Paper Info
Title
A distributed charging strategy based on day ahead price model for PV-powered electric vehicle charging station.
Abstract
This paper studies a distributed charging model based on day-ahead optimal internal price for PV-powered Electric Vehicle (EV) Charging Station (PVCS). Considering the feed-in-tariff of PV energy, the price of utility grid and the forecast model of PV based on back-propagation neural network (BPNN), a system operation model of PVCS is introduced, which consists of the profit model of PVCS operator (PO) and the cost model of EV users. The model proposed in this paper can be designed as a Stackelberg game model, where the PO acts as the leader and all EV users participated are regarded as the followers. An optimization strategy based on heuristic algorithm and nonlinear constrained programming are adopted by the PO and each EV user, respectively. Moreover, a real-time billing strategy is proposed to deal with the errors from the forecasted PV energy and the expected charging arrangements. Finally, through a practical case, the validity of the model is verified in terms of increasing operation profit and reducing charging cost.
Year
DOI
Venue
2019
10.1016/j.asoc.2018.09.041
Applied Soft Computing
Keywords
Field
DocType
Electric vehicle,Charging strategy,Day-ahead price,Stackelberg game,Neural network
Mathematical optimization,Profit model,Electric vehicle,Heuristic (computer science),Charging station,Operator (computer programming),Stackelberg competition,Artificial neural network,Grid,Mathematics
Journal
Volume
ISSN
Citations 
76
1568-4946
0
PageRank 
References 
Authors
0.34
13
5
Name
Order
Citations
PageRank
Tao Rui110.70
Cungang Hu221.09
Guoli Li300.34
Jisheng Tao400.34
Weixiang Shen500.34