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基于多目标混沌粒子群的综合能源系统优化调度方法

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

  • 摘要: 为了提升综合能源系统调度控制效果,提出一种基于多目标混沌粒子群的综合能源系统优化调度方法。该调度方法以风力发电系统功率预测技术为依托,选择综合能源系统运行周期内的投入成本与碳排放量为优化目标,利用改进多目标混沌粒子群算法进行计算分析,以此确定最佳调度方案。通过实践应用,发现相对于传统基于PSO算法与基于NSGA-II算法的调度方法,所提调度方法的应用效果更好,可使综合能源系统运行成本与碳排放量更低,值得大规模推广。

     

    Abstract: 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.

     

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