Investigating Economic Emission Dispatch Problem Using Improved Particle Swarm Optimization Technique

Lecture notes in networks and systems(2017)

引用 5|浏览0
暂无评分
摘要
This paper presents utilization of particle swarm optimization in solving combined economic emission dispatch (EED) problem. The economic emission dispatch is an important problem in power sector as it combines two major objectives viz., cost minimization and emission minimization while maintaining operational constraints. Several meta-heuristic techniques have been developed in recent times and have been applied on power dispatch problems. PSO is such a meta-heuristic technique where time-varying acceleration coefficients (TVAC) are incorporated and used in the EED problem in this work. Thus it addresses the techno-economic-environmental aspect of power system operation. Economic emission dispatch problem is first resolved using weighted sum method, and second trade-off curve between two objectives has been found, referred to as pareto front which traces solutions obtained by non-dominated approach of the problem. The formulation is implemented on IEEE 30 bus test system and outcome obtained validates effectiveness of this research work.
更多
查看译文
关键词
Economic emission dispatch, Time-varying acceleration coefficients incorporated particle swarm optimization (TVAC-PSO), Meta-heuristic techniques, Non-dominated solutions
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要