Optimal Tuning for Power System Stabilizer using Arithmetic Optimizer Algorithm in Interconnected Two-Area Power System

Abstract

Metaheuristic algorithms have been executed to facilitate optimal tuning in modern power systems, including Power System Stabilizers (PSS). Recent-novel metaheuristic algorithms have unique and advanced exploration and exploitation processes, therefore it is expected to improve the optimal tuning approaches. This paper investigated the popular recent-novel metaheuristic algorithm, Arithmetic Optimizer Algorithm (AOA), in optimal tuning for the PSS2A-IEEE model in two-area interconnected power systems. AOA comes with simple and familiar operators and concepts alongside the trend of the recent-novel algorithm with the complex operator. AOA is compared with Harris Hawk Optimizer (HHO) and Equilibrium Optimizer (EO) to find the best optimal tuning for PSS. The algorithms are investigated in 30 runs within 100 iterations. Statistical assessments show that AOA can compete with HHO and EO in finding the minimum error based on overall performance indices. The convergence curve analysis shows that AOA has the best characteristics. The PSS2A-IEEE based on AOA can enhance the small-signal stability of two-area interconnected power systems with 37% to 38% overshoot reduction and 38% to 49% settling time reduction.