Priority Analysis of Influence Factors for Electric Vehicle Demand Response Strategies
As the penetration of renewable energy continues to increase, the demand-side resources in the grid will become more and more important. Electric vehicles (EVs) account for a relatively large proportion of demand-side resources, but individual and social factors have been less considered in multifac...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | International Transactions on Electrical Energy Systems |
| Online Access: | http://dx.doi.org/10.1155/2023/7242304 |
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| _version_ | 1832548005071290368 |
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| author | Yin Yao Yedong Zhu Dongdong Li Bo Zhou Shunfu Lin |
| author_facet | Yin Yao Yedong Zhu Dongdong Li Bo Zhou Shunfu Lin |
| author_sort | Yin Yao |
| collection | DOAJ |
| description | As the penetration of renewable energy continues to increase, the demand-side resources in the grid will become more and more important. Electric vehicles (EVs) account for a relatively large proportion of demand-side resources, but individual and social factors have been less considered in multifactorial studies affecting EV participation in demand response (DR), and the multiscenario DR process has not been adequately studied. Therefore, an EV demand response strategy considering the influence of multiple factors is proposed in this paper. Firstly, a multisource charging load characteristic model is constructed by analyzing the characteristics of EV charging behavior under multiple scenarios. Secondly, the DEMATEL-AISM method is used to analyze the degree of influence of personal and social factors on users’ charging behavior under complex social environments, and the dominant factors in each scenario are identified. Finally, based on the analysis of the dominant factors in multiple scenarios, an EV regulation strategy under the influence of multiple factors is developed to achieve peak shaving. The feasibility of the proposed method is verified through simulation cases. The simulation results reveal that the revenues of aggregators and users are improved, and the stability of the power system is enhanced. |
| format | Article |
| id | doaj-art-a7828af7f71c4f7c977865bc1f121b0a |
| institution | Kabale University |
| issn | 2050-7038 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Transactions on Electrical Energy Systems |
| spelling | doaj-art-a7828af7f71c4f7c977865bc1f121b0a2025-02-03T06:42:41ZengWileyInternational Transactions on Electrical Energy Systems2050-70382023-01-01202310.1155/2023/7242304Priority Analysis of Influence Factors for Electric Vehicle Demand Response StrategiesYin Yao0Yedong Zhu1Dongdong Li2Bo Zhou3Shunfu Lin4Department of Electrical EngineeringDepartment of Electrical EngineeringDepartment of Electrical EngineeringDepartment of Electrical EngineeringDepartment of Electrical EngineeringAs the penetration of renewable energy continues to increase, the demand-side resources in the grid will become more and more important. Electric vehicles (EVs) account for a relatively large proportion of demand-side resources, but individual and social factors have been less considered in multifactorial studies affecting EV participation in demand response (DR), and the multiscenario DR process has not been adequately studied. Therefore, an EV demand response strategy considering the influence of multiple factors is proposed in this paper. Firstly, a multisource charging load characteristic model is constructed by analyzing the characteristics of EV charging behavior under multiple scenarios. Secondly, the DEMATEL-AISM method is used to analyze the degree of influence of personal and social factors on users’ charging behavior under complex social environments, and the dominant factors in each scenario are identified. Finally, based on the analysis of the dominant factors in multiple scenarios, an EV regulation strategy under the influence of multiple factors is developed to achieve peak shaving. The feasibility of the proposed method is verified through simulation cases. The simulation results reveal that the revenues of aggregators and users are improved, and the stability of the power system is enhanced.http://dx.doi.org/10.1155/2023/7242304 |
| spellingShingle | Yin Yao Yedong Zhu Dongdong Li Bo Zhou Shunfu Lin Priority Analysis of Influence Factors for Electric Vehicle Demand Response Strategies International Transactions on Electrical Energy Systems |
| title | Priority Analysis of Influence Factors for Electric Vehicle Demand Response Strategies |
| title_full | Priority Analysis of Influence Factors for Electric Vehicle Demand Response Strategies |
| title_fullStr | Priority Analysis of Influence Factors for Electric Vehicle Demand Response Strategies |
| title_full_unstemmed | Priority Analysis of Influence Factors for Electric Vehicle Demand Response Strategies |
| title_short | Priority Analysis of Influence Factors for Electric Vehicle Demand Response Strategies |
| title_sort | priority analysis of influence factors for electric vehicle demand response strategies |
| url | http://dx.doi.org/10.1155/2023/7242304 |
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