Optimal power flow for large-scale power system with shunt FACTS using fast parallel GA

Abstract

The main disadvantage of GAs is the high CPU time execution and the quality of the solution deteriorate with practical large-scale optimal power flow (OPF) problems. This paper presents an efficient parallel GA (EPGA) combined with fuzzy practical rules for the solution of the large-scale OPF. The length of the original chromosome is reduced successively based on the decomposition level and adapted with the topology of the new partition. Partial decomposed active power demand added as a new variable and searched within the active power generation variables of the new decomposed chromosome. In the second step a simple fuzzy rules designed based in practical expertise rules to control the reactive power of a multi dynamic shunt FACTS Compensators (SVC) to improve the system performances. Numerical results on two test systems IEEE 30-bus and IEEE 118-bus are presented and compared with results of others competitive global approach. The results show that the approach proposed can converge to optimum solution faster than other methods, and obtains the solution with high accuracy.