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  • Policy Research Working Paper 7974

    Assessing the Accuracy of Electricity Demand Forecasts in Developing Countries

    Jevgenijs Steinbuks

    Development Research Group Environment and Energy Team February 2017

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  • Produced by the Research Support Team

    Abstract

    The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

    Policy Research Working Paper 7974

    This paper is a product of the Environment and Energy Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at jsteinbuks@worldbank.org.

    This study assesses the accuracy of time-series econometric methods in forecasting electricity demand in developing countries. The analysis of historical time series for 106 developing countries over 1960–2012 demonstrates that econometric forecasts are highly accurate for the majority of these countries. These forecasts significantly outperform predictions of simple heuristic models, which assume that

    electricity demand grows at an exogenous rate or is propor- tional to real gross domestic product growth. The quality of the forecasts, however, diminishes for the countries and regions, where rapid economic and structural transforma- tion or exposure to conflicts and environmental disasters makes it difficult to establish stable historical demand trends.

  • Assessing the Accuracy of Electricity Demand Forecasts in Developing Countries∗

    Jevgenijs Steinbuks Development Research Group, The World Bank

    JEL:

    Q47

    Keywords:

    electricity

    demand

    forecasting,

    time-series

    econometric

    mod-

    els

    ∗Acknowledgments: The author thanks Deb Chattopadhyay, Vivien Foster, Arthur Kochnakyan, Herman Stekler, Mike Toman, Joeri de Wit and the seminar participants at the Oxford Institute for Energy Studies and the World Bank for their helpful suggestions and comments. Responsibility for the content of the paper is the author’s alone and does not necessarily reflect the views of his institution or member countries of the World Bank.

  • 1 Introduction

    Forecasting the future demand of electricity is an important issue for the utility

    companies, policy-makers, and private investors in developing countries. Reli-

    able electricity demand forecasts are essential for long-term planning of future

    generation facilities and transmission augmentation.

    1 As excess power is not

    easily storable, underestimating electricity demand results in supply shortages

    and forced power outages, which have detrimental effects on productivity and

    economic growth (Calderón and Servén 2004; Fisher-Vanden, et al., 2015; All-

    cott et al., 2016). However, overestimating demand may result in overinvestment

    in generation capacity and ultimately even higher electricity prices because, at

    least for traditional utilities, investment costs need to be recovered to maintain

    financial viability.

    Forecasting long-term electricity demand is a difficult problem as it is subject

    to a range of uncertainties, which include, among other factors, underlying

    population growth, changing technology, economic conditions, and prevailing

    weather conditions (and the timing of those conditions). This problem can be

    particularly challenging in developing countries, where data are often elusive,

    political influences are often brought to bear, and historical electricity demand

    itself is more volatile owing to macroeconomic or political instability.

    Despite the vast significance of having accurate and reliable electricity de-

    mand forecasts for utilities, investors and policy makers, the electricity demand

    forecasting literature comprises of a handful of studies. Table 1 summarizes

    this limited research on electricity production and consumption econometric

    forecasts.

    2 Most of the studies focus on developed economies. Only five studies

    (Abdel-Aal and Al-Garni 1997, Sadownik and Barbosa 1999, Saab et al. 2001,

    Inglesi 2010, and El-Shazly 2013) forecast electricity demand for developing

    countries (Saudi Arabia, Brazil, Lebanon, South Africa, and the Arab Republic

    of Egypt, respectively). As regards data frequency, these studies are almost

    evenly split between short-term forecasts based on monthly data and long-term

    1Though not the focus of this study it is worth noting that reliable electricity demand forecasts are also inportant for short-term load allocation because they help the utilities to optimize the amount of generated power, i.e., maximize their revenue and minimize operational (including environmental) costs.

    2This summary focuses on medium- to long-term econometric projections and does not include high-frequency forecast studies of day-ahead electricity demand. It also omits non- econometric forecast studies based on soft computing techniques such as fuzzy logic, genetic algorithm, and neural networks, and bottom-up computational models such as MARKAL and LEAP. For a comprehensive review of these methods and their applications to energy forecasting, please refer to Suganthi and Samuel (2012).

    2

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