Capacity allocation optimization of wind power hybrid energy storage and heating system to absorb abandoned wind

In order to solve the problem of high energy consumption of buildings and serious wind abandonment in the “three northern” area in winter, a wind power hybrid energy storage and heating system composed of lithium battery storage units, solid heat storage devices and heat pump equipment is designed. Firstly, the output power of wind turbine is predicted based on the BP neural network, and the typical daily load curve of heating is obtained by the k-means cluster analysis. Then, a capacity allocation optimization method of the wind power hybrid energy storage and heating system based on the particle swarm optimization algorithm is proposed, which takes the least total cost of the system and the lowest wind abandonment as the constraints to construct the objective function. Finally, the capacity allocation optimization results of the wind power hybrid energy storage and heating system with and without considering wind abandonment are compared. The research shows that the proposed optimization method can not only effectively reduce the wind abandonment rate with strong scenario applicability, but also meet the demand for clean heating in severe cold zone in winter, which provides a reference for the efficient utilization of renewable energy.