Data-driven approach for real-time distribution network reconfiguration

Finding a global optimal solution to the distribution network reconfiguration (DNR) problem in a short time is a challenging task. This study proposes a real-time online data-driven DNR (3DNR) method. Power loss minimisation, lowest bus voltage maximisation and reliability maximisation are taken as objectives. First, in this study, a methodology combining heuristic algorithm and metaheuristic algorithm to solve DNR is proposed. Then a set of data that satisfies the data drive model requirements is obtained. Next, the improved convolution neural network is used to train the data set of DNR. Unlike the state-of-art methods, the proposed 3DNR can realise the real-time online reconfiguration without power flow calculation. The feasibility and effectiveness of the proposed method are demonstrated on IEEE-34, IEEE-123, and a practical distribution system in Taiwan.

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