Application of Spider-Tailed Horned Viper Optimization for Unit Commitment Problem in Power Systems

The Unit Commitment (UC) problem is a key optimization task in power systems, aiming to schedule generation units while minimizing costs and meeting system constraints.This study applies the recently published Spider-Tailed Horned Viper Optimization (STHVO) algorithm to solve the UC problem.Inspired by the hunting behaviour of the spider-tailed horned viper, STHVO combines exploration and exploitation to balance global search and local refinement.The performance of STHVO is evaluated against twelve established metaheuristics, including GA, PSO, and GWO, showing superior results in solution quality and computational efficiency.STHVO achieves lower operational costs, faster convergence, and reduced computational effort, making it a promising solution for real-time power system operations.A mathematical model of the UC problem, a case study with system data, and detailed simulation results are provided.The comparison highlights STHVO's effectiveness in solving complex UC problems.The results indicate that STHVO is a competitive approach, but further research is needed to address uncertainties, improve scalability, and explore integration with stochastic optimization and multi-objective approaches.This work demonstrates STHVO's potential for practical deployment in power systems but suggests further development for large-scale applications.