Abstract:
Various nations within sub-Saharan Africa are currently facing different
stages of loadshedding, with South Africa being of no exception to this trend.
Loadshedding has been implemented as a strategy to manage electricity
consumption during peak demand periods while allowing for increased
usage during off-peak times. This study examines the monthly trends of
loadshedding and unplanned power outages in South Africa, utilizing mean
and quantile regression count time series models. Unplanned outages can
arise from multiple factors, including maintenance activities on power lines,
equipment malfunctions, adverse weather events, cable theft or emergencies
such as accidents. Recurrent outages impede business activities, leading
to a decrease in productivity and an increase in operational expenditures.
Given the profound impact of power interruptions on economic stability
and social welfare, this research aims to quantify and analyze the temporal
trends and seasonal patterns of outages. By leveraging a comprehensive
dataset, we first apply Poisson and negative binomial regression models to
assess the average frequency and duration of outages, revealing significant
trends and seasonal fluctuations. Following this, we employ quantile
regression techniques to explore the distributional impacts of various factors,
including socioeconomic variables and weather conditions, on the occurrence
of outages. The analysis considers five quantiles—10th, 25th, 50th, 75th,
and 90th. While negative binomial regression adequately captures average
loadshedding dynamics, quantile regression proves superior in modelling
extreme outage conditions that are most relevant for electricity system risk management and policy planning. The data was diagnosed to be highly
correlated. Therefore penalised models were also employed. Our findings
indicate that an increase in contracted demand, along with both planned and
unplanned outages, correlates with a rise in the frequency of loadshedding.
This suggests that loadshedding is influenced not only by heightened demand
but also by failures in generation and distribution infrastructure. The
thorough methodology adopted in this research deepens our understanding
of the challenges surrounding power supply in South Africa, offering critical
insights for policymakers and stakeholders to formulate targeted strategies
aimed at mitigating the effects of loadshedding and enhancing energy
resilience. Tackling these challenges necessitates substantial investment in
infrastructure, a diversification of energy sources, and enhanced management
of the electricity supply chain.
