IoT Enabled Environmental Data Monitoring System to Forecast Solar Generation - Raduan, Fahmi; Syed Zahurul Islam, (Evolution in Electrical and Electronic Engineering, 2022)
The ability to accurately forecast the energy generated by Photovoltaic (PV) systems is critical, and it has been described as one of the main challenges for wide PV implementation. PV power generation is entirely dependent on uncontrollable meteorological factors including solar irradiance, ambient temperature, module temperature, wind pressure and direction, and humidity. So, the main concern for this project was to design and develop an Internet of Things (IoT) enabled weather station using sensing technology that can measure ambient temperature, humidity, wind speed, and light intensity. Other than that, to analyze environmental parameters with PV output power collected with the rate of 4 samples/min over a period of four consecutive days. With the help of an IoT system, it can make users easier to monitor and analyze data collected by using a cloud platform which is ThingSpeak. The location for experimental set-up has been done near the Enviro Lab and behind the Kolej Kediaman Tun Fatimah. The duration for data collection was four consecutive days. Based on the result and analysis that has been done, it was proved that environmental parameters can affect the PV power. Besides that, based on the regression analysis, the PV power can be forecasted even though the reading of actual PV power and the forecasted PV power has big differences. This project can be beneficial to people that want to implement a PV system for forecasting PV output purposes and want to analyze the weather parameters.