Identification of Optimal Path in Power System Network Using Bellman Ford Algorithm

Power system network can undergo outages during which there may be a partial or total blackout in the system. In that condition, transmission of power through the optimal path is an important problem in the process of reconfiguration of power system components. For a given set of generation, load pair, there could be many possible paths to transmit the power. The optimal path needs to consider the shortest path (minimum losses), capacity of the transmission line, voltage stability, priority of loads, and power balance between the generation and demand. In this paper, the Bellman Ford Algorithm (BFA) is applied to find out the optimal path and also the several alternative paths by considering all the constraints. In order to demonstrate the capability of BFA, it has been applied to a practical 230？kV network. This restorative path search guidance tool is quite efficient in finding the optimal and also the alternate paths for transmitting the power from a generating station to demand. 1. Introduction Whenever power interruption takes place it is imperative to bring back the system promptly to its initial state or to an optimal operating network. The problem of obtaining a target network is called power system restoration. It consists of two steps, the first step is to determine an optimal configuration and the second step is to prepare a sequence of switching operations (restoration plan) in order to bring the faulted network into the obtained target system. Power system restoration is a multiobjective, multivariable, multiconstraint, and mixed optimization problem. It is very difficult to establish mathematical models. The most relevant literatures pertaining to power restorations are discussed. Barsali et al. reported the main results of a comprehensive survey on behalf of an independent system operator [1]. The main strategies, critical issues, and practical experiences related to the restoration plans of a wide set of deregulated systems worldwide are presented. Further, the paper proposes possible innovative enhancements being studied for the intricate sample system, aimed at increasing the effectiveness of the restoration service. Naggar et al. implemented a relatively new RECRé software program (French acronym for “Remise En Charge du Réseau”-System Restoration) by Hydro-Québec in 2005 [2]. The aim of this knowledge management system is to have system restoration knowledge that is tangible, growth-oriented, and enhanceable asset. The system is made up of two modules: the knowledge engineering module, whereby modeling can be done of the system