NDLI: Optimal pump operation for water distribution systems using a new multi-agent Particle Swarm Optimization technique with EPANET

Content Provider	IEEE Xplore Digital Library
Author	Al-Ani, D. Habibi, S.
Copyright Year	2012
Description	Author affiliation: Mech. Eng. Dept., McMaster Univ., Hamilton, ON, Canada (Al-Ani, D.; Habibi, S.)
Abstract	The optimal pump scheduling allows for computing the most economical energy costs and provides more efficient operations for complex water distribution systems (WDS) with multiple pumping stations. The proposed technique employs the latest advances in multi-agent Particle Swarm Optimization (MOPSO) to automatically determine the most cost-effective solutions for scheduling/operation multiple pumps in multiple pumping stations, while satisfying both loading conditions and hydraulic performance requirements. The present work considers a bi-objective pump-scheduling problem, where the objectives are: minimize the electrical energy cost ($/KW.h) and minimize the maintenance costs in terms of the total number of pump switches. In additional to the bi-objective pump-operational problem, pressure and tank levels (i.e., initial, minimum, and maximum) are considered as constraints in this paper for computing the most cost-effective solutions. The constraint-handling method, the Modified MOPSO (M-MOPSO) algorithm, and the modified EPANET Toolkit 2.0 are used to solve the constrained multi-objective problem. The results showed that the new MOPSO algorithm produced the most economical pump scheduling solutions.
Sponsorship	IEEE Montreal Sect.
Starting Page	1
Ending Page	6
File Size	1314848
Page Count	6
File Format	PDF
ISBN	9781467314312
ISSN	08407789
e-ISBN	9781467314336
e-ISBN	9781467314329
DOI	10.1109/CCECE.2012.6335031
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-04-29
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optimization Algorithm design and analysis Water resources Particle swarm optimization Job shop scheduling Genetic algorithms Electricity water distribution systems multi-agent optimization parallel computing pump scheduling
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Hardware and Architecture

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