Skip to Main Content
A non-revisiting genetic algorithm (NrGA) was used to determine distribution network configuration for loss reduction. By advocating binary space partitioning (BSP) to divide the search space and employing a novel BSP tree archive to store all the solutions that have been explored before, NrGA can quickly check for revisits by communicating with BSP tree archive when a new solution is generated by genetic algorithm (GA), and can mutate an alternative unvisited solution through a novel adaptive mutation mechanism that based on BSP tree while a revisit has occurred, which achieves no duplicates in the entire search. A method for getting independent loops of distribution network was realized using breadth-first search algorithm. Furthermore, the extended intermediate crossover mode, which requires no tuning parameter such as crossover rate and extends the crossover results, is employed for improving the performance of NrGA in solving distribution network configuration problem. The proposed approach has been successfully tested on three sample systems and three practical systems. Numerical studies have revealed its accuracy and efficient performance.