Lógica fuzzy para avaliação de eficiência energética em sistemas de irrigação de lavouras de arroz

Abstract

Energy efficiency plays an important role in electric power systems, since a small percentage increment in efficiency may lead to significant financial and energy savings. In agricultural-based economy countries, large areas of irrigation represent a meaningful parcel in electrical energy consumption. These installations are generally not automated and the pumps operate continuously regardless of rainfall and other factors that could allow their shutdown. Other aspects usually detected in rice farms are precarious facilities, water leaks, outdated equipment and wrongly dimensioned or reconditioned electric motors. All these elements contribute to the electrical efficiency reduction on this kind of installation and represent an extra cost of the crop cultivation. Furthermore, in Brazil, government regulations impose power utilities to invest 0.5% of their net earnings in end users’ efficiency projects. The main objective of this work is to create a tool to evaluate electrical energy efficiency of irrigated rice crops, establishing an index of efficiency and an estimative of possible energy savings that supports the power utilities to prioritize the allocation of energy efficiency resources on this kind of consumers and also that helps the rural producers to avoid extra electricity costs and reduce water consumption. The proposed methodology is developed through a rule-based Fuzzy algorithm that translates the opinion of specialists at meteorology, soil and rice cultivation. The algorithm considers a wide number of variables, including farm characteristics, meteorological data, and operation conditions of the irrigation system. In addition, the proposed tool is capable of identify possible situations of non-technical losses occurrence. The validation of the proposed methodology was accomplished using fifteen real datasets from irrigated rice crops from Rio Grande do Sul State. Results demonstrated the tool’s proper operation, indicating four cases with index of great inefficiency, along with possible energy savings between 33% and 42%, and five cases with flag of non-technical losses possibility.