实测类噪声数据辨识所得负荷模型参数的时变性和分布性研究
Research on the Time-varying and the Distributed Characteristics of Load Model Parameters Identified with Field Ambient Signals
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摘要: 基于类噪声数据的负荷模型参数辨识方法克服了传统总体测辨法对故障扰动数据的依赖,为跟踪电力负荷的时变性和分布性提供了科学的思路和有效的解决方案,在此基础上,针对电力系统实际量测数据,开展负荷模型参数辨识,进而对辨识参数的时变性和分布性进行分析具有重要的意义。首先,不同站点在不同时间辨识所得模型参数存在一定的差异,由此体现了电力负荷的时变性和分布性,进而采用不同站点在不同时间辨识所得参数进行仿真,所得仿真曲线与实际量测数据的对比表明在全网范围内实时获取负荷模型参数的重要性。Abstract: Different from traditional measurement based load modeling approaches, the parameter identification method of load model based on ambient signal gets rid of the dependence on fault disturbance data so that it offers an effective idea to track the time-varying and the distributed characteristics of power loads. On this basis, load model parameter identification is conducted with field measurement data and this is of great significance for the analysis of the time-varying and the distributed characteristics of the identified load model parameters. To begin with, the parameters identified during different times for different substations are different, which validates the time-varying and the distributed characteristics of power loads. Then, the results of comparison between the simulation curves obtained with different load model parameters and the field measurements indicate that it is important to frequently conduct load model parameter identification for all substations.
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