Service restoration strategy of a distribution network based on heuristic rules and the AHP-CRITIC algorithm
DOI:10.19783/j.cnki.pspc.191024
Key Words:distribution network  fault recovery  distributed generation  heuristic rules  improved AHP method  CRITIC
Author NameAffiliationE-mail
TANG Min’an School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China tangminan@mail.lzjtu.cn 
ZHANG Kaiyue School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China 290062535@qq.com 
XU Xiyuan School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China 2908949918@qq.com 
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Abstract:The self-healing control of the intelligent distribution network is of vital importance for improving the reliability of an electric power system. For distribution network fault recovery with distributed generation, a fault recovery strategy for a distribution network based on heuristic rules and the AHP-CRITIC algorithm is proposed. First, all distributed generators with black-start capability in the blackout area are traversed by a breadth-first search method to form islands and restore power supply. Secondly, by use of heuristic rules in the residual power-loss area, a candidate service restoration scheme set is generated. Thirdly, for service restoration, five evaluation indices such as the proportion of load restoration, switching times of circuit breakers, voltage drop, the margin of load capacity and the quantities of transferred load are introduced. Then the evaluation indices of candidate schemes are calculated, and these schemes are assessed by improved AHP and CRITIC methods. By introducing the idea of comprehensive weight, the deviation between each scheme and the ideal point is calculated to establish the optimal fault recovery scheme for restoring the power supply in the residual power-loss area. Calculation results of a distribution network with five feeders show that the proposed method is effective. This work is supported by National Natural Science Foundation of China (No. 61663021, No. 61763025, and No. 61861025).
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