Parameter Optimization of Measurement-Based Load Model Based on Bootstrap
Han Dong1, Ma Jin2, He Renmu2
1. Institute of Electrical Engineering, Chinese Academy of Sciences Beijing 100190 China 2. Key Laboratory of Power System Protection and Dynamic Security Monitoring and Control of Ministry of Education North China Electric Power University Beijing 102206 China
Abstract:Load model is one of the most important elements in power system simulation and control. This paper proposes a new strategy to choose the parameters of load models based on the Bootstrap. Firstly, the optimization methods are used to identify the parameters through single field-measured curve. And then statistical distribution of each parameter is estimated by the Bootstrap. Finally, the value of each parameter is chosen according to its statistical characteristics. Since the Bootstrap estimates the approximate distribution of unknown parameter by converting the small-sample problem into the large-sample issue, the proposed strategy can make full use of the measured data and objectively estimate the statistical characteristics under small samples space. The case study verifies the validation of the proposed strategy, and it is shown that the load model established by the proposed strategy have good capability on describing the load dynamics.
韩冬, 马进, 贺仁睦. 基于Bootstrap的实测负荷模型参数优选[J]. 电工技术学报, 2012, 27(8): 141-146.
Han Dong, Ma Jin, He Renmu. Parameter Optimization of Measurement-Based Load Model Based on Bootstrap. Transactions of China Electrotechnical Society, 2012, 27(8): 141-146.
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