Title: Optimising pump system with constant and variable speed pumps: case study

Authors: Haien Fang, Wenyan Wu, Mou Lv, Jinliang Gao

Addresses: School of Municipal and Environment Engineering, Harbin Institute of Technology, P.O. box 2624, Harbin, Heilongjiang, 150090, China. ' Faculty of Computing, Engineering and Technology, Staffordshire University, Beaconside Stafford, ST18 0DF, UK. ' School of Civil and Environmental Engineering, Qingdao Technological University, Qingdao 266033, China. ' School of Municipal and Environment Engineering, Harbin Institute of Technology, P.O. box 2624, Harbin, Heilongjiang, 150090, China

Abstract: Optimising pump scheduling is a complex problem, which involves a large space search, continuous and discrete variables, physical and operational constraints and also multi-objectives. In this paper, multi-objective evolutionary algorithms (MOEAs) combined with a repair mechanism are used to solve the optimal operation problem within water supply system. In this work two objectives are minimised: operation cost (energy cost + treatment cost) and maintenance cost, while one objective is maximised: service level of hydraulic. Decision variables are the settings of the pumps and speed ratio of variable-speed pumps at a time step of the total operational time horizon. A mixed coding methodology and a new crossover operator are developed according to the characteristics of decision variables. Three well-known MOEAS (NSGA-II, epsilon-MOEA and SPEA2) are implemented and compared. Practical application of this method shows that it can make efficient decision to support the operators.

Keywords: water supply networks; pump systems; multiobjective evolutionary algorithms; MOEA; mixed coding; repair mechanism; constant speed pumps; variable speed pumps; pump scheduling; operating costs; energy costs; treatment costs; maintenance costs; hydraulic service levels; optimisation.

DOI: 10.1504/IJMIC.2011.040084

International Journal of Modelling, Identification and Control, 2011 Vol.12 No.4, pp.412 - 420

Published online: 21 Mar 2015 *

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