Control constraint‐based optimal PID‐PSS design for a widespread operating power system using SAR algorithm

Abstract

Nowaday's tuning of a power system stabilizer (PSS) over widespread operating conditions to safeguard the power system stability is a challenging task to power engineers. Therefore, there is a need to develop a robust and reliable PSS to produce clean and sustainable energy for power generation. In this research work, a control constraint-based optimal proportional, integral, and derivative (PID)-PSS using nature-inspired search optimization technique called search-and-rescue algorithm (SAR) is developed to suppress the low-frequency oscillations (LFOs) in a power system operating in a wide range of operational states. The wide variations in the system operating conditions are captured by the coefficients of interval polynomial and then simple inequality conditions are attained to assure the power system stability. Furthermore, a multi-objective function (MOF) is formulated to enhance the operation of the proposed PID-PSS for a widespread operating state and also to encounter practical working conditions. A human search-based optimization algorithm, that is, SAR, is implemented to acquire the PID-PSS gains. The design resilience of the proposed PID-PSS is investigated using two test cases of a one-machine infinite-bus (OMIB) power system operating at a widespread and also verified for static and dynamic mechanical disturbances. The simulation results show that the proposed optimal PID-PSS controller outperforms the most prominent controllers in the recent literature.