Research on a new dynamic model of power system investment decision based on differential evolution algorithm

Under the environment of the new round of power system reform, the accounting mode of power grid is changed from price difference to cost plus income, and the competition on the power selling side is released, which greatly affects the income of regional power grids, thus greatly reducing the profit margin of power grid enterprises and greatly restricting the investment capacity. The new power reform also proposes to strengthen the overall planning of power. The investment decision-making problem of new power system is a high-dimensional, nonconvex and multi-constrained optimization problem, and the integration of wind farms further increases the difficulty of the problem. In order to optimize the problem better and enhance the convergence performance of the algorithm, based on DE(Differential Evolution) algorithm, some improvement measures such as shared fitness and adaptive adjustment of control parameters are introduced. The research results show that the improved algorithm proposed in this paper improves the convergence speed of DE algorithm, shortens the operation time to a certain extent, and obtains better optimization results, which verifies the effectiveness of the method.