Monitoramento ambiental e operacional de plantas fotovoltaicas em solo e flutuante com sistemas IoT utilizando comunicação LoRa

Abstract

The advancement of renewable energy sources, especially solar energy, requires precise and accessible monitoring systems capable of ensuring the efficient operation of photovoltaic (PV) plants. In this context, this dissertation presents the implementation and validation of a Photovoltaic Monitoring System (PMS) applied to ground-mounted and floating photovoltaic

(FPV) plants, conceived as a complete, accessible, and modular solution based on open, well- documented technologies widely used in the IoT development community. The proposed

architecture integrates minute-level data acquisition, point-to-point LoRa communication, cloud synchronization through the ThingSpeak platform, and a web system with a MySQL database for data storage, monitoring, and export. The system was deployed in the experimental environment of the Alternative Energies Laboratory (LEA) of the Federal University of Ceará (UFC), known as LEA 3, simultaneously instrumenting a tank with floating modules, a reference tank, and a ground-mounted installation. Variables monitored included irradiance, ambient temperature, relative humidity, wind speed, and temperatures on the modules and in the tank water. The adoption of the acknowledgment (ACK) reception protocol increased the packet delivery rate from values below 50% to 95.49%, remaining at 91.76% throughout 2024. Cross-validation with INMET data confirmed the accuracy of the measurements, with a mean error of 2.12% for irradiation, 1.68% for ambient temperature, and 7.49% for relative humidity. Thermal analyses indicated homogeneity between the center and edge sensors of the modules, with an average difference of less than 1 °C, and similar behavior between ground-mounted and floating modules. For the tanks, it was observed that the reservoir with floating coverage kept the water cooler at maximum temperatures and showed lower daily thermal variability, with an average difference of 1.34 °C compared to the reference tank and a standard deviation of 0.16 °C versus 0.67 °C in the uncovered tank. The work contributes technically to the advancement of PV and FPV monitoring in Brazil by providing an open, reproducible, and experimentally validated IoT architecture that integrates LoRa communication, a web platform, and metrological validation with official data. It is concluded that the proposed system meets the objectives of monitoring, storing, and providing environmental and operational data reliably, establishing an alternative for intelligent monitoring of PV plants.