基于改进粒子群算法的火电系统节能环保多目标优化调度模型  

Multi-objective Optimization Scheduling Model for Thermal Power System Energy Saving and Environmental Protectionby Based on Improved PSO Algorithm

作　　者：陈碧云[1] 程鹏飞[1] 陶松梅[1] 黄海林 

机构地区：[1]广西大学电气工程学院,南宁530004 [2]广深沙角B电力有限公司,广东深圳523937

出　　处：《华东电力》2012年第3期355-358,共4页East China Electric Power

基　　金：国家自然科学基金项目(50767001);广西自然科学基金项目(2011jjA60017)~~

摘　　要：针对火电系统生产过程中的环境污染问题,提出以火电系统节能环保为重点研究对象的多目标优化调度模型,并以改进的粒子群算法进行求解。结合灰色系统理论中有关灰色关联度的概念对粒子群算法多目标求解机制进行改进,对煤耗量、污染气体和烟尘排放等的多目标火电系统优化求解,引入压缩因子改善粒子群算法的性能,增强其全局收敛能力。通过IEEE 14节点系统算例证明本算法的有效性。In order to solve the environmental pollution problem in the thermal power generation process,this paper presents a multi-objective optimization scheduling model with a focus on energy saving and environmental protection, and draws on improved particle swarm optimization（PSO） algorithm for the solutions.The PSO multi-objective solution mechanism is improved in combination with the concept of grey relation in grey theory;thereby the optimized solutions are achieved for the multiple objectives of thermal power system,including coal consumption,gaseous pollutants, dust emissions;compressibility factor is introduced to enhance PSO algorithm performance and its global convergence. Finally,the calculation example of IEEE 14 bus system verifies the validity of the proposed algorithm.

关 键 词：节能减排 多目标优化 电压质量 灰色理论 改进粒子群算法 

分 类 号：TM621.8[电气工程—电力系统及自动化] F407.61[经济管理—产业经济]