Further Research on Load Modeling and Parameter Identification based on Online Measured Data

Yuan Yao, Qian Ai, Xing He, Da Xie, Zheng Yan, and Chuanwen Jiang


asymmetric disturbance, parameter identification, improved immune algorithm, fault recurrence, stability analysis


In this paper, load modeling using asymmetric disturbance data has been proposed and the load model is practically simplified, meanwhile, an improved immune algorithm, namely B-cell group evolvement based immune algorithm(BGEIA), is used in load modeling to improve the operation speed and the reliability of parameter convergence. The proposed method is applied firstly in Guangdong power grid, Southern China. And the feasibility is verified by the results of the mentioned project above. Furthermore, this paper verified the accuracy of the model by means of fault recurrence. Finally, composite load model and original ZIP load model are compared in the stability analysis on section of Guangdong power grid, and the influence and mechanism to the section stability under composite load model are studied in aspects of power-angle, frequency, voltage and power. These positive results can provide the accurate instruction to grid operators.

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