Pub Date : 2024-12-01DOI: 10.1016/j.cles.2024.100158
Caifei Luo, Keyu Zhang
This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/policies/article-withdrawal).
< This article has been retracted at the request of the Authors.
Post-publication, the authors found that using these data, which are not based on officially published documents, as a foundation for scenario setting could lead to significant deviations in the final simulation results. Thus, the authors feel that the findings of the manuscript cannot be relied upon and that the article needs to be retracted.
The authors would like to apologize for any inconvenience caused to the readers.>
{"title":"Retraction notice to “Elasticity of substitution between clean energy and non-clean energy: Evidence from the Chinese electricity industry” [Cleaner Energy Systems 8 (2024) 100117]","authors":"Caifei Luo, Keyu Zhang","doi":"10.1016/j.cles.2024.100158","DOIUrl":"10.1016/j.cles.2024.100158","url":null,"abstract":"<div><div>This article has been retracted: please see Elsevier Policy on Article Withdrawal (<span><span>https://www.elsevier.com/about/policies/article-withdrawal</span><svg><path></path></svg></span>).</div><div>< This article has been retracted at the request of the Authors.</div><div>Post-publication, the authors found that using these data, which are not based on officially published documents, as a foundation for scenario setting could lead to significant deviations in the final simulation results. Thus, the authors feel that the findings of the manuscript cannot be relied upon and that the article needs to be retracted.</div><div>The authors would like to apologize for any inconvenience caused to the readers.></div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100158"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143103035","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}
Pub Date : 2024-12-01DOI: 10.1016/j.cles.2024.100160
Juliet Attah , Latifatu Mohammed , Andrew Nyamful , Paulina Donkor , Anita Asamoah , Mohammed Nafiu Zainudeen , John Adjah , Charles K. Klutse , Sylvester Attakorah Birikorang , Frederick Agyemang , Owiredu Gyampo
The urgent need to address climate change has prompted researchers to explore sustainable power generation methods using low or net-zero fuels and energy storage. Historically, gases derived from acetylene or LPG have been used for welding in factories. Despite its negative effects on the environment and human health, acetylene gas remains widely used. Examples of pollutants released from acetylene gas include carbon dioxide and carbon monoxide, both of which contribute to the greenhouse effect and global warming. There is a need for an alternative gas that is environmentally friendly, economically viable, and readily available. Hydrogen gas is currently used across various industries and is increasingly considered a potential primary fuel source for the future. In this study, a hydrogen fuel cell was used to produce HHO (brown) gas as a replacement for acetylene through electrolysis. The HHO gas was used to weld a randomly selected test piece, which was then evaluated alongside an acetylene-welded test piece. The integrity of both welds was assessed using dye-penetrant and radiographic testing, showing that welds from both gases were strong. Welding with HHO gas, followed by non-destructive inspection, also proved effective, with any defects attributed to inexperience in welding. The adoption of HHO gas in the welding industry is recommended due to its potential socio-economic benefits, health advantages, and environmental friendliness. Challenges related to initial investment costs may be mitigated as technology advances. Further research should focus on qualitative weld testing, economic and environmental impact assessments, and developing a business model for HHO systems.
{"title":"Oxy-hydrogen gas as a sustainable fuel for the welding industry: Alternative for oxy-acetylene gas","authors":"Juliet Attah , Latifatu Mohammed , Andrew Nyamful , Paulina Donkor , Anita Asamoah , Mohammed Nafiu Zainudeen , John Adjah , Charles K. Klutse , Sylvester Attakorah Birikorang , Frederick Agyemang , Owiredu Gyampo","doi":"10.1016/j.cles.2024.100160","DOIUrl":"10.1016/j.cles.2024.100160","url":null,"abstract":"<div><div>The urgent need to address climate change has prompted researchers to explore sustainable power generation methods using low or net-zero fuels and energy storage. Historically, gases derived from acetylene or LPG have been used for welding in factories. Despite its negative effects on the environment and human health, acetylene gas remains widely used. Examples of pollutants released from acetylene gas include carbon dioxide and carbon monoxide, both of which contribute to the greenhouse effect and global warming. There is a need for an alternative gas that is environmentally friendly, economically viable, and readily available. Hydrogen gas is currently used across various industries and is increasingly considered a potential primary fuel source for the future. In this study, a hydrogen fuel cell was used to produce HHO (brown) gas as a replacement for acetylene through electrolysis. The HHO gas was used to weld a randomly selected test piece, which was then evaluated alongside an acetylene-welded test piece. The integrity of both welds was assessed using dye-penetrant and radiographic testing, showing that welds from both gases were strong. Welding with HHO gas, followed by non-destructive inspection, also proved effective, with any defects attributed to inexperience in welding. The adoption of HHO gas in the welding industry is recommended due to its potential socio-economic benefits, health advantages, and environmental friendliness. Challenges related to initial investment costs may be mitigated as technology advances. Further research should focus on qualitative weld testing, economic and environmental impact assessments, and developing a business model for HHO systems.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100160"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142757001","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}
Pub Date : 2024-12-01DOI: 10.1016/j.cles.2024.100161
Erik López-Basto , Gijsbert Korevaar , Samantha Eleanor Tanzer , Andrea Ramírez Ramírez
<div><div>This paper evaluates the potential impacts of introducing low-carbon intensity hydrogen technologies in two oil refineries with different complexity levels, emphasizing the role of hydrogen production in reducing CO<sub>2</sub> emissions. The novelty of this work lies in three key aspects: Comprehensive system analysis of refinery complexity using real site data, integration of low-carbon Hydrogen technologies, long-term and short-term strategies. Two Colombian refineries serve as case studies, with technological solutions adapted to their complexity levels. The methodology involves evaluating different options for hydrogen production, accounting for improvement in technological efficiency over time.</div><div>The refinery systems were evaluated in a cost-optimization model built in Linny-r. Three different scenarios were considered, Business-As-Usual (BAU), high, and low-ambitions decarbonization scenarios, focusing on the time horizons of 2030 and 2050.</div><div>When comparing the two case studies, the preferred decarbonization strategy for both facilities involves the substitution of SMR technology with water electrolyzers powered by renewable electricity. Post-2030, biomass-based hydrogen technology is still a costly alternative; however, to achieve CO<sub>2</sub> neutrality, negative emissions storage of biogenic CO<sub>2</sub> emerges as an achievable alternative.</div><div>Our results indicate the achievability of CO<sub>2</sub> reduction objectives in both refineries. Our results show that achieving long-term CO<sub>2</sub> neutrality requires both refineries to increase renewable electricity production by 5 to 6 times for powering water electrolyzers, steam production by 2 to 2.5 times for CO<sub>2</sub> capture, and supply of dry biomass by 2.6 to 4.5 kt/d.</div><div>The two most significant factors influencing the refining net margin in the decarbonization scenarios are primarily the CO<sub>2</sub> and the renewable electricity prices. The short-term horizon emerges as the pivotal period, particularly within the high-ambition decarbonization scenarios. In this context, the medium complexity refinery demonstrates economic viability until a CO<sub>2</sub> price of 140 €/t CO<sub>2</sub>, while the high complexity refinery endures up to 205 €/t CO<sub>2</sub>.</div><div>The high complexity refinery is better prepared to face the challenges of decarbonization and the impacts generated on the refining margin. Compared to the BAU scenario, the high complexity refinery shows a negative impact on the net margin that corresponds to a 40 % and 5 % reduction in the short and long term, respectively. Meanwhile, for the medium complexity refinery, the impact on net margin amounts to a 52 % reduction in the short term and a 27 % improvement in the long term.</div><div>Furthermore, our research highlights the significant potential for reducing CO<sub>2</sub> emissions by fully eliminating the use of refinery gas as fuel, providing alternat
{"title":"Assessing the impacts of low-carbon intensity hydrogen integration in oil refineries","authors":"Erik López-Basto , Gijsbert Korevaar , Samantha Eleanor Tanzer , Andrea Ramírez Ramírez","doi":"10.1016/j.cles.2024.100161","DOIUrl":"10.1016/j.cles.2024.100161","url":null,"abstract":"<div><div>This paper evaluates the potential impacts of introducing low-carbon intensity hydrogen technologies in two oil refineries with different complexity levels, emphasizing the role of hydrogen production in reducing CO<sub>2</sub> emissions. The novelty of this work lies in three key aspects: Comprehensive system analysis of refinery complexity using real site data, integration of low-carbon Hydrogen technologies, long-term and short-term strategies. Two Colombian refineries serve as case studies, with technological solutions adapted to their complexity levels. The methodology involves evaluating different options for hydrogen production, accounting for improvement in technological efficiency over time.</div><div>The refinery systems were evaluated in a cost-optimization model built in Linny-r. Three different scenarios were considered, Business-As-Usual (BAU), high, and low-ambitions decarbonization scenarios, focusing on the time horizons of 2030 and 2050.</div><div>When comparing the two case studies, the preferred decarbonization strategy for both facilities involves the substitution of SMR technology with water electrolyzers powered by renewable electricity. Post-2030, biomass-based hydrogen technology is still a costly alternative; however, to achieve CO<sub>2</sub> neutrality, negative emissions storage of biogenic CO<sub>2</sub> emerges as an achievable alternative.</div><div>Our results indicate the achievability of CO<sub>2</sub> reduction objectives in both refineries. Our results show that achieving long-term CO<sub>2</sub> neutrality requires both refineries to increase renewable electricity production by 5 to 6 times for powering water electrolyzers, steam production by 2 to 2.5 times for CO<sub>2</sub> capture, and supply of dry biomass by 2.6 to 4.5 kt/d.</div><div>The two most significant factors influencing the refining net margin in the decarbonization scenarios are primarily the CO<sub>2</sub> and the renewable electricity prices. The short-term horizon emerges as the pivotal period, particularly within the high-ambition decarbonization scenarios. In this context, the medium complexity refinery demonstrates economic viability until a CO<sub>2</sub> price of 140 €/t CO<sub>2</sub>, while the high complexity refinery endures up to 205 €/t CO<sub>2</sub>.</div><div>The high complexity refinery is better prepared to face the challenges of decarbonization and the impacts generated on the refining margin. Compared to the BAU scenario, the high complexity refinery shows a negative impact on the net margin that corresponds to a 40 % and 5 % reduction in the short and long term, respectively. Meanwhile, for the medium complexity refinery, the impact on net margin amounts to a 52 % reduction in the short term and a 27 % improvement in the long term.</div><div>Furthermore, our research highlights the significant potential for reducing CO<sub>2</sub> emissions by fully eliminating the use of refinery gas as fuel, providing alternat","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100161"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743834","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}
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&O) algorithm, effectively addressing challenges such as external disturbances and fluctuating wind environments. By combining ADRC with P&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&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&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.
{"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 , Chirine Benzazah , Chakib Mohssine , El akkary Ahmed , Khouili Driss , Rerhrhaye Badr , 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&O) algorithm, effectively addressing challenges such as external disturbances and fluctuating wind environments. By combining ADRC with P&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&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&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}
Pub Date : 2024-12-01DOI: 10.1016/j.cles.2024.100165
Gidphil Mensah , Richard Opoku , Francis Davis , George Yaw Obeng
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.
{"title":"Techno-economic analysis of green hydrogen production and electric vehicle charging using redundant energy on a solar photovoltaic mini-grid","authors":"Gidphil Mensah , Richard Opoku , Francis Davis , 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}
Pub Date : 2024-11-23DOI: 10.1016/j.cles.2024.100163
Houssem Bouazizi , Maha Benali , Jean-Marc Frayret , Rim Larbi
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.
{"title":"Joint Design and Pricing Problem for Symbiotic Bioethanol Supply Chain Network: Model and Resolution Approach","authors":"Houssem Bouazizi , Maha Benali , Jean-Marc Frayret , 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}
Pub Date : 2024-11-19DOI: 10.1016/j.cles.2024.100162
Md Tasbirul Islam , Sikandar Abdul Qadir , Amjad Ali , Muhammad Waseem Khan
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.
{"title":"Economic and environmental impact assessment of renewable energy integration: A review and future research directions","authors":"Md Tasbirul Islam , Sikandar Abdul Qadir , Amjad Ali , 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}
Pub Date : 2024-10-28DOI: 10.1016/j.cles.2024.100156
Abdulhalim Musa Abubakar , Lukman Buba Umdagas , Moses NyoTonglo Arowo , Marwea Al-Hedrewy , Mahlon Kida Marvin , Noureddine Elboughdiri , Aminullah Zakariyya Abdul , Jenisus O. Dejarlo , Rezkallah Chafika
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.
由于对碳中性能源解决方案的需求日益增长，因此有必要开发二氧化碳（CO2）回收和从湿天然气中生产甜碳中性天然气（CNNG）的高效系统。尽管已有一些方法，但在工艺优化、溶剂效率和产出纯度方面仍存在局限性。本研究旨在利用 Aspen Plus V8.8 中建模的集成式三阶段工艺模拟同时回收 CO2 和 CNNG 的系统，从而弥补这些不足。这项工作的独特之处在于采用 ENRTL-RK 基础模型，并结合敏感性分析来优化 13 个相互连接的工艺单元（包括压缩机、热交换器和萃取塔）的输入参数。主要创新包括采用新颖的装置配置，在最佳条件下，CNNG 的回收效率达到 95.94%，二氧化碳纯度达到 93.185%，超过了传统方法。通过仔细调整输入参数，提高了单乙醇胺（MEA）溶剂的性能，与标准操作设置相比，其吸收效率提高了 12%。敏感性分析表明，进料压力和溶剂流速等关键参数是最大化产出效率的主要驱动因素。这项研究还对动力需求进行了详细的量化评估，在 110 巴排气压力下，压缩机制动马力 (BHP) 为 182605 瓦。通过引入系统的工艺优化方法，该研究填补了现有的研究空白，显著提高了 CNNG 和 CO2 的纯度和回收率，同时最大限度地降低了能耗。研究结果不仅证明了该工艺的可行性，还为进一步完善可持续气体处理技术奠定了基础。
{"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 , Lukman Buba Umdagas , Moses NyoTonglo Arowo , Marwea Al-Hedrewy , Mahlon Kida Marvin , Noureddine Elboughdiri , Aminullah Zakariyya Abdul , Jenisus O. Dejarlo , 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 (CO<sub>2</sub>) 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 CO<sub>2</sub> 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 CO<sub>2</sub> 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 CO<sub>2</sub> 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}
Pub Date : 2024-10-24DOI: 10.1016/j.cles.2024.100157
Shree Om Bade, Olusegun Stanley Tomomewo
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.
{"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, 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 m<sup>2</sup>, 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}
Pub Date : 2024-10-12DOI: 10.1016/j.cles.2024.100153
Chukwuemeka Emmanuel Okafor, Komla Agbenyo Folly
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.
{"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, 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}
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