Development of a real-time meteorological data monitoring system for solar energy plants

In this dissertation, a real-time meteorological data monitoring system for solar energy plants was designed. The components of this system are Raspberry Pi, Bosch BME280 heat, humidity and pressure sensor, Sharp GP2Y1010AU0F dust sensor and Apogee SP-110 solar radiation sensor. The data is collected via the sensors that are used in Raspberry Pi 3 and this data is transferred to the Microsoft Azure cloud. When the data is on the cloud, it can be monitored anywhere from any platform which has an internet connection. The system designed is a crucial one regarding the fact that it provides real-time data by using the Internet of Things. The data collected from the system is compared with the data received from Ege University Solar Energy Institute's meteorology station so as to verify the accuracy of the data collected. The data group that is analyzed was obtained from 15 different time ranges. As a result, the system designed in the light of this analysis and the following outcomes revealed. The inaccuracy percentage of temperature data is 1%, humidity data is 5,6%, pressure data is 0,07% and radiation data is 0,38%. In addition, the mean of the data that reflects the density of dust is measured as 117,71μg/m^3.