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Optimizing the Operation of the Haifa-A Water System

By E. Salomons, A. Goryashko, U. Shamir, Z. Rao and S. Alvisi

Abstract

Haifa-A is the first of two case studies relating to the POWADIMA research project. It comprises about 20% of the city’s water-distribution network and serves a population of some 60,000 from two sources. The hydraulic simulation model of the network has 126 pipes, 112 nodes, 9 storage tanks, 1 operating valve and 17 pumps in 5 discrete pumping stations. The complex energy tariff structure changes with hours of the day and days of the year. For a dynamically rolling operational horizon of 24 h ahead, the real-time, near-optimal control strategy is calculated by a software package that combines a genetic algorithm (GA) optimizer with an artificial neural network (ANN) predictor, the latter having replaced a conventional hydraulic simulation model to achieve the computational efficiency required for real-time use. This paper describes the Haifa-A hydraulic network, the ANN predictor, the GA optimizer and the demand- forecasting model that were used. Thereafter, it presents and analyses the results obtained for a full (simulated) year of operation in which an energy cost saving of some 25% was achieved in comparison to the corresponding cost of current practice. Conclusions are drawn regarding the achievement of aims and future prospects

Topics: artificial neural network, genetic algorithm, optimal-control, POWADIMA, water distribution
Year: 2007
DOI identifier: 10.2166/hydro.2006.017
OAI identifier: oai:iris.unife.it:11392/519401
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