A Novel Approach to Optimal Allocation of SVC using Genetic Algorithms and Continuation Power Flow

摘要

This paper proposed a new approach to determine optimal location of SVC to improve voltage profile and maximizing system loadability with and without generators Mvar limits. A variable reactance model for SVC at steady state studies are presented and implemented in load flow program with embedded FACTS Devices. A simultaneous GA and CPF used to determine maximum number of SVC and steady state stability margin, based on closing to point of voltage collapse. As an important result in this paper we obtained a maximum number of SVC beyond which system loadability can not be increase and hence increasing loading level leads to static voltage collapse phenomena. A case study and simulation are done on IEEE57 Bus Test System. In Genetic Algorithm optimization procedure the system loadability and bus voltage profile flattening are used as measuring of power system performance Index.