New approach for optimal UPFC placement using hybrid immune algorithm in electric power systems

Abstract

The unified power flow controller (UPFC) is one of the most promising flexible AC transmission systems (FACTS) devices for the load flow control. Simultaneous optimization of location and parameters for UPFCs is an important issue when a given number of UPFCs is applied to the power system with the purpose of increasing system loadability. This paper presents the application of hybrid immune algorithm (HIA) such as immune genetic algorithm (IGA) and immune particle swarm algorithm (IPSO) to find optimal location of UPFC to achieve optimal power flow (OPF). The overall cost function, the objective function in the OPF, includes the total active and reactive production cost function of the generators and installation cost of UPFCs and hence, should be minimized. The OPF constraints are generators, transmission lines and UPFCs limits. In power system, it may not always be possible to dispatch the contracted power transactions completely due to congestion of the corresponding transmission corridors. In this study simulations were performed on IEEE 14-bus and IEEE 30-bus test systems for different methods. Under all equality and inequality constraints, the HIA proposed approach minimized the objective function better than other methods such as GA, PSO, and IA; and as far as HIA methods were concerned, the IPSO algorithm gave better minimum cost than IGA method. Results of simulations are encouraging and could efficiently be employed for power system operations.