Towards Informed Policy Making: An Analysis of the Impact of COVID-19 on Electricity Purchases in South Africa

Michael Jon Ritchie, Jacobus Wilhelm Burger, Dhasaren Naidoo and Marthinus Johannes Booysen ()
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Michael Jon Ritchie: Electrical and Electronic Engineering, Stellenbosch University, Stellenbosch 7602, South Africa
Jacobus Wilhelm Burger: Department of Economics, Stellenbosch University, Stellenbosch 7602, South Africa
Dhasaren Naidoo: Ontec, Cape Town 7500, South Africa
Marthinus Johannes Booysen: Electrical and Electronic Engineering, Stellenbosch University, Stellenbosch 7602, South Africa

Energies, 2022, vol. 15, issue 20, 1-12

Abstract: The COVID-19 pandemic created large disruptions in the energy industry as governments all around the world responded by enforcing lockdowns on 54% of the global population to slow down the spread of the virus. This impacts the energy consumption of the residential sector as policies prevented residents from leaving their homes and accelerated the transition towards remote work environments. The impact of lockdown on South Africa’s energy sector is unique to other countries due to its extreme inequalities across the affluence divide and ongoing blackouts that affect the entire country. A case study is performed in George, a region in South Africa with a distribution of wealth and energy inequality typical for South Africa. In this paper, the following questions are answered: (i) How has the lockdown period influenced the total energy consumption of a household? and (ii) To what extent has the lockdown affected energy consumption of households based on wealth and demographics? The results of this study showed that implementing the highest stage of lockdown resulted in wealthy communities increasing their overall energy consumption by 5 percentage points and poor communities by 2.5 percentage points. The findings of this study support the use of local data and insight for the unique difference in behavioural change across different communities for optimal decision making in future pandemics or natural disasters.

Keywords: COVID-19 pandemic; impact analysis; electricity usage; prepaid meters; residential buildings; data-driven analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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