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29 November 2023 Research towards a multi-actor vehicle-pile-net interaction strategy
Minglu Yao, Jian Zhang, Yanjun Xi, Qiang Wang, Xuze Zhang, Yang Ji
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Proceedings Volume 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023); 129370N (2023) https://doi.org/10.1117/12.3013346
Event: International Conference on Internet of Things and Machine Learning (IoTML 2023), 2023, Singapore, Singapore
Abstract
This paper proposes a strategy for setting charging service fees under demand response, based on the analysis of the charging behaviour of EV users, to address the problem of impact load caused by the superposition of peak electricity loads due to the disorderly charging behaviour of a large number of EVs. By guiding users to charge in an orderly manner through price signals, not only can the charging cost of users be reduced, but also the operational efficiency of grid assets and the revenue of charging stations can be improved, thus promoting a good interaction between "vehicle-pile-grid".
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Minglu Yao, Jian Zhang, Yanjun Xi, Qiang Wang, Xuze Zhang, and Yang Ji "Research towards a multi-actor vehicle-pile-net interaction strategy", Proc. SPIE 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023), 129370N (29 November 2023); https://doi.org/10.1117/12.3013346
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KEYWORDS
Particles
Medium wave
Power grids
Californium
Power consumption
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