ANNOUNCEMENTS
Digital twins are going to be an integral part of the fourth Industrial revolution (Industry 4.0). This technology takes simulation to the next step. It combines present simulation technology with real time monitoring systems. This helps create an exact digital replica of the asset/process/machine. It takes real time data from the actual asset and keeps improving using machine learning. Any changes or maintenance to the real object is taken as input for the digital twin. This enables us to predict the state of the asset in the future, the need for maintenance, when a component is about to fail and give the exact location of the failure.
This project was aimed to conduct a study about digital twins in the field of solar photovoltaic plants and draft an algorithm that can be used as a base for a digital twin.
Data from Renew Power’s plant in Pokhran was used for the analysis. Regression was used to forecast energy generation and module temperature by using past data from the plant. Python and Microsoft Excel were used in the making of regression models for the purpose of forecasting.
