粒子群优化算法在电力系统中的应用

粒子群优化方法是一种基于群体智能的新型演化计算技术.它在函数优化、神经网络设计、分类、模式识别、信号处理、机器人技术等许多领域已取得了成功应用,但在电力系统中应用的研究起步较晚,关于它实际应用的报道尚不多见.文章较为全面地详述了粒子群优化方法在配电网扩展规划、检修计划、机组组合、负荷经济分配、最优潮流计算与无功优化控制、谐波分析与电容器配置、配电网状态估计、参数辨识、优化设计等方面应用的主要研究成果.随着粒子群优化理论研究的深入,它还将在电力市场竞价交易、投标策略以及电力市场仿真等领域发挥巨大的应用潜力.

A SURVEY ON APPLICATION OF PARTICLE SWARM OPTIMIZATION TO ELECTRIC POWER SYSTEMS

Particle swarm optimization (PSO) based on swarm intelligence is a new evolutionary computational tool and is successfully applied in function optimization, neural network design, classification, pattern recognition, signal processing and robot technology and so on, but the reports on its practical applications in power system are seldom seen. Here, the main research results of applying PSO in following aspects relevant to power system, such as distribution system expansion planning, generator maintenance scheduling, unit commitment, load economic dispatch, optimal power flow calculation and optimal control of reactive power, harmonic analysis and capacitor configuration, distribution state estimation, parameter identification and optimal design, are overall presented in detail. Along with the thorough study of PSO, its great latent capacity will be brought into play in the electricity market auction, bidding strategy and electricity market simulation.