Two-stage Robust optimization Method for Day-ahead Scheduling Considering Renewable Portfolio Standard

摘要

Renewable Portfolio Standard (RPS) can greatly promote clean energy consumption and energy revolution. However, the randomness and volatility of renewable energy output pose challenges to fulfilling the RPS obligation. In order to meet the challenge, a day-ahead scheduling model considering the policy of RPS based on the two-stage robust framework is established in this paper. In this model, the inter-regional transmission constraints of renewable energy are considered because of the extremely uneven geographical distribution of renewable energy in China. In algorithm ways, the model is solved with a column-and-constraint generation method. The master problem is linearized to a mixed integer programming and the sub-problem is converted by strong duality theory rather than KKT equations. The result of case study demonstrates that with the rise of quota ratio and uncertainty budget, the uncertainty becomes increasingly unfavorable to the fulfillment of the policy of RPS. In addition, the superiority of the two-stage robust approach is illustrated.