Pub Date : 2024-09-18DOI: 10.3389/fenrg.2024.1391973
Arshad Chughtai, Mohammad Aslam Uqaili, Nayyar Hussain Mirjat, Faheemullah Shaikh, Shoaib Ahmed Khatri
Pakistan is facing the worst level of energy and economic crisis of its history. The underlying reason of the economic crisis is basically due to the energy crisis. Various approaches have been adopted to tackle the energy crises which the country is facing for over 2 decades. Demand-side management (DSM) is the most potent and cost-effective option to redress the energy crisis, which, unfortunately, has been the most neglected strategy in Pakistan. DSM has the potential to save up to 10.0%–15.0% of primary energy to ensure the country’s future energy security. Laws and codes do exist, but ironically, the most vital element of DSM’s policy framework and implementation mechanism is missing. Hence, the main objective of this research is to develop a DSM model for Pakistan and analyze the reference and DSM scenarios. Low-emission analysis platform (LEAP) is used to develop Pakistan’s DSM model for the study period 2021–2050. The three alternative DSM scenarios developed include energy efficiency (EEF), energy conservation (EC), and load management (LOM), and they are all analyzed. The model results estimate the electricity demand forecast of 1009.8 TWh under the reference scenario in 2050, whereas DSM tends to result in a 26.38% decreased electricity demand compared to the reference scenario. The alternative DSM scenarios also outperform the reference scenario. In 2050, the EC scenario reduces consumption by 178.0 TWh and GHG emissions by 19.20 million metric tons, the EEF scenario reduces consumption by 110.30 TWh and GHG emissions by 10.04 million metric tons, and the LOM scenario suggests reduced consumption by 101.0 TWh and GHG emissions by 6.20 million metric tons. This study concluded that the DSM must be institutionalized in Pakistan by building a robust regulatory framework and execution mechanism at the government and utility levels.
{"title":"Demand-side management scenario analysis for the energy-efficient future of Pakistan: Bridging the gap between market interests and national priorities","authors":"Arshad Chughtai, Mohammad Aslam Uqaili, Nayyar Hussain Mirjat, Faheemullah Shaikh, Shoaib Ahmed Khatri","doi":"10.3389/fenrg.2024.1391973","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1391973","url":null,"abstract":"Pakistan is facing the worst level of energy and economic crisis of its history. The underlying reason of the economic crisis is basically due to the energy crisis. Various approaches have been adopted to tackle the energy crises which the country is facing for over 2 decades. Demand-side management (DSM) is the most potent and cost-effective option to redress the energy crisis, which, unfortunately, has been the most neglected strategy in Pakistan. DSM has the potential to save up to 10.0%–15.0% of primary energy to ensure the country’s future energy security. Laws and codes do exist, but ironically, the most vital element of DSM’s policy framework and implementation mechanism is missing. Hence, the main objective of this research is to develop a DSM model for Pakistan and analyze the reference and DSM scenarios. Low-emission analysis platform (LEAP) is used to develop Pakistan’s DSM model for the study period 2021–2050. The three alternative DSM scenarios developed include energy efficiency (EEF), energy conservation (EC), and load management (LOM), and they are all analyzed. The model results estimate the electricity demand forecast of 1009.8 TWh under the reference scenario in 2050, whereas DSM tends to result in a 26.38% decreased electricity demand compared to the reference scenario. The alternative DSM scenarios also outperform the reference scenario. In 2050, the EC scenario reduces consumption by 178.0 TWh and GHG emissions by 19.20 million metric tons, the EEF scenario reduces consumption by 110.30 TWh and GHG emissions by 10.04 million metric tons, and the LOM scenario suggests reduced consumption by 101.0 TWh and GHG emissions by 6.20 million metric tons. This study concluded that the DSM must be institutionalized in Pakistan by building a robust regulatory framework and execution mechanism at the government and utility levels.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":"53 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-18DOI: 10.3389/fenrg.2024.1421832
Yangjun Ren, Yuening Xia
Digitization has become a core engine for China’s energy companies to achieve green transition in a competitive marketplace. Using the panel data of China’s A-share listed energy companies, this study explores the impact of digitalization on energy companies’ green transition. The finding demonstrates that digitalization can significantly drive energy companies’ green transition. This finding remains valid following a series of robustness tests. Moreover, digitalization can indirectly enhance energy companies’ green transition by enhancing technological innovation and optimizing operational capacity. Further research demonstrates that the promoting effect of digitalization on green transition in the state-owned companies, growing and mature energy companies and companies in the east are more fully released. This research could assist policymakers and professionals in energy companies with decision-making references to promote green transition.
数字化已成为中国能源企业在激烈的市场竞争中实现绿色转型的核心引擎。本研究利用中国 A 股上市能源企业的面板数据，探讨了数字化对能源企业绿色转型的影响。研究结果表明，数字化能够显著推动能源企业的绿色转型。经过一系列稳健性检验，这一结论仍然有效。此外，数字化还能通过加强技术创新和优化运营能力间接促进能源企业的绿色转型。进一步的研究表明，数字化对国有企业、成长期和成熟期能源企业以及东部地区企业绿色转型的促进作用得到了更充分的释放。这项研究可以为能源企业的决策者和专业人士提供决策参考，促进绿色转型。
{"title":"Research on the impact of digitalization on energy companies’ green transition: new insights from China","authors":"Yangjun Ren, Yuening Xia","doi":"10.3389/fenrg.2024.1421832","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1421832","url":null,"abstract":"Digitization has become a core engine for China’s energy companies to achieve green transition in a competitive marketplace. Using the panel data of China’s A-share listed energy companies, this study explores the impact of digitalization on energy companies’ green transition. The finding demonstrates that digitalization can significantly drive energy companies’ green transition. This finding remains valid following a series of robustness tests. Moreover, digitalization can indirectly enhance energy companies’ green transition by enhancing technological innovation and optimizing operational capacity. Further research demonstrates that the promoting effect of digitalization on green transition in the state-owned companies, growing and mature energy companies and companies in the east are more fully released. This research could assist policymakers and professionals in energy companies with decision-making references to promote green transition.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":"51 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-18DOI: 10.3389/fenrg.2024.1421212
R. Lalhmachhuana, Subhasish Deb, Subir Datta, Ksh. Robert Singh, Umit Cali, Taha Selim Ustun
In this work, a study of economic and emission dispatch issues based on the multi-objective optimization is solved, and generation costs and emissions are reduced by utilizing multi-objective optimization techniques. This optimization is carried out in an IEEE-30 bus system, with and without the integration of wind energy sources, with equality and inequality constraints. The equality constraints are the power balance constraints, stipulating that to have an optimal solution, the generated power must be adequate to satisfy the load demand plus losses. The inequality constraints are a collection of limitations for active power generation, reactive power generation, generator bus voltage, and load bus voltage. To track the hourly load demand, a daily load profile is established using the IEEE-30 bus system. The generation costs and emissions in the system are optimized using multi-objective particle swarm optimization and multi-objective Ant–Lion Optimization approaches. In order to determine the goals’ minimum values, a fuzzy min–max technique is applied. The values that have been minimized are then compared to determine how well wind energy integration has reduced the generation costs and emissions. Two case studies are performed in this work. For Case 1, the total generation costs and emissions using MOPSO are less, with a difference of $42.763, while MOALO has lower emissions, with a difference of 157.337 tons. For Case 2, with the implementation of wind energy, MOPSO has lower total generation costs, with a difference of $51.678, and lower emissions, with a difference of 459.446 tons.
{"title":"Multi-objective-based economic and emission dispatch with integration of wind energy sources using different optimization algorithms","authors":"R. Lalhmachhuana, Subhasish Deb, Subir Datta, Ksh. Robert Singh, Umit Cali, Taha Selim Ustun","doi":"10.3389/fenrg.2024.1421212","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1421212","url":null,"abstract":"In this work, a study of economic and emission dispatch issues based on the multi-objective optimization is solved, and generation costs and emissions are reduced by utilizing multi-objective optimization techniques. This optimization is carried out in an IEEE-30 bus system, with and without the integration of wind energy sources, with equality and inequality constraints. The equality constraints are the power balance constraints, stipulating that to have an optimal solution, the generated power must be adequate to satisfy the load demand plus losses. The inequality constraints are a collection of limitations for active power generation, reactive power generation, generator bus voltage, and load bus voltage. To track the hourly load demand, a daily load profile is established using the IEEE-30 bus system. The generation costs and emissions in the system are optimized using multi-objective particle swarm optimization and multi-objective Ant–Lion Optimization approaches. In order to determine the goals’ minimum values, a fuzzy min–max technique is applied. The values that have been minimized are then compared to determine how well wind energy integration has reduced the generation costs and emissions. Two case studies are performed in this work. For Case 1, the total generation costs and emissions using MOPSO are less, with a difference of $42.763, while MOALO has lower emissions, with a difference of 157.337 tons. For Case 2, with the implementation of wind energy, MOPSO has lower total generation costs, with a difference of $51.678, and lower emissions, with a difference of 459.446 tons.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":"207 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-18DOI: 10.3389/fenrg.2024.1403883
Anis ur Rehman, Haris M. Khalid, S. M. Muyeen
IntroductionThe integration of electric vehicles (EVs) into the power network challenges the 1) grid capacity, 2) stability, and 3) management. This is due to the 1) increased peak demand, 2) infrastructure strain, and 3) intermittent charging patterns. Previous studies lack comprehensive integration of renewable energy and battery storage with EV charging.MethodsTo address these challenges, this study explores the effectiveness of incorporating renewable energy resources (RERs) and battery energy storage systems (BESS) alongside the traditional grid. The proposed study utilizes the HOMER Grid® and conducted a comprehensive analysis.ResultsThe proposed study compares two grid integrated scenarios: 1) Case-1 (grid and photovoltaic (PV) systems), and 2) Case-2 (grid, PV systems, and BESS). Both these scenarios are compared against a Base case relying solely on grid power. The evaluation employed techno-economic analysis while focusing on 1) net present cost (NPC), 2) cost of energy, and 3) annualized savings. Additionally, the proposed study analyzed 4) seasonal variations in EV charging demand, 5) grid interactions, 6) PV production, and 7) the operation of BESS in both summer and winter. The comparative analysis reveals that the Base case incurs a net present cost (NPC) of $546,977 and a cost of energy (COE) of $0.354 per kWh. In contrast, Case-1, which integrates a 100 kW PV system, shows a significantly lower NPC of -$122,962 and a reduced COE of -$0.043 per kWh, with annualized savings of $61,492. Case-2, incorporating both the 100 kW PV system and a BESS with a capacity of 9.8 kWh, has a higher NPC of $309,667 but a COE of $0.112 per kWh and provides annual savings of $51,233 compared to the Base case.DiscussionSeasonal analysis highlights that Case-2 achieves the lowest carbon emissions in summer, ranging from 2.0 to 2.5 tons, while Case-1 shows the lowest emissions in winter, ranging from 3.2 to 3.4 tons. This model 1) reduces operational costs, 2) minimizes carbon emissions, while 3) making it compelling for future energy systems in increasing EV adoption.
{"title":"Grid-integrated solutions for sustainable EV charging: a comparative study of renewable energy and battery storage systems","authors":"Anis ur Rehman, Haris M. Khalid, S. M. Muyeen","doi":"10.3389/fenrg.2024.1403883","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1403883","url":null,"abstract":"IntroductionThe integration of electric vehicles (EVs) into the power network challenges the 1) grid capacity, 2) stability, and 3) management. This is due to the 1) increased peak demand, 2) infrastructure strain, and 3) intermittent charging patterns. Previous studies lack comprehensive integration of renewable energy and battery storage with EV charging.MethodsTo address these challenges, this study explores the effectiveness of incorporating renewable energy resources (RERs) and battery energy storage systems (BESS) alongside the traditional grid. The proposed study utilizes the HOMER Grid<jats:sup>®</jats:sup> and conducted a comprehensive analysis.ResultsThe proposed study compares two grid integrated scenarios: 1) Case-1 (grid and photovoltaic (PV) systems), and 2) Case-2 (grid, PV systems, and BESS). Both these scenarios are compared against a Base case relying solely on grid power. The evaluation employed techno-economic analysis while focusing on 1) net present cost (NPC), 2) cost of energy, and 3) annualized savings. Additionally, the proposed study analyzed 4) seasonal variations in EV charging demand, 5) grid interactions, 6) PV production, and 7) the operation of BESS in both summer and winter. The comparative analysis reveals that the Base case incurs a net present cost (NPC) of $546,977 and a cost of energy (COE) of $0.354 per kWh. In contrast, Case-1, which integrates a 100 kW PV system, shows a significantly lower NPC of -$122,962 and a reduced COE of -$0.043 per kWh, with annualized savings of $61,492. Case-2, incorporating both the 100 kW PV system and a BESS with a capacity of 9.8 kWh, has a higher NPC of $309,667 but a COE of $0.112 per kWh and provides annual savings of $51,233 compared to the Base case.DiscussionSeasonal analysis highlights that Case-2 achieves the lowest carbon emissions in summer, ranging from 2.0 to 2.5 tons, while Case-1 shows the lowest emissions in winter, ranging from 3.2 to 3.4 tons. This model 1) reduces operational costs, 2) minimizes carbon emissions, while 3) making it compelling for future energy systems in increasing EV adoption.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":"40 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the case of resistance-inductance lines in PV station area, the problem of voltage overstep is easy to occur. This article proposes a reactive power compensation control method to improve the voltage stability in the photovoltaic power plant area, which addresses the problem of voltage at the point of common coupling (PCC) exceeding the upper limit due to resistance circuits and exceeding the lower limit due to relatively insufficient reactive power output when the output active power is high. The idea is to achieve dynamic adjustment of PCC voltage by paralleling a static reactive power generator (SVG) at the grid connection point and using a variable droop control method. In addition, a reactive power optimization method based on improved particle swarm optimization (IPSO) algorithm is proposed to address the changes in power flow caused by photovoltaic integration in the distribution network system. The proposed improvement method not only effectively reduces network losses but also significantly improves voltage stability.
{"title":"Research on reactive power compensation control method for improving the voltage stability of photovoltaic station area","authors":"Wei Zhang, Zhe Zhang, Yuanyi Dai, Chen Dong, Zhijia Yu, Yue Hu","doi":"10.3389/fenrg.2024.1396074","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1396074","url":null,"abstract":"In the case of resistance-inductance lines in PV station area, the problem of voltage overstep is easy to occur. This article proposes a reactive power compensation control method to improve the voltage stability in the photovoltaic power plant area, which addresses the problem of voltage at the point of common coupling (PCC) exceeding the upper limit due to resistance circuits and exceeding the lower limit due to relatively insufficient reactive power output when the output active power is high. The idea is to achieve dynamic adjustment of PCC voltage by paralleling a static reactive power generator (SVG) at the grid connection point and using a variable droop control method. In addition, a reactive power optimization method based on improved particle swarm optimization (IPSO) algorithm is proposed to address the changes in power flow caused by photovoltaic integration in the distribution network system. The proposed improvement method not only effectively reduces network losses but also significantly improves voltage stability.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":"6 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-13DOI: 10.3389/fenrg.2024.1454275
Manuel Corrales-Gonzalez, George Lavidas, Andrea Lira-Loarca, Giovanni Besio
Nowadays, numerous governments have instituted diverse regulatory frameworks aimed at fostering the assimilation of sustainable energy sources characterized by reduced environmental footprints. Solar, wind, geothermal, and ocean energies were subject to extensive scrutiny, owing to their ecological merits. However, these sources exhibit pronounced temporal fluctuations. Notably, ocean dynamics offer vast energy reservoirs, with oceanic waves containing significant amounts of energy. In the Central American Pacific context, the exploration of wave energy resources is currently underway. Accurate numerical wave models are required for applied studies such as those focused on the estimation of exploitable wave power; and even more so in Central American region of the Pacific Ocean where existing numerical models simulations have so far relied on coarse resolution and limited validation field data. This work presents a high-resolution unstructured wave hindcast over the Central American Pacific region, implemented using the third-generation spectral wave model WAVEWATCH III over the period between 1979 and 2021. The results of the significant wave height have been bias-corrected on the basis of satellite information spanning 2005 to 2015, and further validation was performed using wave buoy and acoustic Doppler current profiler (ADCP) records located in the nearshore region of the Central America Pacific coast. After correction and validation of the wave hindcast, we employed the dataset for the evaluation and assessment of wave energy and its possible exploitation using different wave energy converters (WECs). This evaluation addressed the need to diverse the energy portfolio within the exclusive economic zones of Guatemala, El Salvador, Honduras, Nicaragua, Costa Rica, Panama, Colombia, and Ecuador in a sustainable manner. Moreover, a comprehensive analysis was carried out on the advantages of harnessing wave energy, juxtaposed with the imperative of regulatory frameworks and the current dearth of economic and environmental guidelines requisite for development within the region.
{"title":"Wave energy assessment and wave converter applicability at the Pacific coast of Central America","authors":"Manuel Corrales-Gonzalez, George Lavidas, Andrea Lira-Loarca, Giovanni Besio","doi":"10.3389/fenrg.2024.1454275","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1454275","url":null,"abstract":"Nowadays, numerous governments have instituted diverse regulatory frameworks aimed at fostering the assimilation of sustainable energy sources characterized by reduced environmental footprints. Solar, wind, geothermal, and ocean energies were subject to extensive scrutiny, owing to their ecological merits. However, these sources exhibit pronounced temporal fluctuations. Notably, ocean dynamics offer vast energy reservoirs, with oceanic waves containing significant amounts of energy. In the Central American Pacific context, the exploration of wave energy resources is currently underway. Accurate numerical wave models are required for applied studies such as those focused on the estimation of exploitable wave power; and even more so in Central American region of the Pacific Ocean where existing numerical models simulations have so far relied on coarse resolution and limited validation field data. This work presents a high-resolution unstructured wave hindcast over the Central American Pacific region, implemented using the third-generation spectral wave model WAVEWATCH III over the period between 1979 and 2021. The results of the significant wave height have been bias-corrected on the basis of satellite information spanning 2005 to 2015, and further validation was performed using wave buoy and acoustic Doppler current profiler (ADCP) records located in the nearshore region of the Central America Pacific coast. After correction and validation of the wave hindcast, we employed the dataset for the evaluation and assessment of wave energy and its possible exploitation using different wave energy converters (WECs). This evaluation addressed the need to diverse the energy portfolio within the exclusive economic zones of Guatemala, El Salvador, Honduras, Nicaragua, Costa Rica, Panama, Colombia, and Ecuador in a sustainable manner. Moreover, a comprehensive analysis was carried out on the advantages of harnessing wave energy, juxtaposed with the imperative of regulatory frameworks and the current dearth of economic and environmental guidelines requisite for development within the region.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":"246 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-13DOI: 10.3389/fenrg.2024.1445092
Ran Ding, Xuanyuan Wang, Wei Qiu, Yiming Yao, Haixiang Xu, Yan Geng, Zhihuan Zhuo, Jiayi Han
As the integration of high-proportion renewable energy into the grid increases, the intermittency and uncertainty of renewable energy output significantly affect the safe and stable operation of the power system. Combining utility-scale energy storage technology with renewable coordination is one of the methods to address these issues. Compressed air energy storage (CAES) has garnered extensive attention due to its large capacity, long operational life, and clean, low-carbon advantages. Given the poor compressibility of air and its high critical point, using carbon dioxide as the working fluid in utility-scale energy storage systems can achieve higher energy storage density and cycle efficiency. Accordingly, this paper focuses on the study of utility-scale energy storage system modeling and scheduling methods considering carbon dioxide energy storage. It investigates Compressed Carbon Dioxide Energy Storage (CCES) systems, analyzes the operational framework of typical CCES systems, and sequentially establishes models for the energy storage process, energy release process, hot water tank operation, and gas storage tank operation. Based on this, it explores power system optimization dispatch methods considering CCES, incorporating the established models into an optimization dispatch model for power systems with high wind power penetration. Within the framework of a safe constraint unit commitment study, using the IEEE-30 nodes model, the effectiveness of the established models is validated. The case study results confirm the role of CCES in enhancing the absorption rate of renewable coordination. Moreover, under the same storage conditions, compared to, CCES offers greater charging and discharging power and higher energy storage density.
{"title":"Modeling and scheduling of utility-scale energy storage toward high-share renewable coordination","authors":"Ran Ding, Xuanyuan Wang, Wei Qiu, Yiming Yao, Haixiang Xu, Yan Geng, Zhihuan Zhuo, Jiayi Han","doi":"10.3389/fenrg.2024.1445092","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1445092","url":null,"abstract":"As the integration of high-proportion renewable energy into the grid increases, the intermittency and uncertainty of renewable energy output significantly affect the safe and stable operation of the power system. Combining utility-scale energy storage technology with renewable coordination is one of the methods to address these issues. Compressed air energy storage (CAES) has garnered extensive attention due to its large capacity, long operational life, and clean, low-carbon advantages. Given the poor compressibility of air and its high critical point, using carbon dioxide as the working fluid in utility-scale energy storage systems can achieve higher energy storage density and cycle efficiency. Accordingly, this paper focuses on the study of utility-scale energy storage system modeling and scheduling methods considering carbon dioxide energy storage. It investigates Compressed Carbon Dioxide Energy Storage (CCES) systems, analyzes the operational framework of typical CCES systems, and sequentially establishes models for the energy storage process, energy release process, hot water tank operation, and gas storage tank operation. Based on this, it explores power system optimization dispatch methods considering CCES, incorporating the established models into an optimization dispatch model for power systems with high wind power penetration. Within the framework of a safe constraint unit commitment study, using the IEEE-30 nodes model, the effectiveness of the established models is validated. The case study results confirm the role of CCES in enhancing the absorption rate of renewable coordination. Moreover, under the same storage conditions, compared to, CCES offers greater charging and discharging power and higher energy storage density.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":"77 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-13DOI: 10.3389/fenrg.2024.1478072
Zhangbin Yang, Hongping Yuan, Xi Cai, Xueguang Lian, Jiang Mao, Xiangjian Shi
Regarding the monitoring and control technology of pumped storage power stations, the monitoring methods for the operating parameters of the turbines in pumped storage power stations were first analyzed, including the monitoring locations and methods for pressure and vibration, as well as the analysis of the reasons for special operating conditions; Secondly, the operation monitoring and fault diagnosis system of pumped storage power stations was summarized and introduced, including the commonly used monitoring systems, fault diagnosis principles, and application situations. Finally, the development trend of turbine monitoring technology and fault diagnosis was discussed.
{"title":"Monitoring technology of hydroturbines in pumped storage power stations: a mini review","authors":"Zhangbin Yang, Hongping Yuan, Xi Cai, Xueguang Lian, Jiang Mao, Xiangjian Shi","doi":"10.3389/fenrg.2024.1478072","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1478072","url":null,"abstract":"Regarding the monitoring and control technology of pumped storage power stations, the monitoring methods for the operating parameters of the turbines in pumped storage power stations were first analyzed, including the monitoring locations and methods for pressure and vibration, as well as the analysis of the reasons for special operating conditions; Secondly, the operation monitoring and fault diagnosis system of pumped storage power stations was summarized and introduced, including the commonly used monitoring systems, fault diagnosis principles, and application situations. Finally, the development trend of turbine monitoring technology and fault diagnosis was discussed.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":"99 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the increasing penetration of distributed energy in the distribution network, it is urgent to study how to ensure the stable and reliable operation of the power grid under fault conditions. To solve this problem, this study proposes a method for partitioning distribution network islands and reconstructing faults considering the Conditional Value at Risk (CVaR). This method aims to enhance the resilience of the distribution network and the recovery capability of critical loads. Initially, a partitioning model for distribution network islands based on depth-first and breadth-first search algorithms was constructed. Building upon this partitioning, a fault reconstruction method for distribution networks that considers CVaR was developed. This method utilizes CVaR theory to transform costs and quantifies the risk that the uncertainty of distributed energy resources poses to distribution network reconstruction strategies. Finally, the effectiveness of the proposed method is demonstrated using an improved IEEE 33-node system, generating typical fault scenarios.
{"title":"Conditional value at risk-based island partitioning and fault restoration reconfiguration of active distribution networks","authors":"Zhuyi Peng, Wenjia Zhang, Wenchao Xu, Hui Cai, Feifei Zhao, Xingning Han, Kanghui Gu","doi":"10.3389/fenrg.2024.1460894","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1460894","url":null,"abstract":"With the increasing penetration of distributed energy in the distribution network, it is urgent to study how to ensure the stable and reliable operation of the power grid under fault conditions. To solve this problem, this study proposes a method for partitioning distribution network islands and reconstructing faults considering the Conditional Value at Risk (CVaR). This method aims to enhance the resilience of the distribution network and the recovery capability of critical loads. Initially, a partitioning model for distribution network islands based on depth-first and breadth-first search algorithms was constructed. Building upon this partitioning, a fault reconstruction method for distribution networks that considers CVaR was developed. This method utilizes CVaR theory to transform costs and quantifies the risk that the uncertainty of distributed energy resources poses to distribution network reconstruction strategies. Finally, the effectiveness of the proposed method is demonstrated using an improved IEEE 33-node system, generating typical fault scenarios.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":"188 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The intermittent and fluctuating nature of active power output from wind power significantly affects the Load Frequency Control (LFC) in a power grid based on active power balance. To address this issue, this paper proposes a cloud-based intelligent PI controller designed to enhance the performance of LFC in smart grids with large-scale wind power integration. By using the error and the rate of change of error as the antecedent inputs of the cloud model-based controller and the tuning values of P and I as the consequent outputs of the cloud model, adaptive online tuning of the PI parameters is achieved. Based on the control rules of LFC in interconnected power grids and considering the uncertainty of wind power’s active power output, the membership cloud parameters are designed, which effectively solves the problems of poor parameter robustness in traditional PI control and significant human influence on membership degrees in Fuzzy PI control. A simulation model of a dual-area interconnected power grid with wind power for LFC was built using Matlab/Simulink. Two typical disturbances, namely random fluctuations in wind power and sudden increases/decreases in load, were simulated. The simulation results demonstrate that the cloud model-based intelligent PI controller designed in this paper can effectively track the frequency variations caused by random fluctuations in wind power and exhibits strong robustness.
风电有功功率输出的间歇性和波动性极大地影响了基于有功功率平衡的电网中的负载频率控制（LFC）。针对这一问题，本文提出了一种基于云的智能 PI 控制器，旨在提高大规模风电集成智能电网中 LFC 的性能。通过将误差和误差变化率作为基于云模型控制器的前输入，将 P 和 I 的调整值作为云模型的后输出，实现了 PI 参数的自适应在线调整。基于互联电网中 LFC 的控制规则，并考虑到风电有功功率输出的不确定性，设计了成员云参数，有效解决了传统 PI 控制中参数鲁棒性差和模糊 PI 控制中成员度受人为影响大的问题。利用 Matlab/Simulink 建立了风电双区互联电网的 LFC 仿真模型。模拟了两种典型的干扰，即风力发电的随机波动和负荷的突然增加/减少。仿真结果表明，本文设计的基于云模型的智能 PI 控制器能有效跟踪风电随机波动引起的频率变化，并表现出很强的鲁棒性。
{"title":"Cloud model-based intelligent controller for load frequency control of power grid with large-scale wind power integration","authors":"Dexin Li, Xiangyu Lv, Haifeng Zhang, Xiangdong Meng, Zhenjun Xu, Chao Chen, Taiming Liu","doi":"10.3389/fenrg.2024.1477645","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1477645","url":null,"abstract":"The intermittent and fluctuating nature of active power output from wind power significantly affects the Load Frequency Control (LFC) in a power grid based on active power balance. To address this issue, this paper proposes a cloud-based intelligent PI controller designed to enhance the performance of LFC in smart grids with large-scale wind power integration. By using the error and the rate of change of error as the antecedent inputs of the cloud model-based controller and the tuning values of P and I as the consequent outputs of the cloud model, adaptive online tuning of the PI parameters is achieved. Based on the control rules of LFC in interconnected power grids and considering the uncertainty of wind power’s active power output, the membership cloud parameters are designed, which effectively solves the problems of poor parameter robustness in traditional PI control and significant human influence on membership degrees in Fuzzy PI control. A simulation model of a dual-area interconnected power grid with wind power for LFC was built using Matlab/Simulink. Two typical disturbances, namely random fluctuations in wind power and sudden increases/decreases in load, were simulated. The simulation results demonstrate that the cloud model-based intelligent PI controller designed in this paper can effectively track the frequency variations caused by random fluctuations in wind power and exhibits strong robustness.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":"30 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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