Energy optimization of water supply system scheduling: Novel MINLP model and efficient global optimization algorithm

This article is concerned with global optimization of water supply system scheduling with pump operations to minimize total energy cost. The scheduling problem is first formulated as a non‐convex mixed‐integer nonlinear programming (MINLP) problem, accounting for flow rates in pipes, operation profi...

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Veröffentlicht in:AIChE journal Jg. 62; H. 12; S. 4277 - 4296
Hauptverfasser: Shi, Hanyu, You, Fengqi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Blackwell Publishing Ltd 01.12.2016
American Institute of Chemical Engineers
Schlagworte:
Above ground tanks
Algorithms
Characteristic functions
Computational efficiency
Computer programs
Computing time
Demand
Energy
Energy conservation
Flow rates
Global optimization
Mathematical models
Nonlinear programming
Optimization
Optimization algorithms
outer-approximation
Pipe
Pipes
pump operations
Pumps
Scheduling
Software
Tanks
Valves
Water conveyance
Water distribution
Water distribution systems
Water engineering
Water levels
Water shortages
Water supply
water supply system
Water supply systems
Water tanks
ISSN:0001-1541, 1547-5905
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Zusammenfassung:This article is concerned with global optimization of water supply system scheduling with pump operations to minimize total energy cost. The scheduling problem is first formulated as a non‐convex mixed‐integer nonlinear programming (MINLP) problem, accounting for flow rates in pipes, operation profiles of pumps, water levels of tanks, and customer demand. Binary variables denote on–off switch operations for pumps and flow directions in pipes, and nonlinear terms originate from characteristic functions for pumps and hydraulic functions for pipes. The proposed MINLP model is verified with EPANET, which is a leading software package for water distribution system modeling. We further develop a novel global optimization algorithm for solving the non‐convex MINLP problem. To demonstrate the applicability of the proposed model and the efficiency of the tailored global optimization algorithm, we present results of two case studies with up to 4 tanks, 5 pumps, 5 check valves, and 21 pipes. © 2016 American Institute of Chemical Engineers AIChE J, 62: 4277–4296, 2016
Bibliographie:ArticleID:AIC15332
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SourceType-Scholarly Journals-1
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ISSN:0001-1541
1547-5905
DOI:10.1002/aic.15332