Method for selecting typical load characteristic transformer substation based on multi-source data
A technology of load characteristics and multi-source data, applied in genetic models, electrical digital data processing, genetic rules, etc., can solve problems such as random errors, large differences in load characteristics, and large load peak-to-valley differences
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[0161] The typical load site selection method provided by the present invention comprises the following steps:
[0162] 1. Carry out a general survey of load characteristics for all 220kV substations in Jiangxi Power Grid. This load characteristic survey collected 160 sets of valid data;
[0163] 2. Classify substations according to load composition;
[0164] The fuzzy C-means clustering was improved by the genetic simulated annealing algorithm, and the load composition was selected as the feature vector, and the 160 substations were divided into 9 categories. The cluster centers of each category are shown in Table 1 below;
[0165] Table 1 Detailed list of cluster centers
[0166]
[0167] According to the query clustering center and substation membership matrix, substations are grouped according to the principle of maximum subordination, and the grouping results of substations are shown in Table 2 below;
[0168] Table 2 Grouping of substations
[0169]
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