共 31 条
Grey Wolf Optimizer for Optimal Distribution Network Reconfiguration
被引:0
作者:
Souifi, Haifa
[1
]
Hadj Abdallah, Hsan
[2
]
机构:
[1] ClairiTech Innovat, Dept Engn, R&D, Boudreau Ouest, NB, Canada
[2] Natl Sch Engineers Sfax, Elect Dept, Sfax, Tunisia
来源:
2022 IEEE ELECTRICAL POWER AND ENERGY CONFERENCE (EPEC)
|
2022年
关键词:
Distribution Network Reconfiguration;
Grey Wolf Optimizer;
Power losses;
Backward/Forward algorithm;
Metaheuristic methods;
Union-Find with Path Compression method;
DISTRIBUTION-SYSTEMS;
ALGORITHM;
RELIABILITY;
SEARCH;
FLOW;
D O I:
10.1109/EPEC56903.2022.10000166
中图分类号:
TE [石油、天然气工业];
TK [能源与动力工程];
学科分类号:
0807 ;
0820 ;
摘要:
The distribution network reconfiguration (DNR) has recently been brought to light as one of the most attractive strategies to enhance the performances of distribution systems. In this respect, this paper focuses on solving the DNR problem using a GWO (Grey Wolf Optimizer) algorithm. The proposed method was applied in an IEEE 69-bus test system to reduce its active power losses while satisfying the buses voltages, branches currents and radial topology constraints as well. To thoroughly assess the total active power losses of the distribution system, the Backward/Forward approach was developed in this study. Furthermore, the union-find with path compression technique was used to check the radiality constraint. So as to reveal its efficiency and suitability in solving the DNR issue and reaching the optimal solution, the proposed GWO algorithm was compared to the GA (Genetic Algorithm) and CF-PSO (Constriction Factor-Particle Swarm Optimization) as well. Moreover, it was validated against several techniques developed in recent literature. The research results disclosed that after performing reconfiguration, a significant reduction of total power losses evaluated at 56.17% was obtained and the voltage profile was generally improved.
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页码:405 / 411
页数:7
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