This paper presents a Black Hole Optimization algorithm (BHO) featuring an adaptive event horizon mechanism for solving the unit commitment (UC) problem in electrical power systems. The proposed approach tackles the fundamental challenge of determining cost-optimal startup and shutdown schedules for generating units while minimizing total operational expenses and ensuring compliance with complex operational and system constraints. The enhanced BHO algorithm incorporates key modifications for power system optimization, including adaptive exploration-exploitation balance, merit order-based movement strategies, strategic star generation for base and peak loads, specialized local search techniques, and comprehensive constraint handling for operational requirements. Systematic constraint handling mechanisms ensure complete satisfaction of minimum up/down time constraints and operational limitations. Algorithm validation is performed on a standard 10 -unit benchmark system over a $\mathbf{2 4}$ -hour planning period, with comprehensive statistical analysis across multiple execution runs establishing its robustness and performance repeatability.