TY - GEN
T1 - Tuning Improvement of Power System Stabilizer using Hybrid Harris Hawk Optimization-Equilibrium Optimizer Algorithm
AU - Prakasa, Mohamad Almas
AU - Robandi, Imam
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - A Harris Hawk Optimization (HHO) become popular in recent works to resolve various power system cases, including tuning Power System Stabilizer (PSS). However, HHO has several challenges, such as premature convergence can occur due to less diversity in solutions with an unbalanced exploration and exploitation process. Therefore, this paper proposed The Hybrid Harris Hawk Optimization-Equilibrium Optimizer Algorithm (HHHO-EOA) to enhance HHO performance and acquire better optimal tuning for PSS. The EOA is a well-balanced exploration and exploitation algorithm. A Linearized Heffron-Phillips model for Single-Machine Infinite Bus (SMIB) is modeled to evaluate the proposed algorithm in tuning PSS. Various performance indices are used as the objective functions. The HHHO-EOA has a significantly better enhancement in the convergence curve with consistent results than previous algorithms. The minimum objective function achieved by the proposed algorithm is 78.3% and 60% lower than conventional EOA and HHO. Moreover, the PSS based on the proposed algorithm is 10.24% and 19.69% better in damping the overshoot than conventional EOA and HHO in both frequency and power angle deviation responses.
AB - A Harris Hawk Optimization (HHO) become popular in recent works to resolve various power system cases, including tuning Power System Stabilizer (PSS). However, HHO has several challenges, such as premature convergence can occur due to less diversity in solutions with an unbalanced exploration and exploitation process. Therefore, this paper proposed The Hybrid Harris Hawk Optimization-Equilibrium Optimizer Algorithm (HHHO-EOA) to enhance HHO performance and acquire better optimal tuning for PSS. The EOA is a well-balanced exploration and exploitation algorithm. A Linearized Heffron-Phillips model for Single-Machine Infinite Bus (SMIB) is modeled to evaluate the proposed algorithm in tuning PSS. Various performance indices are used as the objective functions. The HHHO-EOA has a significantly better enhancement in the convergence curve with consistent results than previous algorithms. The minimum objective function achieved by the proposed algorithm is 78.3% and 60% lower than conventional EOA and HHO. Moreover, the PSS based on the proposed algorithm is 10.24% and 19.69% better in damping the overshoot than conventional EOA and HHO in both frequency and power angle deviation responses.
KW - Equilibrium Optimizer Algorithm
KW - Harris Hawk Optimization
KW - Hybrid Algorithm
KW - Power System Stabilizer
UR - http://www.scopus.com/inward/record.url?scp=85150471326&partnerID=8YFLogxK
U2 - 10.1109/ICITISEE57756.2022.10057700
DO - 10.1109/ICITISEE57756.2022.10057700
M3 - Conference contribution
AN - SCOPUS:85150471326
T3 - Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022
SP - 553
EP - 558
BT - Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022
Y2 - 13 December 2022 through 14 December 2022
ER -
