Optimizing steam condenser efficiency: integrating logarithmic spiral search and greedy selection mechanisms in gazelle optimizer for PI controller tuning

Abstract

Steam condensers are critical for maintaining efficiency and stability in thermal power plants by converting exhaust steam back into water. Controlling the pressure within the condenser is essential for optimal performance and operational safety. This paper presents a dynamic model of a steam condenser, with pressure control achieved through a proportional-integral (PI) controller. The PI controller parameters are optimized using the gazelle optimization algorithm (GOA), which is applied for the first time to this system in the literature. Additionally, novel enhancements, the logarithmic spiral (Ls) search with greedy selection, are integrated into GOA to further enhance control effectiveness. The performance of the optimized PI controller is evaluated using nonlinear simulations, which include statistical analysis and fitness function assessments. To validate the effectiveness of the proposed approach, comparisons are made with other widely used optimization techniques. The results reveal that the GOA notably enhances control accuracy and stability, with the enhanced GOA (Ls-GOA) achieving the most significant improvements. This underscores its potential for enhancing steam condenser efficiency in thermal power plants.