Corrective action planning considering FACTS allocation and optimal load shedding using bacterial foraging oriented by particle swarm optimization algorithm

摘要

Reactive power planning (RPP) involves optimal allocationand determination of the type and size of new reactive power (VAR)supplies to satisfy voltage constraints during normal and contingencystates. The RPP issue is in fact an optimization of large scale mixedinteger nonlinear programming problem, so it is proper to use anevolutionary algorithm to solve the problem. In this paper, in orderto solve the RPP problem for corrective action of power systems, thebacterial foraging (BF) oriented by particle swarm optimization (PSO)algorithm (BF-PSO) is proposed. In the algorithm, the VAR control hasbeen carried out by using flexible AC transmission systems (FACTS)devices, in order to minimize the installation costs of these devices.In order to determine the saving rate in the costs, corrective controlis also performed by the utilization of load shedding algorithm. TheIEEE 57-Bus system is used to test the proposed method. Thesimulation results of the proposed algorithm are compared with PSO andgenetic algorithms (GA) to show the efficiency of this method in theRPP problem.