基于多目标粒子群算法的城市工业区节能减排控制方法研究  

Energy Conservation and Emission Reduction Control Method for Urban Industrial Zones Based on Multi Objective Particle Swarm Optimization

作　　者：杨华 YANG Hua(Yuncheng Ecological Environment Bureau,Yuncheng 044000,Shanxi,China)

机构地区：[1]运城市生态环境局,山西运城044000

出　　处：《能源与节能》2024年第8期111-114,共4页Energy and Energy Conservation

摘　　要：为了降低城市工业区能源消耗量,减少排放,引入了多目标粒子群算法,开展城市工业区节能减排控制方法研究。根据城市工业区的能源使用状况和排放特点,明确了节能减排的多个优化目标。在多个条件的约束下,建立了多目标城市工业区节能减排控制模型。利用多目标粒子群算法对模型进行优化改进,结合节能减排控制模型,引入最优折中解理论实现城市工业区节能减排负荷最优分配控制。通过对比实验证明,新的控制方法应用下,城市工业区的能源消耗量和排放量均减少,达到了节能减排的目的。In order to reduce energy consumption and emissions in urban industrial areas,multi objective particle swarm optimization was introduced to conduct research on energy-saving and emission reduction control method in urban industrial areas.Based on the energy usage and emission characteristics of urban industrial zones,multiple optimization goals for energy conservation and emission reduction were identified.A multi-objective energy-saving and emission reduction control model for urban industrial zones was established under multiple constraints.Using multi objective particle swarm optimization to optimize and improve the model,combined with energy-saving and emission reduction control model,introducing optimal compromise solution theory to achieve optimal allocation control of energy-saving and emission reduction load in urban industrial areas.Through comparative experiments,it was proven that the application of the new control method reduced energy consumption and emissions in urban industrial areas,achieving the goal of energy conservation and emission reduction.

关 键 词：城市工业区 能源消耗 节能减排控制 多目标粒子群算法 

分 类 号：F206[经济管理—国民经济] TP391[自动化与计算机技术—计算机应用技术]