Load Identification Modeling with Improved Model Structure

Abstract:

The running state of different induction motor in the load group will be moved toward two directions when it was occurred the large disturbance in the power system, one is to keep on running, another is out of step or stall. If the quantity of stall induction motor in the group is a large number, the dynamic of stall motors will effect on the stability of power system obviously. So it is necessary to develop the detailed load model to simulate the complicated dynamic characteristic of the load group. An improved synthesis load model which combines two kinds of induction motor is proposed, and the improved genetic algorithm is used to identify the parameter of load model. The case is studied to illustrate the effective and comprehensive adaptability of the proposed identification model.

• Periodical: Applied Mechanics and Materials (Volume 740)
• Pages: 368-372
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.740.368
• Online since: March 2015
• Authors: Shu Jun Liu*, Ping Liu
• Keywords: Genetic Algorithm (GA), Load Modeling, Motor Group, Parameter Identification

References

[1] Kosterev D N, Taylor C W, Mittelstadt W A. Model validation for the August 10, 1996 WSCC system outage[J]. IEEE Trans on power Systems, 1999, 14(3): 967-979.

DOI: 10.1109/59.780909

[2] Pereira L, Kosterev D, Mackin P, et al, An interim dynamic induction motor model for stability studies in the WSCC[J], IEEE Trans on power Systems, 2002, 17(4): 1108-1115.

DOI: 10.1109/tpwrs.2002.804960

[3] He Renmu, Ma Jin, Composite load modeling via measurement approach, IEEE Transactions on power systems, 2006, 21(2): 663-671.

DOI: 10.1109/tpwrs.2006.873130

[4] TangYong, Hou Junxian, Liu Wenzhuo. The modeling of distribution network and var compensator and induction motor in the load model for power system digital simulation[J]. Proceeding of the CSEE, 2005. 25(3): 8-12.

[5] Zhang Hongbin, Tang Yong, Zhang Dongxia, et al. Analysis on Effects of Different Load Model on Transmitting Capacty of Northeast China Power Grid. Power System Technology. 2007, 31(4): 55-58.

[6] Tang Yong, Zhang Dongxia, Zhang Hongbin, et al. Synthesis Load Model and its Fitting Parameters in Simulation of Large Disturbance Test Carried Out in Northeast China Power Grid. Power System Technology. 2007, 31(4): 75-78.

[7] Zhao Bing, Tang Yong, Zhang Wenchao, et al. Validation of Synthesis Load Model and Its Parameter Modification Based on Post-Disturbance Simulation Method. Power System Technology. 2010, 34(1): 45-50.

[8] Zheng Jinghong, Zhu Shouzhen, Slip Coherency Based Approach for Air Conditioning Load Modeling[J], Automation of Electric Power Sytems, 2008, 32(16): 11-15.

[9] Hua Bai, Pei Zhang, A Novel parameter idengtification approach via hybrid learning for aggregate load modeling, IEEE Transactions on power systems, 2009, 24(3): 1145-1154.

DOI: 10.1109/tpwrs.2009.2022984

[10] Zhou Ming. Sun Shudong. Genetic Algorithms: Theory and Applications[M]. National Defence and Industrial publishing. (1999).

[11] ZHAO Bing, TANG Yong, ZHANG Wen-chao, et al. Determination of Induction Motor Simulation Model Parameters Based on the Motor Manufacture Data[J]. Proceedings of the CSEE. 2010, 30(1): 52-58.