Forecasting of solar potential and investigation of voltage stability margin using facts device: a synopsis from geography of things perspective. (24th December 2021)

• Record Type: Journal Article
• Authors: Howlader, Masum; Mahmood, Khandaker Sultan; Zakaria, Md.Golam; Kadir, Kazi Mahtab; Iqbal, Mirza Mursalin
• Is Part Of: International journal of grid and utility computing. Volume 12:Number 5/6(2021)
• Page Start: 486
• Page End: 498
• Publication Date: 2021-12-24
• Subjects: renewable energy -- thyristor controlled series capacitor -- support vector regression -- GoT; Electronic data processing -- Distributed processing -- Periodicals; Electronic commerce -- Management -- Computer programs -- Periodicals; 004.605
• Languages: English
• ISSNs: 1741-847X

Abstract

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.