JADE平台粒子群算法在环境经济调度中的应用  

Application of Particle Swarm Optimization of JADE Platform in Environmental Economic Dispatching

作　　者：黄冕 陈智慧[2] 郭壮志[2] 

机构地区：[1]广东电网有限责任公司河源供电局,广东河源517000 [2]广东工业大学自动化学院,广东广州510006

出　　处：《广东电力》2015年第4期51-56,共6页Guangdong Electric Power

基　　金：国家自然科学基金资助项目(51307025);广东省自然科学基金资助项目(S2013040013776;S2012040007911);广东省教育厅育苗工程资助项目(2013LYM_0019)

摘　　要：在环境经济调度模型中,为同时降低火电机组的燃料成本和污染气体排放量进行多目标优化,模型引入阀点效应并考虑网损,在满足功率平衡和出力限制的前提下,采用一种基于JADE平台下的粒子群多目标优化算法对模型进行求解。算法吸收了粒子群算法的进化机制,将Pareto占优策略和拥挤距离相结合并应用在粒子群算法中,添加了动态惯性权重特性和小概率变异,提高了算法全局搜索能力。在JADE平台下搭建算法模型,并运用IEEE-30节点6机组和IEEE-118节点40机组的标准测试系统进行仿真,结果表明该算法提高了系统的计算速度,改进了算法的并行性,更适合求解大规模复杂系统。In the environmental economic dispatching model,for reducing fuel costs of the thermal power unit and emission load of polluted gas at the same time,multi-objective optimization was conducted. The model introduced valve point effect and considered transmission losses,meanwhile,on the premise of satisfying power balance and output limit,a kind of parti-cle swarm multi-objective optimization based on JADE platform was used for solving. The algorithm absorbed evolution mechanism of particle swarm optimization（PSO）,combined and applied Pareto dominant strategy and crowding distance in PSO,added dynamic inertia weight characteristic and small probability variation and improved global searching ability of the algorithm. On JADE platform,the algorithm model was set up,standard testing systems of IEEE-30 node six units and IEEE-1 1 8 node forty units were used for simulation. The results indicate that this algorithm could improve calculation speed of the system and concurrency of the algorithm which may be more suitable to solve large-scale and complicates system.

关 键 词：JADE 多 AGENT 粒子群 PARETO 环境经济调度 

分 类 号：TM855.2[电气工程—高电压与绝缘技术]