含双馈异步风电机组的配电网无功优化
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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.
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.
引文
[1]赵晶晶,符杨,李东东.考虑双馈电机风电场无功调节能力的配电网无功优化[J].电力系统自动化,2011,35(11):33-38.
[2]李闯,陈民铀,付昂,等.含风电场的配电网无功优化策略研究[J].电力系统保护与控制,2013,41(9):100-105.
[3]张丽,徐玉琴,王增平,等.包含分布式电源的配电网无功优化[J].电工技术学报,2011,26(3):168-174.
[4]李鑫滨,马阳,鹿鹭.一种基于校正因子的自适应简化粒子群优化算法[J].燕山大学学报,2013,37(5):453-458.
[5]吴璇,王建.基于多目标混沌粒子群算法的矿区电网无功优化[J].低压电器,2011(20):40-42.
[6]雷敏,杨万里,彭晓波,等.基于改进简化粒子群算法的含DG的配电网无功优化[J].华北电力大学学报,2015,42(1):39-44.
[7]杨洪,陆金桂.基于遗传算法和粒子群算法优化算法的电力系统无功优化[J].南京工业大学学报,2007,29(5):58-61.
[8]余健明,刘飞.基于禁忌搜索算法的含风电机组的配电网无功优化研究[J].西安理工大学学报,2013,29(1):70-75.
[9]何属清,鹏建春,毛丽林,等.含多个风电机组的配电网无功优化[J].电力系统自动化,2010,34(19):37-41.
[10]李鑫滨,朱庆军,马红霞,等.粒子群算法及其在电力系统无功优化中的应用[J].燕山大学学报,2008,32(3):245-250.
[11]唐贤伦,张衡,周家林,等.多Agent结构的混沌PSO在无功优化中的应用[J].电机与控制学报,2013,17(6):15-21.
[12]赵志刚,常成.自适应混沌粒子群优化算法[J].计算机工程,2011,37(15):128-130.
[13]Shan Cheng,Min Youchen.Multi-objective reactive power optimization strategy for distribution system with penetration of distributed generation[J].International Journal of Electrical Power and Energy Systems,2014,62:221-228.
[14]张永勤.双馈感应电机风电场并网后的配电网无功优化算法[J].自动化应用,2013,24(7):74-76.
[2]李闯,陈民铀,付昂,等.含风电场的配电网无功优化策略研究[J].电力系统保护与控制,2013,41(9):100-105.
[3]张丽,徐玉琴,王增平,等.包含分布式电源的配电网无功优化[J].电工技术学报,2011,26(3):168-174.
[4]李鑫滨,马阳,鹿鹭.一种基于校正因子的自适应简化粒子群优化算法[J].燕山大学学报,2013,37(5):453-458.
[5]吴璇,王建.基于多目标混沌粒子群算法的矿区电网无功优化[J].低压电器,2011(20):40-42.
[6]雷敏,杨万里,彭晓波,等.基于改进简化粒子群算法的含DG的配电网无功优化[J].华北电力大学学报,2015,42(1):39-44.
[7]杨洪,陆金桂.基于遗传算法和粒子群算法优化算法的电力系统无功优化[J].南京工业大学学报,2007,29(5):58-61.
[8]余健明,刘飞.基于禁忌搜索算法的含风电机组的配电网无功优化研究[J].西安理工大学学报,2013,29(1):70-75.
[9]何属清,鹏建春,毛丽林,等.含多个风电机组的配电网无功优化[J].电力系统自动化,2010,34(19):37-41.
[10]李鑫滨,朱庆军,马红霞,等.粒子群算法及其在电力系统无功优化中的应用[J].燕山大学学报,2008,32(3):245-250.
[11]唐贤伦,张衡,周家林,等.多Agent结构的混沌PSO在无功优化中的应用[J].电机与控制学报,2013,17(6):15-21.
[12]赵志刚,常成.自适应混沌粒子群优化算法[J].计算机工程,2011,37(15):128-130.
[13]Shan Cheng,Min Youchen.Multi-objective reactive power optimization strategy for distribution system with penetration of distributed generation[J].International Journal of Electrical Power and Energy Systems,2014,62:221-228.
[14]张永勤.双馈感应电机风电场并网后的配电网无功优化算法[J].自动化应用,2013,24(7):74-76.