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Optimizing Pump Operations in Water Supply Networks Through Genetic Algorithms
Author(s) -
Mambretti Stefano,
Orsi Enrico
Publication year - 2016
Publication title -
journal ‐ american water works association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.466
H-Index - 74
eISSN - 1551-8833
pISSN - 0003-150X
DOI - 10.5942/jawwa.2016.108.0025
Subject(s) - water supply , computer science , genetic algorithm , scheduling (production processes) , water supply network , energy consumption , software , reliability engineering , mathematical optimization , engineering , mathematics , electrical engineering , machine learning , environmental engineering , programming language
Proper scheduling of pump operations (i.e., the specific combinations of pumps and operating parameters to meet system requirements) can yield substantial savings in energy costs for water supply systems. In recent decades, optimization procedures have been developed to solve this complex and multiobjective problem. In the current research, a genetic algorithm method was selected to optimize pump operations to reduce energy consumption while maintaining good service. The method was then applied to the water supply network of Milan, Italy, a large, complex system in which hydraulic head is maintained by the action of pumping stations. On the basis of real data and following field testing, the operations of the network and its pumping stations were first simulated with specially developed software that uses the EPANET Toolkit and then optimized with the proposed method. When checked against real data, simulation results indicated that application of the optimization procedures could produce significant improvement and cost savings.