Stability improvement of the Southern Sulawesi system using the Hippopotamus Optimization Algorithm (HOA)

Abstract

This study proposes a Multi Band Power System Stabilizer (MB-PSS) optimized with the Hippopotamus Optimization Algorithm (HOA) to enhance dynamic stability in the Southern Sulawesi (Sulbagsel) electricity system integrated with wind power plants (WPPs). Unlike previous works applying HOA to distribution networks or photovoltaic optimization, this study addresses a key gap: the absence of HOA based stabilizer optimization in large scale multi machine systems, particularly in Sulbagsel. The novelty lies in positioning HOA as an alternative swarm intelligence method suited to the nonlinear characteristics of MB-PSS tuning. While the claim of being the first HOA application in Sulbagsel requires stronger justification, this study extends its relevance by bridging overlaps in related domains. Damping analysis and time domain simulations are conducted to benchmark HOA against Grey Wolf Optimization (GWO) and Whale Optimization Algorithm (WOA). Results show that HOA achieves superior performance: overshoot in generator speed deviation decreases to 0.009923 to 0.002359 p.u., settling time reduces from 16s without stabilizer to 9.58s, and the maximum damping ratio increases to 0.7185. These outcomes confirm HOA’s capability to improve oscillation damping, though additional reporting of frequency responses and voltage stability metrics would strengthen the empirical contribution. Theoretically, this study highlights HOA’s balance between exploration and exploitation, making it suitable for multimodal cost functions in stabilizer tuning. However, broader theoretical implications, such as HOA’s advancement of stability theory beyond empirical results, remain underexplored. Future research should address this dimension to consolidate HOA’s role in advanced power system stability studies.