Open AccessLight robustness model for the bidding strategy of an electric vehicle aggregator
Author(s) -
Gong Xin,
Wang Fei,
Su Yu,
Xu Qiangqiang
Publication year - 2021
Publication title -
iet smart grid
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.612
H-Index - 11
ISSN - 2515-2947
DOI - 10.1049/stg2.12026
Subject(s) - news aggregator , bidding , robustness (evolution) , electric vehicle , computer science , mathematical optimization , market clearing , operations research , econometrics , economics , microeconomics , engineering , mathematics , biochemistry , chemistry , power (physics) , physics , quantum mechanics , gene , operating system
Considering the uncertainties of the behaviour of electric vehicles (EVs) and the bidding of other participants in the market, the light robustness bidding model for the EV aggregator in the day‐ahead market is constructed. The model is a bilevel model, with the upper‐level model representing cost minimisation of the EV aggregator, whereas the lower‐level model represents market clearing providing market price and bidding energy for the upper‐level model. Bids of other market participants and EV driving pattern were not known to the EV aggregator in advance. They were seen as uncertain variables. A numerical example was used to illustrate the feasibility of the proposed method. Through the example analysis, the costs of the EV aggregator under different circumstances are compared and, under the same uncertainties, the results of the method proposed herein are also compared with the traditional robust optimisation method and stochastic fuzzy programming method.