大规模风电接入微电网的两阶段分布式鲁棒储能容量优化方法

For the uncertainty and randomness of renewable energy output, KL divergence is used to simulate the uncertainty of wind power, and a two-stage distributed robust optimization model is established, the first stage determines the investment cost of energy storage capacity, and the second stage calculates the minimum operating cost of the microgrid, which improves the economy while ensuring robustness compared with traditional robust optimization. In the model, the coordinated control of energy storage, distributed controllable power supply and demand response load is considered, and a response scheduling strategy is proposed, and the robustness of the KL divergence threshold control scheme can be adjusted. After transforming the elliptic fuzzy set into a box uncertain set, the original problem is decomposed into the main problem and sub-problem in the form of mixed integer linear programming by CC&G algorithm and strong duality theory, and finally the optimal solution is obtained. The simulation results show that the proposed method has good economy, robustness and flexibility, and can provide reference for practical decisions.