Prediction of temporal and spatial distribution of electric vehicle charging load considering coupling factors
One of the components to realize the mutual benefit and win-win between electric vehicle (EV) and power grid is to effectively predict the charging load of EVs while the difficulty of charging load prediction is increased because of the randomness of temporal and spatial transfer of EV and a variety...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Electric Power Engineering Technology
2022-05-01
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| Series: | 电力工程技术 |
| Subjects: | |
| Online Access: | https://www.epet-info.com/dlgcjs/article/pdf/210828338 |
| _version_ | 1811295319379410944 |
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| author | CHENG Shan ZHAO Zikai CHEN Nuo YU Zihao |
| author_facet | CHENG Shan ZHAO Zikai CHEN Nuo YU Zihao |
| author_sort | CHENG Shan |
| collection | DOAJ |
| description | One of the components to realize the mutual benefit and win-win between electric vehicle (EV) and power grid is to effectively predict the charging load of EVs while the difficulty of charging load prediction is increased because of the randomness of temporal and spatial transfer of EV and a variety of coupling factors in the transfer process. In this paper,a method for predicting the spatial and temporal distribution of EV charging load considering dynamic transfer planning and coupling factors is proposed. Firstly,an individual travel mathematical model with multiple types of EVs is established based on travel chain technology. On this basis,considering the traffic flux,road conditions and temperature,the mathematical model of energy consumption per mileage of EV is constructed. Secondly,based on Markov decision process theory,considering the residual path and road network congestion information,the road network information is dynamically updated and the temporal and spatial transfer path of EVs is randomly planned. Finally,based on an example,the temporal and spatial distribution of EV and its charging load are compared and analyzed under different strategies,functional areas and travel days. The results show that the proposed method can fully reflect the travel decision of EV owners,and the prediction results can truly reflect the differences in the amplitude and distribution of charging load due to EV types and functional areas. |
| first_indexed | 2024-04-13T05:31:39Z |
| format | Article |
| id | doaj.art-e14f4298961541aabe7d54177bb465b6 |
| institution | Directory Open Access Journal |
| issn | 2096-3203 |
| language | zho |
| last_indexed | 2024-04-13T05:31:39Z |
| publishDate | 2022-05-01 |
| publisher | Editorial Department of Electric Power Engineering Technology |
| record_format | Article |
| series | 电力工程技术 |
| spelling | doaj.art-e14f4298961541aabe7d54177bb465b62022-12-22T03:00:26ZzhoEditorial Department of Electric Power Engineering Technology电力工程技术2096-32032022-05-01413194201,20810.12158/j.2096-3203.2022.03.023Prediction of temporal and spatial distribution of electric vehicle charging load considering coupling factorsCHENG Shan0ZHAO Zikai1CHEN Nuo2YU Zihao3Yichang Key Laboratory of Intelligent Operation and Security Defense of Power System (China Three Gorges University), Yichang 443002, China;College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaYichang Key Laboratory of Intelligent Operation and Security Defense of Power System (China Three Gorges University), Yichang 443002, China;College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaYichang Key Laboratory of Intelligent Operation and Security Defense of Power System (China Three Gorges University), Yichang 443002, China;College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaYichang Key Laboratory of Intelligent Operation and Security Defense of Power System (China Three Gorges University), Yichang 443002, China;College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaOne of the components to realize the mutual benefit and win-win between electric vehicle (EV) and power grid is to effectively predict the charging load of EVs while the difficulty of charging load prediction is increased because of the randomness of temporal and spatial transfer of EV and a variety of coupling factors in the transfer process. In this paper,a method for predicting the spatial and temporal distribution of EV charging load considering dynamic transfer planning and coupling factors is proposed. Firstly,an individual travel mathematical model with multiple types of EVs is established based on travel chain technology. On this basis,considering the traffic flux,road conditions and temperature,the mathematical model of energy consumption per mileage of EV is constructed. Secondly,based on Markov decision process theory,considering the residual path and road network congestion information,the road network information is dynamically updated and the temporal and spatial transfer path of EVs is randomly planned. Finally,based on an example,the temporal and spatial distribution of EV and its charging load are compared and analyzed under different strategies,functional areas and travel days. The results show that the proposed method can fully reflect the travel decision of EV owners,and the prediction results can truly reflect the differences in the amplitude and distribution of charging load due to EV types and functional areas.https://www.epet-info.com/dlgcjs/article/pdf/210828338electric vehicle (ev)markov decision process theorytravel chainenergy consumption modelcharging loadtemporal and spatial distribution |
| spellingShingle | CHENG Shan ZHAO Zikai CHEN Nuo YU Zihao Prediction of temporal and spatial distribution of electric vehicle charging load considering coupling factors 电力工程技术 electric vehicle (ev) markov decision process theory travel chain energy consumption model charging load temporal and spatial distribution |
| title | Prediction of temporal and spatial distribution of electric vehicle charging load considering coupling factors |
| title_full | Prediction of temporal and spatial distribution of electric vehicle charging load considering coupling factors |
| title_fullStr | Prediction of temporal and spatial distribution of electric vehicle charging load considering coupling factors |
| title_full_unstemmed | Prediction of temporal and spatial distribution of electric vehicle charging load considering coupling factors |
| title_short | Prediction of temporal and spatial distribution of electric vehicle charging load considering coupling factors |
| title_sort | prediction of temporal and spatial distribution of electric vehicle charging load considering coupling factors |
| topic | electric vehicle (ev) markov decision process theory travel chain energy consumption model charging load temporal and spatial distribution |
| url | https://www.epet-info.com/dlgcjs/article/pdf/210828338 |
| work_keys_str_mv | AT chengshan predictionoftemporalandspatialdistributionofelectricvehiclechargingloadconsideringcouplingfactors AT zhaozikai predictionoftemporalandspatialdistributionofelectricvehiclechargingloadconsideringcouplingfactors AT chennuo predictionoftemporalandspatialdistributionofelectricvehiclechargingloadconsideringcouplingfactors AT yuzihao predictionoftemporalandspatialdistributionofelectricvehiclechargingloadconsideringcouplingfactors |