Forecasting electricity demand in South Africa: A critique of Eskom’s projections

2011

Energy Policy

a b s t r a c tIn South Africa, the electricity mismatch of supply and demand has been of major concern. Additional to past problems, the 2008 electricity crisis made the solution crucial after its damaging consequences to the economy. The disagreement on the need and consequences of the continuous electricity price hikes worsens the situation.To contribute to the recent electricity debate, this paper proposes a time-varying price elasticity of demand for electricity; the sensitivity of electricity consumption to price fluctuations changes throughout the years. The main purpose of this study is the estimation of the price elasticity of electricity in South Africa during the period 1980-2005 by employing an advanced econometric technique, the Kalman filter.Apart from the decreasing effect of electricity prices to consumption (À 71.8% in the 1990s and À 94.5% in the 2000s in average), our results conclude to an important finding: the higher the prices (for example in the 1980s) the higher the sensitivity of consumers to price fluctuations.Thus, further increases of the electricity prices may lead to changes in the behaviour of electricity consumers, focusing their efforts on improving their efficiency levels by introducing demand-side management techniques or even turning to other sources of -cheaper -energy.

Section: Discussionsupporting

confidence: 55%

The evolution of price elasticity of electricity demand in South Africa: A Kalman filter application

2011

Energy Policy

“…The CSIR (2010) model omits the price impact on electricity demand for two reasons: a) the team believes that it is impossible to model price elasticity successfully at the national level and there is a need for sectoral price elasticities such as Ziramba (2008 answered this predicament] and b) due to the fact that such high electricity price increases have not occurred in the past, so there is no precedent set to analyse further. On the other side, Inglesi (2010) and Inglesi and Pouris (2010) employ econometric methods to estimate the price elasticity and based on specific assumptions show that the inclusion of prices (and their high increases lately) can even overturn the path of the electricity consumption from upwards to downwards. It is important to mention that the 1986 review (Pouris, 1986) identified that all forecasts for the year 2000 predicted a demand of 300.000 GWH +/_10% and no study was taking into consideration the effects of prices, technology based efficiencies and similar.…”

Section: Electricity Demand Forecastsmentioning

confidence: 99%

“…Indeed, Inglesi (2010) also concludes that in the short-run, price was not a determinant of electricity consumption. Inglesi and Pouris (2010) also used the same approach to forecast electricity consumption and critically assess Eskom's estimations.…”

Section: South African Department Of Energy (Doe)mentioning

confidence: 99%

“…As part of the IRP 2010 process, SO (2010) and CSIR (2010) forecast electricity demand using primarily statistical modelling and expansion of historical trends; while Inglesi (2010) and Inglesi and Pouris (2010) make use of econometric methods to forecast. The main difference behind their results may not, though, stem from the employed methodology but rather the choice of variables to predict the future electricity demand values.…”

Section: Electricity Demand Forecastsmentioning

confidence: 99%

See 1 more Smart Citation

On the causality and determinants of energy and electricity demand in South Africa: A review

Energy Sources, Part B: Economics, Planning, and Policy

Pouris

2016

The purpose of this paper is to review, summarize, and critically assess the academic studies that have dealt with either the causal relationship between energy consumption and growth or the determinants of energy demand in South Africa from 2007 and outline recent forecasts for electricity demand. The results of this review aim to identify gaps in the existing research. From a policy point of view, the findings of this effort have the potential to inform the relevant stakeholders to make appropriate interventions to improve the status quo of the energy sector. The results have indicated that studies examining the causality direction between energy (electricity) consumption and economic growth have failed to reach a consensus. The main differences identified were the time periods examined, the econometric approaches, and the variables included in the estimations. Another potential reason for the results is the availabilityor lack thereof-of data specific for the country. On the other side, the studies looking at the factor affecting energy (electricity) demand have agreed that economic growth or income or output are considered significant factors. The role of prices was debatable among different studies. This has become more apparent when reviewing the few forecasting efforts in the country that resulted in conflicting results.

“…Papers such as Alton et al (2013) Blignaut (2012, Blignaut et al (2015); Inglesi-Lotz & Blignaut (2011;2012a;2012b;; Inglesi & Pouris (2010);Joubert (2015); Spalding-Fecher & Khorommbi (2003);and Winkler (2007), amongst others, have made valuable contributions to the literature across a wide variety of electricity related topics. However, none of these papers used a comprehensive general equilibrium modelling framework to assess the economy-wide effects of Medupi and Kusile, specifically, whilst also measuring the cost of lost production due to inadequate supply in recent years, as we do in this paper.…”

Section: Background and Literaturementioning

confidence: 99%

An economy-wide evaluation of new power generation in South Africa: The case of Medupi and Kusile

Bohlmann

et al. 2016

Energy Policy

This paper investigates the role that the building of two new power stations, Medupi and Kusile, will play in facilitating future economic activity in South Africa. We use a dynamic computable general equilibrium (CGE) model to estimate the economy-wide effects of these new power stations. Our simulation results also provide insight into how much the local economy has lost due to inadequate electricity supply in the period leading up to the construction of Medupi and Kusile. We find that the decision to build additional power generation capacity was necessary and justified, and that the failure to sooner recognise the need for expansion of the country's electricity generation capacity and subsequent delays in commissioning Medupi and Kusile, likely cost the economy over R110bn in lost production. Additional analysis, in which a further two-year delay in the construction of Medupi and Kusile is simulated, shows that such an event will cause the economy to perform below baseline projections up to 2022.JEL Codes: C68, Q41, Q43