Fast Optimal Network Reconfiguration with Guided Initialization Based on a Simplified Network Approach

• Main Authors: Mansor, N.N (Author), Mohamad, H. (Author), Mokhlis, H. (Author), Samman, M.A (Author), Sapari, N.M (Author), Suyono, H. (Author)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc., 2020
• Subjects: Bioluminescence; Conventional methods; Distribution system; Distribution systems; Electrical distribution networks; firefly algorithm; Firefly algorithms; Heuristic algorithms; Heuristic methods; Meta-heuristic techniques; network reconfiguration; Network re-configuration; Optimal network reconfiguration; Optimal systems; Optimization; Two stage optimizations
• Online Access: View Fulltext in Publisher; View in Scopus
• ISBN: 21693536 (ISSN)
• ISSN: 21693536 (ISSN)
• DOI: 10.1109/ACCESS.2020.2964848

Optimal Network Reconfiguration (NR) is a well-accepted approach to minimize power loss and enhance voltage profile in the Electrical Distribution Networks (EDN). Since the NR problem contains huge combinational search space, most researchers consider the meta-heuristic techniques to attain NR solution. However, these meta-heuristic techniques do not guarantee to obtain the optimal solution besides they require large processing time to converge. This is mainly due to (1) random initialization and updating of population and (2) the continuous verification of population during the search process. With the aim of reducing the computational time and improving the consistency in obtaining the optimal solution as well as minimizing power loss and enhancing the voltage profile of the EDN, this work proposes a new method based on two-stage optimizations. The proposed method introduces an approach to simplify the network into simplified network graph. Then, this approach is utilized for guided initializations and generations of the population and for the proper population's codification. The proposed method is implemented using the firefly algorithm and verified on 33-bus and 118-bus test systems. The results show the ability of the proposed method to obtain the optimal solution within fast computational time and with superior consistency compared to the conventional methods. © 2013 IEEE.