Baseline of the projection under a structural change in energy demand

This article investigates the long-term energy demand and energy policy measures when undergoing structural changes in energy demand. Initially, the statistical test shows the possibility of the structural change from the late 2000s. Therefore, we developed the energy demand model to forecast the energy demand by 2030 that considers the structural change. The results show that there may be a 12% reduction in the energy demand in 2030 compared to the reference case in the Japanese government's outlook, which is equal to about 86.0% of the effect of the planned policy measures by the government, but also that it is difficult to achieve energy-originated CO2 emissions in the national target. Our analysis suggests that mitigation policies are required, but those in the planned policy measures are not completely required to achieve the goal.     

The impact of the first oil crisis on energy demand in Korea

This paper investigates how the first oil crisis affected energy demand in Korea. First, annual growth rates in energy consumptions for pre-and post-crisis periods are compared. Second, the price and income elasticities of energy sources estimated from the 1961–1972 and 1961–1976 observations are compared. Third, F-test is performed with an oil demand equation to see whether a structural change in oil demand occurred after the first oil crisis. The author concludes that the impact of the first oil crisis in Korea was not serious enough to cause a structural change in oil demand.     

An empirical analysis of energy demand in Namibia

Using a unique database of end-user local energy data and the recently developed Autoregressive Distributed Lag (ARDL) bounds testing approach to cointegration, we estimate the long-run elasticities of the Namibian energy demand function at both aggregated level and by type of energy (electricity, petrol and diesel) for the period 1980–2002. Our main results show that energy consumption responds positively to changes in GDP and negatively to changes in energy price and air temperature. The differences in price elasticities across fuels uncovered by this study have significant implications for energy taxation by Namibian policy makers. We do not find any significant cross-price elasticities between different fuel types.     

Potential energy demand for cooling in the 50 largest metropolitan areas of the world: Implications for developing countries

Air conditioning of dwellings in developing countries is currently rather rare, but increasing personal income is expected to change that. This study examined the potential energy demand for cooling in the 50 most populous metropolitan areas of the world, and assessed the incremental demand in developing countries that this would create on top of the current energy demand due to heating. The analysis used local cooling and heating degree-day data. The main results are as follows: (1) Most of the largest metropolitan areas are in developing countries (38 out of 50), and most of them, in turn, are in warm to hot climates. (2) All but two of the top 30 metropolitan areas in terms of cooling degree days are in developing countries. (3) The potential cooling demands are greater than heating demands in most of the metropolitan areas that are in developing countries (24 out of 38). The main implication of these findings is that increasing personal income is likely to lead to an unprecedented increase in energy demand in many developing countries. For example, the potential cooling demand in metropolitan Mumbai is about 24% of the demand for the entire United States.     

Examining the role of energy efficiency and non-economic factors in energy demand and CO2 emissions in Nigeria: Policy implications

This paper examines the role of energy efficiency and non-economic factors such as consumers' preferences, lifestyles and values (which have hitherto been ignored) in energy demand and CO₂ emissions modelling for Nigeria. We use a structural time series model to estimate various energy demand and CO₂ intensity models that take account of the aforementioned factors. We adopt preferred models from these estimates to analyse how energy demand and CO₂ emissions in Nigeria might evolve by generating three different future scenarios to 2025. We find energy efficiency and non-economic factors to influence energy demand and CO₂ emissions. The long-run income and price elasticities obtained differ significantly from those in existing studies that have ignored these salient factors. In a business-as-usual scenario, the results indicate that energy demand will continue to grow. Consequently, present policies do not sufficiently mitigate aggregate CO₂ emissions in Nigeria. The lesson for policy makers is that the extant policies introduced to restrain CO₂ emissions (from a production perspective) have to be combined with new policies that influence consumers' lifestyles and behaviours, develop energy efficient technologies and apply low tariffs on imported energy efficient appliances, to drive down CO₂ emissions from a consumption perspective.     

Determinants of energy demand in the French service sector: A decomposition analysis

This paper analyzes the changes in the energy consumption of the service sector in France over the period 1995–2006, using the logarithmic mean Divisia index I (LMDI I) decomposition method. The analysis is carried out at various disaggregation levels to highlight the specifics of each sub-sector and end-use according to their respective determinants. The results show that in this period the economic growth of the service sector was the main factor that led to the increase in total energy consumption. Structure, productivity, substitution and intensity effects restricted this growth, but with limited effect. By analyzing each end-use, this paper enables a more precise understanding of the impact of these factors. The activity effect was the main determinant of the increase in energy consumption for all end-uses except for air conditioning, for which the equipment rate effect was the main factor. Structural changes in the service sector primarily impacted energy consumption for space heating and cooking. Improvements in productivity limited the growth of energy consumption for all end-uses except for cooking. Finally, energy efficiency improvements mainly affected space-heating energy use.     

Energy models for demand forecasting—A review

Energy is vital for sustainable development of any nation - be it social, economic or environment. In the past decade energy consumption has increased exponentially globally. Energy management is crucial for the future economic prosperity and environmental security. Energy is linked to industrial production, agricultural output, health, access to water, population, education, quality of life, etc. Energy demand management is required for proper allocation of the available resources. During the last decade several new techniques are being used for energy demand management to accurately predict the future energy needs. In this paper an attempt is made to review the various energy demand forecasting models. Traditional methods such as time series, regression, econometric, ARIMA as well as soft computing techniques such as fuzzy logic, genetic algorithm, and neural networks are being extensively used for demand side management. Support vector regression, ant colony and particle swarm optimization are new techniques being adopted for energy demand forecasting. Bottom up models such as MARKAL and LEAP are also being used at the national and regional level for energy demand management.     

The costs of failure: A preliminary assessment of major energy accidents, 1907–2007

A combination of technical complexity, tight coupling, speed, and human fallibility contribute to the unexpected failure of large-scale energy technologies. This study offers a preliminary assessment of the social and economic costs of major energy accidents from 1907 to 2007. It documents 279 incidents that have been responsible for $41 billion in property damage and 182,156 deaths. Such disasters highlight an often-ignored negative externality to energy production and use, and emphasize the need for further research.     

Household consumption,associated fossil fuel demand and carbon dioxide emissions: The case of Greece between 1990 and 2006

This paper explores how Greece’s household consumption has changed between 1990 and 2006 and its environmental implications in terms of fossil fuel demand and carbon dioxide (CO₂) emissions. The results show that the 44% increase in Greece’s household expenditure between 1990 and 2006 was accompanied by a 67% increase in fossil fuel demand. Of this total, indirect demand accounted for approximately 60% throughout the 16-year period, increasing by 56% overall, whereas direct fossil fuel demand grew by 80%. The results also show that associated CO₂ emissions increased by 60%, resulting in a “relative decoupling” from energy demand. This relative decoupling is shown to be due to fossil fuel mix changes from the supply side rather than action from consumers. These insights highlight the opportunities for demand-side policies to further reduce fossil fuel demand and CO₂ emissions, allowing Greece to set more proactive and ambitious post-Kyoto targets.     

The demand for energy for irrigation in the USA

There seems to be some question concerning the relationship between irrigation and the price of energy. Did changes in the price of energy actually impact irrigation in the USA? Additionally, the substitution between alternative types of energy seems to be a possibility for irrigation. Whether in fact it occurred is another matter. In this study, an appropriate model is developed and estimated to address the issues. The specific energy types considered include motor gasoline, diesel fuel, liquefied petroleum gas, natural gas and electrical energy. The results for 1978 and for 1980 clearly indicate that energy use for irrigation is responsive to the price of energy. Additionally, some substitution between energy types took place during this period. Finally, when the question of the stability of the demand for the various energy types is addressed, the suggestion is that the demand for the energy types considered was stable for the 1978 and 1980 periods.     

Multivariate Box-Jenkins analysis: A case study in UK energy demand forecasting

The paper discusses a recent case study of Box-Jenkins multivariate techniques in the area of short-term energy demand forecasting by (i) explaining the reasons for adopting Box-Jenkins techniques; (ii) showing how the scale of the problem can be reduced by introducing a two-stage forecasting model; (iii) showing how the models performed against historical data in 1983.     

Improvement of energy demand forecasts using swarm intelligence: The case of Turkey with projections to 2025

The energy supply and demand should be closely monitored and revised the forecasts to take account of the progress of liberalization, energy efficiency improvements, structural changes in industry and other major factors. Medium and long-term forecasting of energy demand, which is based on realistic indicators, is a prerequisite to become an industrialized country and to have high living standards. Energy planning is not possible without a reasonable knowledge of past and present energy consumption and likely future demands. Energy demand management activities should bring the demand and supply closer to a perceived optimum. Turkey's energy demand has grown rapidly almost every year and is expected to continue growing. However, the energy demand forecasts prepared by the Turkey Ministry of Energy and Natural Resources overestimate the demand. Recently many studies are performed by researchers to forecast the energy demand of Turkey. Particle swarm optimization (PSO) technique has never been used for such a study. In this study a model is proposed, using PSO-based energy demand forecasting (PSOEDF), to forecast the energy demand of Turkey more efficiently. Although there are other indicators as well, gross domestic product (GDP), population, import and export are used as basic energy indicators of energy demand. In order to show the accuracy of the algorithm, a comparison is made with the ant colony optimization (ACO) energy demand estimation model which is developed for the same problem.     

Structural changes in Japan''s economy and society and outlook for long-term energy supply and demand

The purpose of this report is to give an outlook for Japan's energy supply and demand to 2015, while taking into consideration structural changes in the economy and society at present and into the future, and to extract subjects that we should address today. When projecting energy supply and demand for the next two decades, we face a number of uncertainties both at home and abroad. In order to project energy supply and demand in the future, three scenarios are assumed: the standard case, the high growth case and the low growth case. Energy supply and demand are projected for each case, showing conditions under which the three scenarios are achieved.     

The demand for gasoline: a comment on the cross-section analysis by Drollas

A recent article [1] used data for 1977 from different countries to estimate the long-run price elasticity of demand for gasoline. Some aspects can be criticized, particularly the interpretation of the results and the model used. An alternative is developed which accepts that the key factor influencing gasoline consumption is the stock of cars. However, energy use per car will vary depending on the size of the country and its average income and price of fuel. This model gives a non-linear equation which is estimated using the same data. All the coefficients are significant with the price elasticity being inelastic.     

Household energy demand in Kenya: An application of the linear approximate almost ideal demand system (LA-AIDS)

This paper estimates price and fuel expenditure elasticities of demand by applying the linear Approximate Almost Ideal Demand system (LA-AIDS) to 3665 households sampled across Kenya in 2009. The results indicate that motor spirit premium (MSP), automotive gas oil (AGO) and lubricants are price elastic while fuel wood, kerosene, charcoal, liquefied petroleum gas (LPG) and electricity are price inelastic. Kerosene is income elastic while fuel wood, charcoal, LPG, electricity, MSP and AGO are income inelastic. The results also reveal fuel stack behaviour, that is, multiple fuel use among the households. Main policy implications of the results include increasing the penetration of alternative fuels as well as provision of more fiscal incentives to increase usage of cleaner fuels. This not withstanding however, the household income should be increased beyond a certain point for the household to completely shift and use a new fuel.     

Prospect of the upper limit of the energy demand in China from regional aspects

The aim of this article is to indicate the upper limit of the annual energy demand in China, taking into consideration regional demand trends and projecting these trends into the distant future. The upper limit of energy consumption is not strictly the maximum amount of consumption. It means that the actual consumption will possibly exceed this level but not by much.     

Residential demand for energy commodities : A household production function approach

This paper formulates a demand model for energy commodities using a household production function approach. The model is stated in a utility maximization framework where utility is assumed to be a function of two composite commodities directly yielding utility. Electricity and natural gas are used as inputs along with a capital stock to produce one of the utility-yielding commodities. The other utility-yielding commodity is assumed to be produced with two non-energy goods and capital stock which are purchased on the market. The Kuhn-Tucker conditions are then used to characterize the optimal time paths for input purchases and investments by the household.     

Decentralized energy supply: Suitability for the UK's industrial sectors

From the results reported here it is suggested that policy decisions about the potential contribution of decentralized energy supply systems to UK industrial energy requirements should be based on the suitability of individual sectors rather than averaged over all sectors. The suitability of decentralized energy sources is evaluated, based on a themodynamic match between source and demand. This suitability criterion is used to identify the most appropriate sector in manufacturing industries for the adoption of decentralized energy supply, leaving aside economic cost considerations and individual site requirements.     

Reduction potentials of energy demand and GHG emissions in China's road transport sector

Rapid growth of road vehicles, private vehicles in particular, has resulted in continuing growth in China's oil demand and imports, which has been widely accepted as a major factor effecting future oil availability and prices, and a major contributor to China's GHG emission increase. This paper is intended to analyze the future trends of energy demand and GHG emissions in China's road transport sector and to assess the effectiveness of possible reduction measures. A detailed model has been developed to derive a reliable historical trend of energy demand and GHG emissions in China's road transport sector between 2000 and 2005 and to project future trends. Two scenarios have been designed to describe the future strategies relating to the development of China's road transport sector. The ‘Business as Usual’ scenario is used as a baseline reference scenario, in which the government is assumed to do nothing to influence the long-term trends of road transport energy demand. The ‘Best Case’ scenario is considered to be the most optimized case where a series of available reduction measures such as private vehicle control, fuel economy regulation, promoting diesel and gas vehicles, fuel tax and biofuel promotion, are assumed to be implemented. Energy demand and GHG emissions in China's road transport sector up to 2030 are estimated in these two scenarios. The total reduction potentials in the ‘Best Case’ scenario and the relative reduction potentials of each measure have been estimated.