New encoding based on the minimum spanning tree for distribution feeder reconfiguration using a genetic algorithm

Abstract

Power distribution networks are typically structured in a radial topology with extra tie switches to allow for a manual reconfiguration in case of unexpected failure or scheduled maintenance. With the implementation of the smart grid, it is now realistic to also consider the power demand fluctuation and have real-time reconfiguration of the network to always operate in the optimal topology, minimizing distribution losses. In this paper, we propose the use of a genetic algorithm to find the optimal configuration of the network. The algorithm uses a unique solution encoding based on branch weights and computes the minimum spanning tree to decode the candidate solutions. This novel encoding ensures that the radial topology of the network is maintained without the need for complex operators resulting in an efficient and powerful solver. Finally, the solver is tested on distribution networks ranging from 16 to 4400 buses. The quality of the final solutions is equal or better, the maximum network size considered is much larger and the execution time is significantly shorter than that of state-of-the-art methods.