Optimized control, and experimental validation of a novel multi-stage parabolic trough collector for solar water...

This study presents the development, optimized PID control, and experimental validation of a novel Multi-Stage Parabolic Trough Collector (MPTC) for solar water heating systems, aiming to enhance thermal efficiency and adaptability under varying environmental conditions. The research is structured into three key stages. First, a time-dependent mathematical model is developed to characterize the thermal and dynamic behavior of the system, incorporating essential parameters such as heat absorption, fluid dynamics, and energy losses. Second, a proportional-integral-derivative (PID) controller is designed and optimized using advanced techniques, including Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to ensure robust system stability and dynamic responsiveness. GA and PSO are selected over classical methods (e.g., Ziegler-Nichols) due to their superior ability to handle non-linearities, multi-objective trade-offs, and real-world disturbances typical of solar thermal systems. Lastly, a prototype MPTC featuring a modular, high-efficiency absorber design, is fabricated and experimentally tested under both controlled and real-outdoor conditions. Experimental results demonstrated a steady-state temperature error of 1.111% under dynamic irradiance conditions, confirming the model's accuracy. These results are compared with simulation outputs to validate the model and fine-tune the control strategies. The present model achieves a thermal efficiency of 16.2%, which exceeds that of comparable models reported in the literature. This integrated approach bridges theoretical modeling with experimental validation, offering a practical and scalable framework for enhancing the performance of adaptive solar thermal systems.