摘要
针对双馈异步风电机组的出力具有随机性这一特点,采用场景分析法对其出力进行分析,使其更有代表性;在此基础上,建立了以电压偏差最小和有功功率损耗最小的多目标无功优化模型;针对粒子群算法存在易早熟的问题,提出了一种自适应混沌粒子群算法(ACPSO),并将其作为无功优化的算法;利用该算法对含双馈异步风电机组的IEEE33系统进行无功优化计算,并将优化后的结果与其它文献提出的算法相比较,验证了所提算法的有效性。
In order to solve the problem that the output of the doubly fed induction generator is stochastic, the method of scene analysis is used to analyze its output, which makes it more representative. Based on the above, a multi-objective reactive power optimization model with minimum voltage deviation and minimum active power loss is established. Aiming at the problem that the PSO algorithm is easy to be premature,an adaptive chaos particle swarm optimization（ ACPSO） algorithm is proposed, which is used as a reactive power optimization algorithm. Using this algorithm, the reactive power optimization of the IEEE33 system with doubly fed induction generator is calculated,and the optimized results are compared with other algorithms,the effectiveness of the proposed algorithm is verified.
出处
《燕山大学学报》
CAS
北大核心
2015年第5期438-442,共5页
Journal of Yanshan University
关键词
配电网
双馈异步风电机组
无功优化
自适应混沌粒子群算法
场景分析法
distribution network
doubly fed induction wind turbine
reactive power optimization
adaptive chaotic particle swarm optimization algorithm
scene analysis method
