Application of Genetic Algorithms and Hybrid Fuzzy-Genetic Algorithm for Optimal Control of LTC and Shunt Capacitor on Unbalanced Distribution System

Abstract

The unbalanced conditions are taken into account in the Volt/VAr control of distribution system. The aim of the control is to simultaneously minimize energy loss and improve voltage profile. The optimization may be achieved by optimal dispatch of Load Tap Changer (LTC) and shunt capacitors considering system unbalanced. A Genetic Algorithm (GA) is developed to determine the load curve division useful for effective LTC scheduling and switching constraint satisfaction. GA is also appointed for the dispatch due to the ability of simultaneously scheduling the devices and checking the fulfillment of switching constraints prior to performing calculations. The algorithm is further enhanced by including fuzzy approach into the existing GA procedure. For power flow analyses under unbalanced conditions, Forward/Backward Propagation Algorithm is developed. The optimization is implemented on the IEEE 34-bus unbalanced distribution system. The advantages of fuzzy inclusion are highlighted. The main contribution is inclusion of unbalanced system conditions into the optimal dispatch problem.