Low‐frequency oscillations are created in the power system due to the interconnection of large electric networks with weak tie‐lines, heavy power exchanges, and sudden changes in load demand and generation, which must be damped quickly for stability. The proposed work consists of a power system stabilizer (PSS) tuned by three different optimization algorithms, which are the genetic algorithm, the moth‐flame algorithm, and a novel snake optimization algorithm (SOA) with the key features of exploitation and exploration. The first main objective is to optimally tune the controlling parameters of PSS, which could attain the best quick response and develop a robust power system achieved by SOA. The second novel contribution is the development of an advanced Heffron–Phillips model (AHPM), including the dynamics of d ‐axis internal voltage. The AHPM is designed with a higher‐order Synchronous Generator Model 1.1. There are only 6 K‐constants in the traditional model, whereas in AHPM, there are 10 K‐constants to represent the system dynamics. The integration of renewables into the grid creates new challenges. This AHPM is capable of meeting these challenges due to better mathematical modeling of the system. The damping ratio is (0.9830) with SOA‐based PSS.With AHPM, there is no need for the inclusion of FACTS devices with PSS to meet the stability issues. This next‐generation AHPM is an efficient and economical model. This model is developed using MATLAB R2020a.
Agrawal et al. (Thu,) studied this question.