基于混沌与量子粒子群算法相结合的负荷模型参数辨识研究

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Abstract Load modeling has become a critical problem that is urgent to be solved in power system modeling. Precise field measurement data,proper load model structure and accurate parameter identification are three key factors that can affect the results of the measurement-based load modeling. In this paper,CQDPSO algorithm,a hybrid optimization algorithm that combines chaotic optimization algorithm(COA) and quantum delta-potential-well-based particle swarm optimization(QDPSO) algorithm is proposed to identify the parameters of the selected load model. Finally,simulation results using field measurement data illustrate that the proposed method has advantages in calculation precision,convergence speed when compared with particle swarm optimization(PSO) algorithm and QDPSO algorithm. The application of CQDPSO algorithm in load model parameter identification can improve the accuracy of load models.

Key words： Chaotic optimization algorithm(COA) quantum delta-potential-well-based particle swarm optimization(QDPSO) algorithm power fault recorder parameter identification load modeling

Received: 28 May 2014 Published: 22 January 2015

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TM714

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	Articles by authors
	Wang Zhenshu
	Bian Shaorun
	Liu Xiaoyu
	Yu Kai
	Shi Yunpeng

Cite this article:

Wang Zhenshu,Bian Shaorun,Liu Xiaoyu等. Research on Load Model Parameter Identification Based on the CQDPSO Algorithm[J]. Transactions of China Electrotechnical Society, 2014, 29(12): 211-217.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2014/V29/I12/211

[1] Ma Jin,Han Dong,He Renmu,et al. Reducing identified parameters of measurement-based composite load model[J]. IEEE Transactions on Power Systems,2008,23(1): 76-83.
[2] 王振树,李林川,牛丽. 基于贝叶斯证据框架的支持向量机负荷建模[J]. 电工技术学报,2009,24(8): 127-134,140. Wang Zhenshu,Li Linchuan,Niu Li. Load modeling based on support vector machine based on Bayesian evidence framework[J]. Transactions of China Electro- technical Society,2009,24(8): 127-134,140.
[3] 汤涌,张红斌,侯俊贤,等. 负荷建模的基本原则和方法[J]. 电网技术,2007,31(4): 1-5. Tang Yong,Zhang Hongbin,Hou Junxian,et al. Study on essential principle and methods for load modeling [J]. Power System Technology,2007,31(4): 1-5.
[4] Kosterev D N,Taylor C W,Mittelstadt W A. Model validation for the August 10,1996 WSCC system outage[J]. IEEE Transactions on Power Systems,1999,14(3): 967-979.
[5] Pereira L,Kosterev D,Makin P,et al. An interim dynamic induction motor model for stability studies in the WSCC[J]. IEEE Transactions on Power System,2002,17(4): 1108-1115.
[6] Price W W,Wirgau K A,Murdoch A,et al. Load modeling for power flow and transient stability computer studies[J]. IEEE Transactions on Power Systems,1998,3(1): 180-187.
[7] Wang Zhenshu,Bian Shaorun,Liu Yan,et al. The load characteristics classification and synthesis of substations in large area power grid[J]. International Journal of Electrical Power & Energy Systems,2013,48(1): 71-82.
[8] Lin Chia-Jen,Yung-Tien Chen,Chiou C Y,et al. Dynamic load models in power systems using the measurement approach[J]. IEEE Transactions on Power Systems,1993,8(1): 309-315.
[9] Liu Zhonghui,Wang Zhenshu,Su Meihua. Dynamic load modeling based on extreme learning machine[J]. Applied Mechanics and Materials,2012(195-196): 1043-1048.
[10] 鞠平,刘伟航,项丽,等. 电力系统负荷建模的自动故障拟合法[J]. 电力系统自动化,2013,37(10): 60-64. Ju Ping,Liu Weihang,Xiang Li,et al. Automatic post-disturbance simulation based method for power system load modeling[J]. Automation of Electric Power Systems,2013,37(10): 60-64.
[11] Ping Ju,Chuan Qin,Feng Wu,et al. Load modeling for wide area power system[J]. International Journal of Electrical Power & Energy Systems,2011,33(4): 909-917.
[12] Abdelaziz A Y,Badr M A L,Younes A H. Dynamic load modeling of an Egyptian primary distribution system using neural networks[J]. International Journal of Electrical Power & Energy Systems,2007 29(9): 637-649
[13] Maitra A,Gaikwad A,Zhang P,et al. Using system disturbance measurement data to develop improved load models[C]. IEEE Power Systems Conference and Exposition,2006: 1978-1985.
[14] Ren-Feng Yuan,Qian Ai,Xing He. Research on dynamic load modelling based on power quality monitoring system[J]. IET Generation,Transmission & Distribution,2013,7(1): 46-51.
[15] 王振树,张波,李欣唐,等. 新型电力故障录波监测系统[J]. 电力系统自动化,2007,31(10): 92-96,101. Wang Zhenshu,Zhang Bo,Li Xintang et al. A novel type of power fault recording and monitoring system [J]. Automation of Electric Power Systems,2007,31(10): 92-96,101.
[16] 仲卫进,艾芊. 扩展卡尔曼滤波在动态负荷参数辨识中应用[J]. 电力自动化设备,2007,27(2): 47-50. Zhong Weijin,Ai Qian. Application of extended Kalman filter in parameter identification of dynamic load model[J]. Electric Power Automation Equipment,2007,27(2): 47-50.
[17] 艾芊,陈陈,沈善德,等. 简化前馈网络用于负荷模型参数辨识的研究[J]. 中国电机工程学报,2005,25(5): 21-27. Ai Qian,Chen Chen,Shen Shande,et al. Research on parameter identification of load models by using liner BP networks[J]. Proceedings of the CSEE,2005,25(5): 21-27.
[18] Hua Bai,Pei Zhang,Venkataramana Ajjarapu. A novel parameter identification approach via hybrid learning for aggregate load modeling[J]. IEEE Transac- tions on Power Systems,2009,24(3): 1145-1154.
[19] 程颖,鞠平,吴峰,等. 负荷模型参数辨识的粒子群优化法及其与基因算法比较[J]. 电力系统自动化,2003,27(11): 25-29. Cheng Ying,Ju Ping,Wu Feng,et al. Ps algorithm in load parameter identification and its comparison with genetic algorithm[J]. Automation of Electric Power Systems,2003,27(11): 25-29.
[20] Van den Bergh F. An analysis of particle swarm optimizers[D]. Pretoria: University of Pretoria,2001.
[21] Jun Sun,Bin Feng,Wenbo Xu. Particle swarm optimiza- tion with particles having quantum behavior[C]. Proceedings of the 2004 Congress on Evolutionary Computation,2004: 325-331.
[22] Kou Pangao,Zhou Jianzhong,Wang Changqing,et al. Parameters identification of nonlinear state space model of synchronous generator[J]. Engineering Applications of Artificial Intelligence,2011,24(7): 1227-1237.
[23] Sun Jun,Fang Wei,Wu Xiaojun,et al. Qos multicast routing using a quantum-behaved particle swarm optimization algorithm[J]. Engineering Applications of Artificial Intelligence,2011,24(1): 123-131.
[24] Omkar S N,Khandelwal R,Ananth T V S,et al. Quantum behaved particle swarm optimization(QPSO) for multi-objective design optimization of composite structures[J]. Expert Systems with Applications,2009,36(8): 11312-11322.
[25] 王爽心,姜妍,韩芳,等. 一种综合负荷模型参数辨识的混沌优化策略[J]. 中国电机工程学报,2006,26(12): 111-116. Wang Shuangxin,Jiang Yan,Han Fang,et al. A chaotic optimization strategy used in parameter iden- tification of composite load model[J]. Proceedings of the CSEE,2006,26(12): 111-116.
[26] Leandro dos Santos Coelho. Tuning of PID controller for an automatic regulator voltage system using chaotic optimization approach[J]. Chaos,Solitons and Fractals,2009,39(4): 1504-1514.
[27] 汤涌,张红斌,侯俊贤,等. 考虑配电网络的综合负荷模型[J]. 电网技术,2007,31(5): 34-38. Tang Yong,Zhang Hongbin,Hou Junxian,et al. A synthesis load model with distribution network[J]. Power System Technology,2007,31(5): 34-38.
[28] Byoung-Kon Choi,Hsiao-Dong Chiang,Yinhong Li,et al. Measurement-based dynamic load models: derivation,comparison and validation[J]. IEEE Transac- tions on Power Systems,2006,21(3): 1276-1283.