Research on Dynamic Operating Point Coordination Optimization Algorithm of Wind Farms

In the content of carbon peaking and carbon neutrality, the development and utilization of renewable energy have become major initiatives in China's energy development strategy. Wind power is one of the most valuable renewable energy sources. As the total installed capacity of wind power continues to increase and the proportion of wind power in the national energy generation continues to rise, the volatility and uncertainty of its power generation also bring new challenges to the power system. In this paper, we consider the optimization of wind power generation control strategy and parameters to improve the stability of the power grid and new energy consumption capacity. This paper proposes a genetic algorithm-based wind farm dynamic operating point coordination optimization algorithm to make the wind turbine operate at the operating point with minimum load, minimum operating cost, and maximum total power generation under normal external conditions, and also proposes a control strategy framework for wind farms under emergency/fast active command. In this paper, a wind farm with 16 wind turbines is built on MATLAB/Simulink to verify the feasibility of the algorithm verified by this model.