Optimization strategy for smoothing wind and solar power output fluctuations based on Copula correlation modeling and coordinated regulation of thermal storage electric heating

Aiming at the grid-connected fluctuation problem caused by the abundant wind and solar energy resources but insufficient local absorption capacity in rural areas of my country, this paper proposes an output fluctuation smoothing optimization strategy that integrates multi-wind farm correlation modeling and flexible regulation of thermal storage electric heating. Firstly, a multidimensional joint probability distribution model based on Copula function is constructed, and the improved K-means clustering algorithm is used to achieve scene reduction, obtain characteristic scenes with probability weights, and effectively characterize the spatiotemporal dependence of the output of wind farm groups. Secondly, in view of the problem of delayed load response and high simultaneity of thermal storage electric heating, a wind-solar-thermal storage collaborative optimization model is constructed. With the goal of minimizing the net load fluctuation of the system, the operation mode of the electric boiler and the charging and discharging strategy of the thermal storage device are dynamically coordinated. Finally, the simulation shows that the proposed strategy not only ensures the indoor temperature comfort, but also verifies the effectiveness of improving the wind-solar absorption capacity and reducing the regulation pressure of the power grid.