Forecasting of solar potential and investigation of voltage stability margin using facts device: a synopsis from geography of things perspective

摘要

The uncertain and erratic nature of renewable energy in solar form is quite laborious to integrate into conventional system operation. In the first part, machine-learning algorithm is used to train models on solar irradiance data and different meteorological weather information to predict solar irradiance. The above-mentioned data is taken from publicly available Geographical Information System (GIS) data. This can be realistically collected using Internet of Things (IoT) devices and sensors which, if based on a GIS approach transforms the system into Geography of Things (GoT). Again, the intermittent and inertia-less nature of PV systems can produce significant power oscillations problems. In the second part, it is shown that residue-based power oscillation damping (POD) controller significantly improves the inter-area oscillation damping. This report overall puts an in-depth analysis with regard to the challenges of solar resources with the integrating, planning, operation and particularly the stability of the power grid.