Multi-Energy Power System Scheduling Based on Improved Grasshopper Algorithm

With the continuous development of the power system and the increasing awareness of environmental protection, the proportion of renewable energy generation in the power system is constantly increasing, and the scheduling of single thermal power generation units has become a coordinated scheduling mode for multi-energy generation. To solve the scheduling optimization problem of multi-energy power systems with energy storage devices, this paper establishes a multi-energy power system scheduling model of wind-solar-thermal-energy storage battery-pumped storage with the goal of minimizing system generation costs and pollution emissions. This paper introduces an adaptive strategy based on the number of iterations to optimize position update factor. Gaussian mutation is used to perturb the algorithm population, and the elite strategy in the ant lion algorithm is combined with the grasshopper algorithm to solve the proposed scheduling model using an improved multi-objective grasshopper algorithm. Real examples are simulated and analyzed on the Matlab platform, and an optimal multi-objective power system scheduling scheme is proposed. Through simulation analysis of test functions and simulation examples, the superiority of the improved algorithm and the rationality of the established model are verified.