Memetic SSA tuned fractional PSS for low frequency power system oscillations. Issue 5 (4th July 2022)

• Record Type: Journal Article
• Authors: Satapathy, Samarjeet; Nahak, Narayan; Parida, Jyotiranjan
• Is Part Of: Journal of information & optimization sciences. Volume 43:Issue 5(2022)
• Page Start: 973
• Page End: 982
• Publication Date: 2022-07-04
• Subjects: 37N35; Memetic salp swarm algorithm -- Salp swarm algorithm -- Power system stabilizer -- Damping controller -- Power system oscillations; Electronic data processing -- Periodicals; Information science -- Periodicals; Mathematical optimization -- Periodicals; 519.6
• DOI: 10.1080/02522667.2022.2101213
• Languages: English
• ISSNs: 0252-2667

Abstract

Abstract: Memetic salp swarm algorithm (MSSA) is proposed in the present work to optimally set the gains of fractional power system stabilizer (FPSS) for damping angular speed variation in power system. The optimization is based on the objective of minimizing variation in rotor angular frequency subject to disturbance which is change in reference voltage applied to generator. A single generator system connected with infinite bus has been experimented in this work for sudden and random variations in reference voltage applied to generator. The power system stabilizer (PSS) is based on fractional lead-lag control actions and MSSA is employed to tune the controller gains. Eigen values are analyzed with proposed control and MSSA has been compared with PSO (Particle swarm optimization) and salp swarm algorithm (SSA). It is observed from system response that MSSA can effectively tune the PSS parameters for oscillation damping subject to critical disturbances like random reference voltage variations.