Investigations on multi-objective optimization based optimal power dispatch problem with facts devices using foraging algorithms

Abstract

The demand for electrical power has grown rapidly in recent years due to the increase in population and growth of industries. The electric utilities are called to serve more power through their networks for maintaining the optimal and secure operations of the power system. Conventionally, the optimal operation of the power system networks is based on the cost minimization and is called as Optimal Power Flow problem. In order to improve the performance of the power system, the Optimal Power Dispatch (OPD) is formulated for planning the power systems requirements. This thesis mainly focuses on the solution of the OPD problem to enrich the quality of power to the end users, with economic facets and various major factors of power system like reduction in system loss, enhancing the voltage stability and minimizing the cost of generation. The expansion of the power transmission networks is limited due to environmental right-of-way and economic reasons. Subsequently, there is a need for alternatives for stable operation and better exploitation of the existing power system facilities. The Flexible AC Transmission System (FACTS) devices have gained interest in enhancing the power transfer capability and power support, when it is connected in an optimal manner. reactive power is essential for maintaining voltage stability. The voltage constraint at the network restricts active power delivery to the loads and results in forced load restriction. The present research investigates critical operation of power system for better real and reactive power dispatch, and for improving the voltage stability by using reliability analysis. The reliability analyses are Fast Line Flow Index (FLFI), Voltage Stability Approach (VSA) and Q-V Analysis. Due to the strict regulations on environmental protection, the conventional operation at minimum fuel cost cannot be the only basis for dispatching electric power. The present research aims at simultaneously optimizing the various objectives of the OPD problem.