Robust Optimization of Static Reserve Planning With Large-Scale Integration of Wind Power: A Game Theoretic Approach

This paper presents a methodology based on game theory for power system static reserve planning with large-scale integration of wind power to ensure the generating capacity adequacy. First, a min–max game model is proposed for decision-making problems with uncertainties. Then, it is applied to the static reserve capacity planning problem. In the proposed model, the system planner (as one player) aims to find the minimum static reserve capacity to meet the total load demand while keeping the system reliability index within a desired value. Nature (as the other player), which determines the wind power output, is modeled as an attacker who wants to worsen the system reliability level due to its uncertainty and inaccurate prediction. Then, a two-stage relaxation algorithm is introduced to solve the min–max game. Finally, the proposed model for static reserve planning is applied to the IEEE Reliability Test System (RTS), and its robustness and high efficiency are demonstrated by comparing it to the traditional expectation method and Monte Carlo method.