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

Authors: Masum Howlader; Khandaker Sultan Mahmood; Md.Golam Zakaria; Kazi Mahtab Kadir; Mirza Mursalin Iqbal

Addresses: Department of Electrical and Electronic Engineering, University of Asia Pacific, 74/A Green Road, Farmgate, Dhaka 1205, Bangladesh ' Department of Electrical and Electronic Engineering, University of Asia Pacific, 74/A Green Road, Farmgate, Dhaka 1205, Bangladesh ' Department of Electrical and Electronic Engineering, University of Asia Pacific, 74/A Green Road, Farmgate, Dhaka 1205, Bangladesh ' Department of Electrical and Electronic Engineering, University of Asia Pacific, 74/A Green Road, Farmgate, Dhaka 1205, Bangladesh ' Department of Electrical and Electronic Engineering, University of Asia Pacific, 74/A Green Road, Farmgate, Dhaka 1205, Bangladesh

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.

Keywords: renewable energy; thyristor controlled series capacitor; support vector regression; GoT.

DOI: 10.1504/IJGUC.2021.120094

International Journal of Grid and Utility Computing, 2021 Vol.12 No.5/6, pp.486 - 498

Received: 28 Dec 2019
Accepted: 14 Aug 2020
Published online: 07 Jan 2022 *

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