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Comparison of the fuzzy regression analysis and the least squares regression method to the electrical load estimation

机译:模糊回归分析与最小二乘回归法在电力负荷估算中的比较

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An essential point in correct calculations and analysis of power distribution systems is a proper evaluation of loads. The acquisition of this data is complex because of a large number of nodes and their area distribution. As a rule receiving nodes are not equipped with stationary measuring instruments so measurements of loads are performed only sporadically. The theory which enables efficient description of unreliable and inaccurate data, and relationship between them, is the fuzzy set theory. The paper presents possibilities of application of the fuzzy set theory to power distribution system calculations. Unreliable and inaccurate input data were modeling by means of fuzzy numbers. A regression model, expressing the correlation between a substation peak load and a set of customer features (explanatory variables), existing in the substation population, is determined. The fuzzy set approach and standard regression method are compared.
机译:正确计算和分析配电系统的关键是正确评估负载。由于大量节点及其区域分布,因此获取此数据非常复杂。通常,接收节点未配备固定的测量仪器,因此负载的测量仅偶尔执行。模糊集理论是使不可靠和不准确的数据以及它们之间的关系的有效描述的理论。本文提出了将模糊集理论应用于配电系统计算的可能性。通过模糊数字对不可靠和不准确的输入数据进行建模。确定一个回归模型,该模型表示变电站高峰负荷与一组存在于变电站总体中的客户特征(解释变量)之间的相关性。比较了模糊集方法和标准回归方法。

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