Stochastic-Robust Decision-Making Model for Flexible Load Aggregator Considering Uncertainties
Jia Yulong1, Mi Zengqiang1, Yu Yang1, Shen Hao1, Fan Hui2
1.State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Baoding 071003 China; 2. State Grid Hebei Electric Power Supply Co. Ltd Shijiazhuang 050000 China
Abstract With the increasing proportion of electric vehicles, distributed energy storages and thermostatically controlled loads connected to the new generation smart grid, flexible load aggregator, as a bidding entity, will be able to participate in day-ahead electricity market. In this paper, we propose that a stochastic robust model for bidding decision-making of flexible load aggregator in the day-ahead market considering uncertainty. The minimal operating costs of flexible load aggregator is the objective function. The uncertainty of day-ahead price is modeled using stochastic scenarios. The uncertainty of driving behaves of electric vehicles and ambient temperature of temperature-controlled loads are modeled using confidence bounds. Uncertainty of flexible load response are modeled using response willing coefficient simulation. By solving the mixed integer linear programming model, the effectiveness of the proposed model is verified by the example, and the bidding strategy for purchasing and selling energy in flexible load aggregator at different time period is obtained. The model will provide decision-making for flexible load aggregator to participate in the bidding of electricity market.
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2019, Vol. 34 
