Review of Optimization Techniques for Power Network Reconfiguration

While electricity is being transmitted from electricity generation stations to the customers, there are power losses in between the transmission lines, which influences the electricity quality and the performance of the distribution network. Power network reconfiguration techniques have been used to decrease power energy losses in transmission lines and to improve the voltage profile in one-of-a-kind nodes of the electric system. There is quantity of optimization algorithms which have been evolved and proposed as tools to look at the performance of a reconfigured electrical distribution network. The aim of this analysis paper is to conduct associate degree investigation, in the form of a comparative analysis, of the different optimization methods, such as the Artificial Intelligence (AI) algorithms that includes Artificial Neutral Networks (ANN), Fuzzy Logic Algorithm (FLA), Genetics Algorithm (GA) and Particle Swarm Optimization (PSO) Algorithm. The hybrid bio-inspired algorithm is also reviewed; which is the combination of the genetics algorithm and Particle Swarm Optimization (HGAPSO). Really, most of the electrical distribution networks are reconfigured radially and thus modification of the radial shape of the distribution feeders is accomplished with the aid of converting the open/closed states of the isolator s in order that the load may be transferred from one feeder to another.