An Optimal Scheduling Method for Integrated Energy Systems Based on Multi-objective Chaotic Particle Awarm

To enhance the dispatching and control effectiveness of integrated energy systems, an optimized scheduling method for integrated energy systems based on multi-objective chaotic particle swarm optimization is proposed. This method relies on wind power generation system power forecasting technology, selects operational costs and carbon emissions within the integrated energy system's operating cycle as optimization objectives, and employs an improved multi-objective chaotic particle swarm algorithm for computational analysis to determine the optimal dispatching scheme. Practical application results demonstrate that compared to traditional scheduling methods based on PSO and NSGA-II algorithms, the proposed method achieves superior performance, with lower operational costs and carbon emissions for the integrated energy system, making it suitable for large-scale implementation.