| 引用本文: | 郭艳艳,熊国江.大规模电力系统经济调度的改进竞争群优化算法[J].电力系统保护与控制,2017,45(15):97-103.[点击复制] |
| GUO Yanyan,XIONG Guojiang.Large scale power system economic dispatch based on an improved competitive swarm optimizer[J].Power System Protection and Control,2017,45(15):97-103[点击复制] |
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| 摘要: |
| 提出了一种求解大规模电力系统经济调度(Economic Dispatch, ED)问题的改进竞争群优化算法(Improved Competitive Swarm Optimizer, ICSO)。CSO算法本质上受粒子群优化PSO算法所启发，具有原理简单，容易实现，搜索能力强等特点。在分析CSO算法存在的不足的基础上，提出了相应的劣质个体改进更新策略和控制参数自适应调节策略，以更好地平衡局部搜索和全局搜索。通过4个算例从经济性、收敛性、鲁棒性等多维角度对比分析了ICSO算法的可行性和有效性。算例仿真结果表明，ICSO具有较好的优化性能，可作为大规模ED问题的可靠求解方法。 |
| 关键词: 电力系统 大规模经济调度 阀点效应 竞争群优化算法 |
| DOI：10.7667/PSPC161194 |
| 投稿时间：2016-08-01修订日期：2016-10-07 |
| 基金项目:湖北省教育科学规划2015年度立项课题(2015B257) |
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| Large scale power system economic dispatch based on an improved competitive swarm optimizer |
| GUO Yanyan,XIONG Guojiang |
| (Technology Institute of Locomotive Vehicle, Wuhan Railway Vocational College of Technology, Wuhan 430205, China;Guizhou Electric Power Grid Dispatching and Control Center, Guiyang 550002, China) |
| Abstract: |
| An improved competitive swarm optimizer (ICSO) is proposed for large scale power system economic dispatch. The CSO is fundamentally inspired by the particle swarm optimization (PSO). It is with advantages of simple principle, easy implementation, and strong search ability. Based on the analysis of the disadvantages of the CSO, an improved loser updating strategy and an adaptive adjusting strategy of control parameter are proposed to balance the local and the global researching abilities. Four cases are employed to comparatively demonstrate the ICSO’s viability and effectiveness from different perspectives of economy, convergence, and robustness. Simulation results indicate that the ICSO is with better performance and can be used as a reliable method for large-scale ED. |
| Key words: power system large scale economic dispatch valve-point effect competitive swarm optimizer |
