Optimal Power Flow Based on Grey Wolf Optimizer: Case Study Iraqi Super Grid High Voltage 400 kV

Abstract

This paper deals with solving optimal power flow problems using one of the new meta-heuristic optimizations inspired by the behavior of grey wolves (Canis lupus). Optimal power flow (OPF) faced several challenged such as increased of fuel cost of generation units, increased the real power losses at transmission lines, increased of voltage deviation of each bus, and uncontrolled of voltage stability for whole system. Therefore, in this paper, the objective functions that have been optimized include generation cost (GC), power loss (PL), voltage deviation (VD), and voltage stability index (VSI). The GWO algorithm has been applied on the Iraqi Super Grid High Voltage 400 kV (ISGHV 400 kV) to set the optimal control variables. The results obtained by this algorithm have been compared with the results obtained by the initial study case to determine the percentage of reduction rate. This comparison proved the efficiency and superiority of the GWO algorithm when applied to the power system networks. The percentages of reduction rates compared with the initial case are 45.08%, 27.28%, 70.64%, and 15.40% of generation cost (GC), power loss (PL), voltage deviation (VD), and voltage stability index (VSI), respectively.