Genetic optimization toward operation of water intake-supply pump stations system. (10th January 2021) - Chen, Wanpeng; Tao, Tao; Zhou, Aijiao; Zhang, Lu; Liao, Lei; Wu, Xumeng; Yang, Kai; Li, Chenxiu; Zhang, Tian C.; Li, Zhi
Abstract: The water intake and water supply pump stations consume a large amount of energy every year, and their energy efficiency improvement has a significant impact on the operations of the water industry. In this study, a general model for simplifying a simulated two-stage system (i.e., water intake and water supply pumping stations) was established. Optimization strategies were developed based on a dynamic-level-feedback-control approach. Non-dominated sorted genetic algorithm-II (NSGA-II) was used to solve the multi-objective optimization problem. Both cost-driven and energy-driven optimizations were proposed from the perspective of reliability, economy, and durability of pumping station operation. Results show that, compared to the extant strategy currently used, the cost- and energy-driven optimization strategies developed in this study can reduce operating energy costs of the system by 7.0% and 6.2%, and have satisfactory stability under the condition of uncertain water demand. Cost-driven optimization improves the power demand response of the two-stage system by increasing the load transfer in peak periods. Energy-driven optimization reduces carbon dioxide emissions by reducing the total operational energy consumption of the system. Highlights: A general model of the water intake-supply pump stations is constructed. Pump switching on/off number and time interval are synthetically considered for the operational durability. Dynamic-level-feedback-control approach helps to ensure the operational reliability of the two-stage system. Load transfer and energy consumption are conducive to enhancing system operational energy efficiency.