Dynamic synergy optimization (DSO): An integrated approach of metaheuristic algorithms and PID control for real-time stability enhancement in refrigeration systems

Abstract

With increasing global energy demand, improving the efficiency of refrigeration systems and reducing their environmental impact is crucial, especially since refrigeration often accounts for a significant portion of energy consumption. Traditional Proportional-Integral-Derivative (PID) control methods struggle with the complex, nonlinear nature of refrigeration systems, resulting in slow response times and limited optimization capabilities. While metaheuristic algorithms can perform global searches, they often lack the real-time fine-tuning necessary for optimal dynamic control. This study introduces Dynamic Synergy Optimization (DSO), a novel framework that integrates metaheuristic algorithms with PID control. Unlike conventional methods that only turn PID parameters using metaheuristics, DSO combines the global optimization power of metaheuristics with the real-time adjustment capabilities of PID, providing effective global search and local refinement. The PID controller ensures quick adaptation and system stability. Experimental results show that the Harris Hawks Optimization algorithm integrated with PID control outperforms standard PID control with a 63.3 % reduction in response time, a 69.2 % decrease in stabilization time, and a 19.65 % enhancement in energy efficiency. The DSO strategy significantly enhances the dynamic response and stability of refrigeration systems, reduces hysteresis, and accelerates the attainment of steady-state operation.