Title
A Multi-timescale Response Capability Evaluation Model of EV Aggregator Considering Customers’ Response Willingness
Abstract
With the popularization of charging piles and the development of V2G (vehicle-to-grid) technology, electric vehicles (EVs) will have more and more opportunities to participate in the operation and scheduling of electric power system. As an agent between the power grid and EV customers, electric vehicle aggregator (EVA) need to comprehend the available EVs' response capacity (RC) when trading with the system operator. This paper proposes a model aiming to evaluate the multitimescale RC of EVA. The RC evaluation of EVA takes into account the response willingness of EV customers, which can make the evaluation of RC boundary more accurate. Firstly, a temporal RC evaluation model of EV monomer considering chargedischarge state and state of charge (SOC) is established. Secondly, based on the consumer psychology model which reflects the relationship between customers' responsivity and incentive price, a multi-timescale RC evaluation model of EVA considering customers' willingness is built. The day-ahead RC of EVA is evaluated by the state prediction data of EVs. According to the control strategy which considers response time (RT) and SOC indicators comprehensively, the RC evaluation results of EVA is revised in intra-day. Finally, using the statistical data from the EU MERGE project, the effectiveness of the proposed evaluation model is verified, and the impact of incentive price and scheduling time scale on the RC of EVA are analyzed. The results indicate that the proposed model can effectively track the scheduling goals of the system and realize the dynamic update of the RC of EVA.
Year
DOI
Venue
2020
10.1109/IAS44978.2020.9334926
2020 IEEE Industry Applications Society Annual Meeting
Keywords
DocType
ISSN
Electric vehicle aggregator,vehicle-to-grid,multitimescale,response capability evaluation,response willingness
Conference
0197-2618
ISBN
Citations 
PageRank 
978-1-7281-7193-7
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Xiangchu Xu100.34
Kangping Li201.01
Fei Wang354.91
Zengqiang Mi400.34
Yulong Jia500.34
Yanwei Jing600.34