Decision Model of Electric Vehicle Aggregator based on Information Gap Decision Theory

Electric vehicle (EV) aggregators help EV owners and power dispatch centers integrate distributed EV resources for facilitating participation in power trading. However, scheduling is affected by the uncertainty of prices in spot market. In this paper, a charging/discharging management model is constructed under uncertain electricity prices to maximize the benefits of EV aggregators, with the margin between the actual price and its prediction quantified by the information gap decision theory. According to the EVA's attitude toward risks, both risk-averse strategy and risk-seeking strategy can be formulated. Specifically, the risk-averse strategy aims to minimize the reduction of returns due to fluctuating prices, while the risk-seeking strategy seeks higher uncertainty returns. Through validation, the effectiveness of the proposed model in offering EV charging/discharging strategies for the aggregators with different risk preference is proved.