A machine learning framework to quantify and assess the impact of COVID-19 on the power sector: An Indian context

• DOI: 10.1016/j.adapen.2021.100078
• Publication Date: 2021-12-08T17:15:49Z
• Authors: Manu Suvarna; Apoorva Katragadda; Ziying Sun; Yun Bin Choh; Qianyu Chen; Pravin PS; Xiaonan Wang
• Keywords: Consumption; Pandemic; Baseline (sea)

As the COVID-19 continues to disrupt global norms, there is requirement of modeling frameworks accurately assess and quantify impact pandemic on electricity sector its emissions. In this study, we devise machine learning models estimate induced reduction in consumption based weather, econometrics, social-distancing parameters for seven major Indian states. per our baseline model, find that dropped by 15–33% 2020 (March-May) during complete lockdown phase, followed 6–13% (June-August) unlock phases gradually reached norms September 2020. a result, net CO2 emissions from power generation 7% 5% compared 2018 2019 respectively. Amidst ongoing second wave since mid-April 2021, projected across states May-August accounting two scenarios. Under reference worst-case scenarios, approximates 106% 96% non-pandemic situation, The framework developed study purely data-orientated, cross-deployable spatio-temporal scales can serve as valuable tool inform current future energy policies amidst post COVID-19.