Abstract: In response to the issues of high optimization time costs and increased wind-solar power generation costs in the economic scheduling optimization of wind-solar microgrids, an improved particle swarm optimization-based method for economic scheduling optimization of wind-solar microgrids is proposed. The objective function is established with the aim of minimizing the operational costs of wind-solar microgrids. Constraints such as energy balance, controllable unit operation, and energy storage system conditions are designed to construct an economic scheduling optimization model for wind-solar microgrids. By improving the position and velocity update methods of particles in the particle swarm optimization algorithm, premature convergence during computation is avoided. Using the improved particle swarm optimization algorithm to solve the established optimization model, the economic scheduling optimization decision for wind-solar microgrids is completed, achieving economic scheduling optimization of wind-solar microgrids based on the improved particle swarm optimization algorithm. Experimental results show that the design method optimizes decision-making time costs to no more than 100 ms per iteration, and the average incremental cost of wind-solar power generation in the optimized microgrid is 1.65 yuan/kW, demonstrating excellent timeliness and economic efficiency.