Making a Smart Pressure Reducing Valve for Reducing Pressure Fluctuation Caused by Water Hammer in Water Distribution Network Using Input-Output Feedback Linearization

Document Type : Research Paper


1 MSc. Student of Water Resources Management, Dept. of Civil Engineering, Faculty of Engineering, University of Birjand, Birjand, Iran

2 Assist. Prof., Dept. of Civil Engineering, Faculty of Engineering, University of Birjand, Birjand, Iran

3 Assist. Prof., Dept. of Power Engineering, Faculty of Electrical Engineering and Computer, University of Birjand, Birjand, Iran

4 Postdoctoral., Dept. of Civil Engineering, Faculty of Engineering, University of British Columbia, Vancouver, Canada


Using pressure reducing valves to reduce the pressure in water distribution systems to the minimum of required value is one of the most effective ways for leakage reduction. Valve opening/closing, switching a pump on/off and water consumption fluctuation by a large consumer cause transient flows. Interference between transient flow and a PRV with constant needle-valve setting may intensify pressure waves in WDS. Applying smart PRVs can limitpressure fluctuation. In this research, Input-output feedback linearization method has been used for smart PRV control. The results of this method have been compared with PRV with CNVS and proportional-integral-derivative controller. A theoretical network taken from references was used to evaluate the proposed methods. Network demands include normal consumers and an industrial large consumer. Water hammer caused by consumption variations, PRV with CNVS operation, IOFL method and PID controllers were modeled in Simulink. PRV outlet head fluctuation in PRV with CNVS is 18 to 28 m in PID controller and in IOFL method are 26 to 28 m. Also, the results showed that the IOFL method has smoother and less fluctuation than PID. Root-mean-square error for PRV outlet head in CNVS, PID controller and IOFL is 1.6, 0.32 and 0.28, respectively. Therefore, IOFL method has less error and better performance than PID. Also, this method has simpler computational operations by converting nonlinear system equations to linear equations.


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