A Neural Network Based Irradiance Meter

This paper proposes a novel design for a Low-Cost Sensor to measure Solar Irradiance. There are mainly three types of devices to measure solar irradiance over the Earths surface Pyranometers (direct and diffuse solar irradiance), Pyrheliometers (direct solar irradiance) and Albedometers (reflected solar irradiance). These devices measure irradiance in W/m2 being highly accurate and therefore expensive. The proposed sensor has to be able of measuring global and diffuse irradiance ensuring high precision. The device a good candidate for large deployment in photovoltaic power plants. The proposed sensor is implemented through a photovoltaic cell, a temperature sensor, and a low-cost microcontroller this paper proposes a novel approach for solar irradiance measurement based on neural networks. In the case of irradiance sensor which is available in market has high cost to calibrate, but in this case the use of a microcontroller allows for easy calibration, updates, and enhancement by simply adding code libraries