Intelligent Control and Efficiency Improvement Methods for Parallel Pumping Systems

Annotation: This research presents an intelligent control algorithm to improve the energy efficiency of parallel centrifugal pumping systems, widely used in industrial and municipal applications. Parallel pumping systems are vital for handling variable flow demands and ensuring operational reliability. However, conventional control methods often lead to energy inefficiencies due to suboptimal operation and static control mechanisms. The study begins by modeling the dynamics of parallel pumping systems, considering parameters such as flow rate, head, and energy consumption. Using pump performance curves and affinity laws, the proposed control algorithm dynamically adjusts pump operations based on real-time demand, ensuring optimal energy efficiency. Unlike traditional methods, the algorithm eliminates the need for startup measurements and integrates adaptive staging and de-staging techniques. Experimental results show that the intelligent control algorithm improves energy efficiency by 15% compared to traditional methods. The methodology includes simulation and experimental validation. MATLAB/Simulink simulations verify the algorithm's effectiveness under varying operational conditions, while a prototype system with DSP-based VFD controllers demonstrates its practical applicability. The results indicate significant energy savings, enhanced operational stability, and reduced wear and tear compared to conventional methods. The proposed approach offers scalability and adaptability, making it suitable for diverse applications such as power generation, wastewater treatment, and industrial processes. This work contributes to the development of sustainable and energy-efficient solutions for industrial systems.