IGDT-based Demand Side Discharge Bidding Decision Strategy for Electric Vehicle Load Aggregator
Abstract
In allusion to the serious affect of uncertainty of electricity price in the spot market on electric vehicle load aggregator, firstly by use of Monte Carlo simulation the bidding electric quantity in the management area of the load aggregator who could participate in electricity market next day, was obtained. Secondly, utilizing information gap decision theory (IGDT) the deviation between the market cleaning price and the forecasted price was quantized, and then taking the profit maximization of electric vehicle load aggregator as the objective a demand side discharging bidding model was constructed. Analysis on calculating example shows that the proposed bidding decision method possesses availability in economy and flexibility and so on; meanwhile the enthusiasm of electric vehicle owners to take part in the electricity market bidding will be improved.
