Evaluation of static characteristic coefficients basing on field test data

Anastasia Kovaleva, A. Tavlintsev, E. Lyukhanov, S. Gusev, I. Zicmane, L. Petrichenko
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Abstract

It is known that composition and behavior of an electrical load are constantly changing over time, therefore, to model and analyze the modes of power systems, it is necessary to update load models. This article proposes a method for processing the data of passive measurements to obtain static characteristic coefficients of loads. The developed algorithm includes the following subtasks: selection of initial data; determination of an acceptable modeling interval; clustering and filtering of measurement data; selection and statistical evaluation of the load static characteristic. This algorithm was applied to estimate coefficients of linearized static characteristic model of a real load node based on the field measurements and showed results close to the previously obtained experimental estimates for this type of load. This indicates the applicability of the proposed method for assessing the static characteristic coefficients of various load nodes.
基于现场试验数据的静特性系数评估
众所周知,电力负荷的组成和行为是随时间不断变化的,因此,为了建模和分析电力系统的模式,有必要更新负荷模型。本文提出了一种处理被动测量数据以获得载荷静态特征系数的方法。所开发的算法包括以下子任务:初始数据的选择;确定可接受的建模区间;测量数据的聚类与过滤;负载静态特性的选择与统计评价。将该算法应用于基于现场实测的实际负载节点线性化静态特性模型系数估计,结果与该类型负载的实验估计值接近。这表明所提出的方法适用于评估各荷载节点的静态特征系数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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