Pub Date : 2024-02-27DOI: 10.3389/fenrg.2024.1383513
R. Rafieenia, Bing Guo, Wei Peng, R. Pomi
{"title":"Editorial: Microbial communities for bioenergy recovery from wastes and waste streams","authors":"R. Rafieenia, Bing Guo, Wei Peng, R. Pomi","doi":"10.3389/fenrg.2024.1383513","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1383513","url":null,"abstract":"","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140427419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Editorial: Multi-physics and multi-scale modeling and simulation methods for nuclear reactor application","authors":"Xingjie Peng, Shichang Liu, Qingming He, Jingang Liang, Jiankai Yu","doi":"10.3389/fenrg.2024.1361541","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1361541","url":null,"abstract":"","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139958101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-30DOI: 10.3389/fenrg.2024.1373437
{"title":"Erratum: Development of a supply chain model for the production of biodiesel from waste cooking oil for sustainable development","authors":"","doi":"10.3389/fenrg.2024.1373437","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1373437","url":null,"abstract":"","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140482474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-18DOI: 10.3389/fenrg.2023.1361118
Deqi Chen, Wei Ding, Lin Chen
{"title":"Editorial: Complex flow and heat transfer in advanced nuclear energy systems","authors":"Deqi Chen, Wei Ding, Lin Chen","doi":"10.3389/fenrg.2023.1361118","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1361118","url":null,"abstract":"","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139525874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-29DOI: 10.3389/fenrg.2023.1349129
Haoran Zhang, Hu Liu, Rui Wang
{"title":"Editorial: New paths towards carbon-neutral future energy systems: planning, operation, and market design","authors":"Haoran Zhang, Hu Liu, Rui Wang","doi":"10.3389/fenrg.2023.1349129","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1349129","url":null,"abstract":"","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139147314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-29DOI: 10.3389/fenrg.2023.1339932
Dongdong Zhang, Huihwang Goh, Haisen Zhao, Tanveer Ahmad
{"title":"Editorial: Key technologies of smart energy system optimization","authors":"Dongdong Zhang, Huihwang Goh, Haisen Zhao, Tanveer Ahmad","doi":"10.3389/fenrg.2023.1339932","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1339932","url":null,"abstract":"","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139145003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-29DOI: 10.3389/fenrg.2023.1298557
Mahamad Nabab Alam, Almoataz Abdelaziz, Tahir Khurshaid, S. Nikolovski, Meng Yen Shih
{"title":"Editorial: Advanced protection for the smart grid","authors":"Mahamad Nabab Alam, Almoataz Abdelaziz, Tahir Khurshaid, S. Nikolovski, Meng Yen Shih","doi":"10.3389/fenrg.2023.1298557","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1298557","url":null,"abstract":"","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139213289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-20DOI: 10.3389/fenrg.2023.1295476
Mounir Bouzguenda, Muahmmad Hatatah, Sheharyar, Aamir Ali, Ghulam Abbas, Aamir Khan, Ezzeddine Touti, Amr Yousef, S. Mirsaeidi, Ahmed Alshahir
The growing popularity of electric vehicles presents a significant challenge to current electric grids since the rising number of these vehicles places additional strain on power systems inside distribution networks. A proposed paradigm is presented for electric vehicles (EVs), which is subsequently partitioned into three distinct dispatching areas to assess its practicality. This study is structured around two primary objectives. The first objective focuses on EV owners aiming to minimize their electricity consumption costs while also receiving compensation for providing services. The second objective involves using an aggregator to establish distinct tariffs for each dispatching area. Additionally, the aggregator aims to shift the charging load demand from peak to off-peak hours and distribute the charging demand to each agent. The authors of this study propose the utilization of a charging and discharging coordination method, specifically the Multi-Agents Charging and Discharging (MACD) algorithm, as a means to successfully tackle the issue of charging demand during peak hours. The objective of the proposed algorithm is to effectively handle the increased charging requirements during peak periods by using vehicle-to-grid (V2G) technologies within the context of Smart Grid systems and electric vehicle (EV) batteries. Importantly, this reduction is achieved without compromising the performance of electric vehicles (EVs) or the convenience experienced by EV owners. The algorithm under consideration demonstrates reduced power charging costs for various sectors. Specifically, it achieves a decrease of 15% for households, 14.6% for corporate buildings, and 14.5% for Industrial Park EV aggregators.
{"title":"An optimal dispatch schedule of EVs considering demand response using improved MACD algorithm","authors":"Mounir Bouzguenda, Muahmmad Hatatah, Sheharyar, Aamir Ali, Ghulam Abbas, Aamir Khan, Ezzeddine Touti, Amr Yousef, S. Mirsaeidi, Ahmed Alshahir","doi":"10.3389/fenrg.2023.1295476","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1295476","url":null,"abstract":"The growing popularity of electric vehicles presents a significant challenge to current electric grids since the rising number of these vehicles places additional strain on power systems inside distribution networks. A proposed paradigm is presented for electric vehicles (EVs), which is subsequently partitioned into three distinct dispatching areas to assess its practicality. This study is structured around two primary objectives. The first objective focuses on EV owners aiming to minimize their electricity consumption costs while also receiving compensation for providing services. The second objective involves using an aggregator to establish distinct tariffs for each dispatching area. Additionally, the aggregator aims to shift the charging load demand from peak to off-peak hours and distribute the charging demand to each agent. The authors of this study propose the utilization of a charging and discharging coordination method, specifically the Multi-Agents Charging and Discharging (MACD) algorithm, as a means to successfully tackle the issue of charging demand during peak hours. The objective of the proposed algorithm is to effectively handle the increased charging requirements during peak periods by using vehicle-to-grid (V2G) technologies within the context of Smart Grid systems and electric vehicle (EV) batteries. Importantly, this reduction is achieved without compromising the performance of electric vehicles (EVs) or the convenience experienced by EV owners. The algorithm under consideration demonstrates reduced power charging costs for various sectors. Specifically, it achieves a decrease of 15% for households, 14.6% for corporate buildings, and 14.5% for Industrial Park EV aggregators.","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139258286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-20DOI: 10.3389/fenrg.2023.1283348
Ahmed G. Khairalla, Hossam Kotb, K. Aboras, Muhammad Ragab, Hesham B. ElRefaie, Y. Ghadi, Amr Yousef
Large-scale energy storage systems (ESSs) that can react quickly to energy fluctuations and store excess energy are required to increase the reliability of electricity grids that rely heavily on renewable energy sources (RESs). Hybrid systems, which combine different energy storage technologies such as batteries and supercapacitors, are becoming increasingly popular because no single technology can satisfy all requirements. In this study, a supercapacitor is used to stabilize quickly shifting bursts of power, while a battery is used to stabilize gradually fluctuating power flow. This paper proposes a robust controller for managing the direct current (DC) bus voltage to optimize the performance of ESS. The proposed controller combines a fractional-order proportional integral (FOPI) with a classical PI controller for the first time in the DC microgrid area. The hybrid (FOPI-PI) controller achieves an outstanding and superior performance in all transient and dynamic response specifications compared to other traditional controllers. The parameters of the suggested controller are incorporated with the self-adaptive bonobo optimizer (SaBO) to determine the optimal values. Furthermore, various optimization techniques are applied to the model and the SaBO’s output outperforms other techniques by minimizing the best objective function. In addition, the current study has utilized a novel power management strategy that includes two closed current loops for both batteries and supercapacitors. By using this method, batteries’ lifespans may be increased while still retaining optimal system performance. The suggested controller is implemented in MATLAB/Simulink 2022b, and the outcomes are reported for several case studies. The findings demonstrate that the control technique remarkably improves the transient response, such as transient duration, overshoot/undershoot, and the settling time. The proposed controller (FOPI-PI) with the SaBO optimizer is effective in maintaining the DC bus voltage under load and solar system variation.
{"title":"Enhanced control strategy and energy management for a photovoltaic system with hybrid energy storage based on self-adaptive bonobo optimization","authors":"Ahmed G. Khairalla, Hossam Kotb, K. Aboras, Muhammad Ragab, Hesham B. ElRefaie, Y. Ghadi, Amr Yousef","doi":"10.3389/fenrg.2023.1283348","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1283348","url":null,"abstract":"Large-scale energy storage systems (ESSs) that can react quickly to energy fluctuations and store excess energy are required to increase the reliability of electricity grids that rely heavily on renewable energy sources (RESs). Hybrid systems, which combine different energy storage technologies such as batteries and supercapacitors, are becoming increasingly popular because no single technology can satisfy all requirements. In this study, a supercapacitor is used to stabilize quickly shifting bursts of power, while a battery is used to stabilize gradually fluctuating power flow. This paper proposes a robust controller for managing the direct current (DC) bus voltage to optimize the performance of ESS. The proposed controller combines a fractional-order proportional integral (FOPI) with a classical PI controller for the first time in the DC microgrid area. The hybrid (FOPI-PI) controller achieves an outstanding and superior performance in all transient and dynamic response specifications compared to other traditional controllers. The parameters of the suggested controller are incorporated with the self-adaptive bonobo optimizer (SaBO) to determine the optimal values. Furthermore, various optimization techniques are applied to the model and the SaBO’s output outperforms other techniques by minimizing the best objective function. In addition, the current study has utilized a novel power management strategy that includes two closed current loops for both batteries and supercapacitors. By using this method, batteries’ lifespans may be increased while still retaining optimal system performance. The suggested controller is implemented in MATLAB/Simulink 2022b, and the outcomes are reported for several case studies. The findings demonstrate that the control technique remarkably improves the transient response, such as transient duration, overshoot/undershoot, and the settling time. The proposed controller (FOPI-PI) with the SaBO optimizer is effective in maintaining the DC bus voltage under load and solar system variation.","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139256060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-17DOI: 10.3389/fenrg.2023.1267355
Bibo Yin, Ping Kuang, Xinhui Deng
Introduction: The digital economy plays a crucial role in achieving synergistic reduction in air pollutants and carbon emissions.Methods: A super-efficiency slack-based model with undesirable outputs was applied to systematically calculate the efficiency of synergistic air pollutants and carbon emissions governance (ESACG). This study used the difference-in-differences (DID), propensity score matching-DID, quantile DID methods and generalized random forest model to empirically test the impact and its heterogeneity of the digital economy on the ESACG, with the establishment of the National Big Data Comprehensive Pilot Zone as a quasi-natural experiment.Results: 1) The digital economy significantly improved the ESACG by optimizing industrial structure in source management, improving energy utilization efficiency in process control, and promoting green technological innovation in end blocking. The digital literacy of talent and digital financial support strengthened its enhancing effect, but the digital infrastructure was insignificant. 2) The digital economy significantly enhanced the ESACG in the cross-regional and regional demonstration zones but inhibited it in the pioneering zones. Its impact on the ESACG in big data infrastructure-integrated development zones was insignificant. 3) Between the 25th and 90th quantiles, there was an asymmetric inverted U-shaped influence of the digital economy on the ESACG, with no discernible impact at the 10th quantile. In cities with better economic development and technological innovation, the contribution of the digital economy to the ESACG was more significant.Discussion: It is necessary to continuously advance the construction of existing pilot zones, steadily expand their coverage, and differentiate between harnessing the experiences of reducing pollution and carbon emissions to formulate strategies for synergistic regional governance.
{"title":"The effect of synergistic pollution and carbon reduction in the digital economy: Quasi-experimental evidence from Chinese cities","authors":"Bibo Yin, Ping Kuang, Xinhui Deng","doi":"10.3389/fenrg.2023.1267355","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1267355","url":null,"abstract":"Introduction: The digital economy plays a crucial role in achieving synergistic reduction in air pollutants and carbon emissions.Methods: A super-efficiency slack-based model with undesirable outputs was applied to systematically calculate the efficiency of synergistic air pollutants and carbon emissions governance (ESACG). This study used the difference-in-differences (DID), propensity score matching-DID, quantile DID methods and generalized random forest model to empirically test the impact and its heterogeneity of the digital economy on the ESACG, with the establishment of the National Big Data Comprehensive Pilot Zone as a quasi-natural experiment.Results: 1) The digital economy significantly improved the ESACG by optimizing industrial structure in source management, improving energy utilization efficiency in process control, and promoting green technological innovation in end blocking. The digital literacy of talent and digital financial support strengthened its enhancing effect, but the digital infrastructure was insignificant. 2) The digital economy significantly enhanced the ESACG in the cross-regional and regional demonstration zones but inhibited it in the pioneering zones. Its impact on the ESACG in big data infrastructure-integrated development zones was insignificant. 3) Between the 25th and 90th quantiles, there was an asymmetric inverted U-shaped influence of the digital economy on the ESACG, with no discernible impact at the 10th quantile. In cities with better economic development and technological innovation, the contribution of the digital economy to the ESACG was more significant.Discussion: It is necessary to continuously advance the construction of existing pilot zones, steadily expand their coverage, and differentiate between harnessing the experiences of reducing pollution and carbon emissions to formulate strategies for synergistic regional governance.","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139264232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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