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The objective of this research study was the development of an intelligent system based on artificial neural networks for water distribution networks that operate with parallel pumps. The purpose of the system is to automate the process and to define the operating state of the electric motors (on, off or with partial rotation speed). The intelligent system developed is generic, which allows the application of its control structure in similar processes, and it was applied in an experimental setup that simulates a real water supply system. The performance of the network was tested experimentally under different operating conditions, including in the presence of disturbances. The settling time was, in all experiments, less than 30 seconds, the tests did not show overshoot and the maximum error was 2.9%. Results showed excellent performance in terms of pressure regulation, and it is hoped that the controller can be successfully implemented in real water distribution systems, in order to reduce water and electricity consumption, decrease maintenance costs and increase the reliability of operating procedures.

Rapid growth in population over last few decades has resulted in changes of supply system consumption patterns. Such, require effort from companies in technical aspects; targeting need of strategies to improve operational efficiency. Management system, based on automated control, carries a strong mechanism to gauge these results. Aim of this paper is to present a comparative study of both hydraulic and electric parameters of an experimental automated network. Network behavior was analyzed under two conditions: without use of controller and with Proportional-Integral -Derivative (PID) controller. Results indicated efficiency of applied controller in different consumption scenarios. Dealing with energy efficiency, it was verified that, according to calculations related to specific energy consumption (SEC), reduction on electrical energy is notable with use of controller.

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