Fault recovery of distribution network containing distributed generation based on heuristic search algorithm and multi-population genetic algorithm

• Published in: Systems science & control engineering Vol. 6; no. 3; pp. 100 - 108
• Main Authors: Xu, Zhe, Zhang, Zhijing, Jiang, Wen, Fan, Shuxian, Gong, Maofa
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 21.09.2018; Taylor & Francis Group
• Subjects: Distributed generation; fault recovery of distribution network; load shedding; multi-population genetic algorithm; the method of improved branch exchange
• ISSN: 2164-2583; 2164-2583
• DOI: 10.1080/21642583.2018.1531793

In order to solve low optimization efficiency and 'premature convergence' of the traditional genetic algorithm in fault recovery of the distribution network with DG, a new recovery scheme based on the heuristic algorithm and multi-population genetic algorithm is proposed. During the initial process, the heuristic algorithm is used to obtain certain individuals who are close to the local optimized solutions, so that it can search in the better individuals. And then, the multi-population genetic algorithm is introduced to achieve co-evolution among various groups, which takes into account the balance between the global and local searching abilities. Due to existing large number of infeasible solutions that do not satisfy the radial requirements in the searching process, topology simplification is performed to improve the searching speed and computational efficiency. Before the failure recovery, this paper determines whether to put into load shedding by using the repeated power flow method. Finally, the feasibility and validity of the optimization algorithm are demonstrated by case studies in the paper.