSA-NN (MAE: 22.0583, RMSE: 34.5154), CA-NN (MAE: 9.1189, RMSE: 22.4646), and ARIMA (MAE: 494.6275, RMSE: 584.3098). The PSO<img>NN also achieves the lowest maximum error of 104.7381 compared to 490.3125 for HSA-NN, 827.0163 for CA-NN, and 1,160.0000 for ARIMA. Additionally, the low two-tail probability values (P(<em>T</em> ≤ <em>t</em>)), all below the significance level of 0.05, indicate that the differences between PSO<img>NN and the other methods (HSA-NN, CA-NN, and ARIMA) are statistically significant. These results highlight the superior accuracy and robustness of the PSO<img>NN model in predicting battery RUL. This study contributes to the field by presenting the PSO<img>NN as a highly effective tool for accurate battery RUL estimation, as evidenced by its superior performance over alternative methods.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100151"},"PeriodicalIF":0.0,"publicationDate":"2024-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419857","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}