Kazak Dzmitry, ZHAO Feng
(School of Automation & Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China)
Abstract： The validity of electric power system simulation or prediction models depends on static load model. Measurement-based approach is the unique method to identify them adequately. The measured power depends on both load reaction to supply voltage alteration and random process of load alteration. Basically, there is no any universal method that can single out the inherent static load model from experimental data. The paper offers a proprietary technique which is the particular solution of the task. The technique considers the selection of neighboring measurement pairs with the supply voltage altering significantly between them, the exclusion of selected pairs by load power factor and subsequent selection of the inherent static load model presented as the polynomial load model. The usage of the technique to identify static load model at “Fenster” industrial enterprise (in Borisov city) is presented. The ideas considered in the paper can be used for future development of static load model identification methods with the data obtained during both active experiment and in other operating models of electric power systems.
Key words： static load model； electric power system； load power factor； step-down transformer substation
CLD number： TM744 Document code： A
Article ID： 1674-8042（2016）03-0214-07 doi： 10.3969/j.issn.1674-8042.2016.03.002
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基于测量的电力系统静态负荷模型辨识方法
翰 林， 赵 峰
（兰州交通大学 自动化与电气工程学院， 甘肃 兰州 730070）
摘 要: 电力系统仿真和预测模型的有效性依赖于静态负载模型， 而基于测量数据研究的方法是确定该模型是否合适的唯一方法。 由于测量的功率值大小取决于响应电压波动的负荷变化或随机因素， 一般来说， 没有一种通用的方法能从任何实验数据中分析出来其固有的静态负载模型。 针对这一情况， 本文提出针对某些特定问题的技术， 该技术考虑了电源电压变化对所选测量区域及其邻域的显著影响， 然后基于负载功率因数的判断来选择恰当的固有静态负载模型作为多项式负载模型， 最后采用位于鲍里索夫市的芬斯特工业有限公司的算例来验证该技术在静态负载模型辩识中的效果。 结果表明， 本文的技术可有效促进未来含有电力系统内各电力设备实时数据的情况下静态负荷模识方法的发展。
关键词: 静态负载模型； 电力系统； 负荷功率因数； 降压变电站
引用格式： Kazak Dzmitry, ZHAO Feng. Measurement-based approach for identification of static load model of electric power system. Journal of Measurement Science and Instrumentation, 2016, 7(3)： 214-220. ［doi： 10.3969／j.issn.1674-8042.2016.03.002］
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