Reserve optimization method of new energy power system based on improved particle swarm optimization algorithm

With the advancement of the “double carbon” goal, the capacity of distributed new energy access to the power grid is continuously improved, and the operational uncertainty of the power system is enhanced, which makes it more and more difficult for the power grid to absorb distributed power sources. In order to solve this problem, a reserve optimization method for new energy power system based on improved particle swarm optimization is proposed by flexibly adjusting the source-load interaction. Firstly, the reserve optimization model of the source new energy power system is constructed with the goal of minimizing the dispatching cost, operation cost and reserve cost, and the reserve optimization configuration of the new energy power system is realized by satisfying the source network load constraints. Secondly, because the constructed model has the problems of difficult solution, strong nonlinearity and high dimension, this paper uses the improved particle swarm optimization algorithm to optimize the model. Finally, through the simulation of IEEE39, it is verified that the proposed method can effectively reduce the cost and improve the consumption capacity of new energy.