Title: A genetic optimisation model for energy conservation of circulating water pump station with variable speed pumps

Authors: Yirun He; Siqi Wu; Qianyu Cheng; Chenyu Tian; Qi Deng; Qi Kang

Addresses: School of Electronic and Information Engineering, Tongji University, Shanghai 201804, China ' School of Electronic and Information Engineering, Tongji University, Shanghai 201804, China ' Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, 99907734, Hong Kong ' School of Software, Dalian University of Technology, No. 321, Tuqiang Street, Dalian, 116620, China ' School of Electronic and Information Engineering, Tongji University, Shanghai 201804, China ' School of Electronic and Information Engineering, Tongji University, Shanghai 201804, China

Abstract: As vital energy-consuming equipment of the industrial cooling circulating water system, scientific scheduling of the circulating water pump station (CWPS) is crucial for energy conservation. In this paper, we propose a genetic optimisation model. An optimal scheduling model is established to minimise power consumption, considering the production demand and pumps' high-efficiency area constraints. Branch water pipe characteristic curves are introduced to determine the accurate pump operating condition. A multi-strategy genetic algorithm (MSGA) is proposed for the strict production demand constraints and the deficiency of complex constraint processing techniques. The MSGA screens feasible solutions by simply judging and achieves infeasible region information utilisation and search strategy adaptive adjustment by the sequence-based fitness construction, multi-mutation and adaptive control parameters strategies. The case results show that the proposed model can significantly reduce power consumption while improving pump efficiency over the original operation scheme of CWPS.

Keywords: circulating water pump station; CWPS; energy conservation; genetic optimisation; optimal scheduling; multi-strategy genetic algorithm; MSGA.

DOI: 10.1504/IJBIC.2024.141454

International Journal of Bio-Inspired Computation, 2024 Vol.24 No.2, pp.98 - 108

Received: 27 Dec 2023
Accepted: 22 Apr 2024
Published online: 13 Sep 2024 *

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