Research on optimal allocation of flow and head in cascade pumping stations based on Harris hawks optimization

Author:

Hou Xiaopeng1,Zhang Leike1,Liu Xiaolian1,Wang Xueni12,Tian Yu3,Deng Xianyu4,Ye Chen5

Affiliation:

1. a College of Water Resource Science and Engineering, Taiyuan University of Technology, Taiyuan 030024, China

2. b Henan Key Laboratory of Water Resources Conservation and Intensive Utilization in the Yellow River Basin, North China University of Water Resources and Electric Power, Zhengzhou 450046, China

3. c State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China

4. d China Water Northeastern Investigation, Design and Research Co., Ltd, Changchun 130021, China

5. e College of Harbour and Coastal Engineer, JiMei University, Xiamen 361000, China

Abstract

Abstract To address the problems of massive energy consumption and low operating efficiency in cascade pumping stations (CPSs), an optimized scheduling model for CPSs with water flow and head constraints was constructed in this study. The Harris hawks optimization (HHO) algorithm was employed to solve this model owing to its excellent performance in the field of engineering majorization. Based on this model, an optimal scheduling method for CPSs was proposed and applied to the three-stage pumping station system. The results demonstrate that the optimization schemes based on the HHO algorithm can improve the operational efficiency and annual cost savings under three different pumping flow conditions by 0.16, 0.55, and 0.56%, reducing the annual operating cost by ¥22,703, ¥74,581, and ¥75,356, respectively, relative to the currently used schemes. These results are better than those obtained by the particle swarm optimization (PSO) algorithm and genetic algorithm (GA). Furthermore, in terms of computational time, the optimization method with the HHO algorithm can show an improvement of 8.94–29.74% compared with those of PSO and GA, verifying the feasibility and efficiency of the HHO algorithm in the optimal scheduling for CPSs. Therefore, the proposed method is effective at solving the scheduling problem of CPSs.

Funder

the Basic Research Programs of Shanxi Province

the National Key R&D Program of China

the Open Research Fund of Henan Key Laboratory of Water Resources Conservation and Intensive Utilization in the Yellow River Basin

the National Natural Science Foundation of China - Youth Program

the National Natural Science Foundation of China

Publisher

IWA Publishing

Subject

Water Science and Technology

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