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Spatial‐temporal response capability probabilistic evaluation method of electric vehicle aggregator based on trip characteristics modelling.

Authors :
Xu, Xiangchu
Mi, Zengqiang
Yu, Shiyuan
Zhan, Zewei
Ji, Ling
Source :
IET Generation, Transmission & Distribution (Wiley-Blackwell). May2023, Vol. 17 Issue 9, p2192-2206. 15p.
Publication Year :
2023

Abstract

Accurately evaluating the response capability of electric vehicles (EVs) is very important for an EV aggregator (EVA) to formulate reasonable bidding strategies in ancillary service markets. Most of the methods proposed in the existing literature only evaluate EVs' temporal response capability while ignoring their spatial distribution. In addition, the evaluation results provided by the existing methods are typically deterministic, which fails to characterize the uncertainty of EV trip. The above two issues pose high risk of economic loss for the EVA. To this end, a probabilistic evaluation method of spatial‐temporal response capability for EVA is proposed in this paper. The gravity model is adopted to calculate a spatial transfer probability matrix describing EV owners' trip characteristics between different areas at each time in a region which is divided into several different areas according to the evaluation requirements. Then, the trip chains of EVs are modelled based on the spatial transfer probability matrix, and the states of charge (SOCs) of EVs are tracked in the process. The spatial‐temporal response capability of EVA is evaluated based on charging–discharging states and states of charge of EVs, and the probabilistic evaluation results of response capability are obtained by multiple Monte Carlo simulations. The effectiveness of the proposed method is verified on a real dataset from San Francisco, CA, USA. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17518687
Volume :
17
Issue :
9
Database :
Academic Search Index
Journal :
IET Generation, Transmission & Distribution (Wiley-Blackwell)
Publication Type :
Academic Journal
Accession number :
163488853
Full Text :
https://doi.org/10.1049/gtd2.12788