Study on Frequency-Response Optimization of Electric Vehicle Participation in Energy Storage Considering the Strong Uncertainty Model
Due to numerous distributed power sources connecting to the grid, which results in strong grid volatility and diminished power quality, the traditional energy storage configuration is limited in terms of flexibility and economy. Based on this, integrating electric vehicles (EVs) into the distributio...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/16/1/35 |
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| _version_ | 1832587301080793088 |
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| author | Li Cai Chenxi Yang Junting Li Yuhang Liu Juan Yan Xiaojiang Zou |
| author_facet | Li Cai Chenxi Yang Junting Li Yuhang Liu Juan Yan Xiaojiang Zou |
| author_sort | Li Cai |
| collection | DOAJ |
| description | Due to numerous distributed power sources connecting to the grid, which results in strong grid volatility and diminished power quality, the traditional energy storage configuration is limited in terms of flexibility and economy. Based on this, integrating electric vehicles (EVs) into the distribution network as energy storage devices has emerged as a promising development direction. This paper proposes a frequency-response optimization study considering the strong uncertainty model of EVs. First, from the perspective of temporal-spatial characteristics, energy storage resources, and users’ willingness to respond, the strong uncertainty model of EVs is constructed by fitting the trip chain and the access probability of their participation in energy storage. Second, the frequency optimization model is integrated and constructed according to the response capability of a single EV. Finally, examples and scenarios are analyzed to verify that the maximum and minimum frequency offsets are reduced by 69.41% and 66.69%, respectively, which significantly reduces frequency fluctuations and stabilizes the output of EV clusters. |
| format | Article |
| id | doaj-art-8fb97aef7a594cb6a3da9f1eeb4c5ae0 |
| institution | Kabale University |
| issn | 2032-6653 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj-art-8fb97aef7a594cb6a3da9f1eeb4c5ae02025-01-24T13:52:50ZengMDPI AGWorld Electric Vehicle Journal2032-66532025-01-011613510.3390/wevj16010035Study on Frequency-Response Optimization of Electric Vehicle Participation in Energy Storage Considering the Strong Uncertainty ModelLi Cai0Chenxi Yang1Junting Li2Yuhang Liu3Juan Yan4Xiaojiang Zou5Department of Electrical Engineering, Chongqing Three Gorges University, Chongqing 404000, ChinaDepartment of Electrical Engineering, Chongqing Three Gorges University, Chongqing 404000, ChinaDepartment of Electrical Engineering, Chongqing Three Gorges University, Chongqing 404000, ChinaDepartment of Electrical Engineering, Chongqing Three Gorges University, Chongqing 404000, ChinaDepartment of Electrical Engineering, Chongqing Three Gorges University, Chongqing 404000, ChinaResearch and Development Department, Chongqing Andaocheng Automotive Technology Co., Ltd., Chongqing 404100, ChinaDue to numerous distributed power sources connecting to the grid, which results in strong grid volatility and diminished power quality, the traditional energy storage configuration is limited in terms of flexibility and economy. Based on this, integrating electric vehicles (EVs) into the distribution network as energy storage devices has emerged as a promising development direction. This paper proposes a frequency-response optimization study considering the strong uncertainty model of EVs. First, from the perspective of temporal-spatial characteristics, energy storage resources, and users’ willingness to respond, the strong uncertainty model of EVs is constructed by fitting the trip chain and the access probability of their participation in energy storage. Second, the frequency optimization model is integrated and constructed according to the response capability of a single EV. Finally, examples and scenarios are analyzed to verify that the maximum and minimum frequency offsets are reduced by 69.41% and 66.69%, respectively, which significantly reduces frequency fluctuations and stabilizes the output of EV clusters.https://www.mdpi.com/2032-6653/16/1/35electric vehiclesstrong uncertaintyparticipation in energy storagefrequency optimizationuser responsiveness |
| spellingShingle | Li Cai Chenxi Yang Junting Li Yuhang Liu Juan Yan Xiaojiang Zou Study on Frequency-Response Optimization of Electric Vehicle Participation in Energy Storage Considering the Strong Uncertainty Model World Electric Vehicle Journal electric vehicles strong uncertainty participation in energy storage frequency optimization user responsiveness |
| title | Study on Frequency-Response Optimization of Electric Vehicle Participation in Energy Storage Considering the Strong Uncertainty Model |
| title_full | Study on Frequency-Response Optimization of Electric Vehicle Participation in Energy Storage Considering the Strong Uncertainty Model |
| title_fullStr | Study on Frequency-Response Optimization of Electric Vehicle Participation in Energy Storage Considering the Strong Uncertainty Model |
| title_full_unstemmed | Study on Frequency-Response Optimization of Electric Vehicle Participation in Energy Storage Considering the Strong Uncertainty Model |
| title_short | Study on Frequency-Response Optimization of Electric Vehicle Participation in Energy Storage Considering the Strong Uncertainty Model |
| title_sort | study on frequency response optimization of electric vehicle participation in energy storage considering the strong uncertainty model |
| topic | electric vehicles strong uncertainty participation in energy storage frequency optimization user responsiveness |
| url | https://www.mdpi.com/2032-6653/16/1/35 |
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