An Early Warning Method of Distribution System Fault Risk Based on Data Mining

<table class="table-group" id="tab1"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td class="align_left">Category</td><td class="align_center">Data sources</td><td class="align_center">Specific information</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left">Fault data</td><td class="align_center">95598 customer service system, marketing business management system and distribution automation system</td><td class="align_center">Power outage time, power outage frequency, name of feeder, substation of power outage feeder, number of affected households, feeder construction mode, power supply area classification</td></tr><tr><td class="align_left">Meteorological information</td><td class="align_center">China meteorological network</td><td class="align_center">Rainfall, minimum temperature, maximum temperature, average temperature, humidity, wind speed, wind level, visibility, cloud cover, snowfall, thunderstorm day</td></tr><tr><td class="align_left">Operation data</td><td class="align_center">Electricity information collection system</td><td class="align_center">Distribution transformer capacity, real-time load</td></tr><tr><td class="align_left">Parameter data</td><td class="align_center">Geographical information system and distribution production management system</td><td class="align_center">The total length of the feeder, the length of the overhead section, the length of the cable, the operation time, and the substation</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Related data of distribution system fault warning.</div>

Mathematical Problems in Engineering

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Table 1

Table 1: An Early Warning Method of Distribution System Fault Risk Based on Data Mining 