Eficiência energética por meio de um controlador PI autossintonizado por lógica fuzzy em sistema de distribuição de água de um setor da grande Curitiba

Abstract

This dissertation presents an application of artificial intelligence, the fuzzy logic, structured as a fuzzy controller, for the tuning of the Kp and Ki gains of a PI controller. The latter, configured in a frequency converter for the operation of a motor-pump assembly of the drinking water supply system in the region called Recalque Mercês (RMER), in the city of Curitiba, comprising 4 districts with 140 km of pipeline and more than 13 thousand connections to customers. Today, the system operates with PI traditional control with fixed gains, varying the speed of the motor-pump assembly, controlled by a pressure sensor downstream to the pumping. However, the variation in the consumption of potable water supplied is very large during the period of one day, being maximum at dusk and minimum during the dawn, and with seasonal characteristics, consumption increases with heat and decreases in the cold, which makes static control inefficient at certain times. The proposal is to adopt the fuzzy control to change the coefficients of the PI controller throughout the day, autonomously, according to the instantaneous consumption and thus achieve a better energy efficiency of the system, appreciating the quality of service provided to the population. That is, ensuring the flow and pressure of water to the consumer. Through MatLab®, simulation tools, Simulink® and SimScape®, two models were created, one with the current control and the other with the intelligent proposal. An abbreviation of the network and the existing pumping system of the lift, the reduction of 4 engine-pump assemblies to only 1 (one) and a single path, making 5.4 km distance, to the socalled critical point location, where it is further, higher and more difficult to keep the pressure at the 10 mwg (1 bar), as a rule. The developed fuzzy controller has 2 inputs, the reservoir level and the downstream pressure of the motor-pump assembly, and 2 outputs, proportional and integral gains for the PI. With the rulesbased framework, 123 inference rules were created for the system to perform favorably. The simulations were carried out with the reference of data – 3 months of historical – of measurements of the reservoir and pressure sensor that is the feedback of the existing PI control. Thus, the energy efficiency of 6.15% per month, in terms of electric power consumed, was achieved, compared to the traditional control model.