A graph theory application for fast and efficient search of optimal radialized distribution network topology

Abstract

The topological changes and re-configuration can be brought into an existing power network by operation of sectionalizing switches on the feeder lines. Distribution networks can be operated either in meshed or in radial configuration. While primary meshed distribution networks have advantages like lower short circuit current, reduced overall conductor length and increased reliability and fault tolerance, the radial networks on the other hand stand-out on their merits of simple installation and easier relay coordination. An optimal radial network can operate at higher efficiency owing to its reduced power losses and can offer higher voltage stability. Transformation of a primary meshed network to a radially reconfigured optimal network requires selection of the “best” set of switches on the feeders that are to be opened or closed so that each feeder can be operated close to its maximum loadability limit and the resulting optimal network operates at its lowest feasible value of power loss and highest voltage stability index. This theoretical concept of optimal power network radialization is however difficult to implement in practice due to the heavy computational burden and unacceptably long searching time as the number of feasible alternative configurations is usually massive for large power networks. Given the extent of the search space, the heuristic search approaches are usually more practical and common in power network reconfiguration. This paper presents a novel guided search approach based on Edmond’s Maximal Spanning Tree Algorithm to achieve the optimal radial configuration for an arbitrary power network rapidly and efficiently. Efficacy of the proposed method has been tested on 30-node and 57-node mesh distribution networks with encouraging results.