Abstract:
In the context of the current energy crisis, electricity consumption, especially by large consumers, must be reduced, rationally, without affecting the quality of services provided. Pressure pumping stations (PPS) in irrigation systems are usually equipped with 4 to 8 electric pumping sets with an installed power that can even exceed 1 MW. Since the PPS serving the irrigation plots must work mainly on demand, the required flow rate in the network can vary widely even during each day of the irrigation period. Also, due to the dependence of the pressure loss on the flow carried in the pipe network, this dependence is usually represented by an increasing quadratic function, and the variation of the required flow also leads to a variation, generally significant, of the pressure required from the PPS. To ensure the necessary flow, the PPS are automated with Supervisory control and data acquisition (SCADA) systems, which optimally control the configuration of the electric pumps in operation and their speed. This article presents a mathematical model and algorithm that facilitate the determination of the correlation between the pressure and flow required from the PPS ((p-Q)c), rendered by an increasing function. The implementation of (p-Q)c in the SCADA system software at PPS 2 in the Trifești-Sculeni irrigation system, in the eastern part of Romania, determined a reduction of energy consumption by up to 16%.
