An adaptive network-based fuzzy inference system for short-term natural gas demand estimation: Uncertain and complex environments

Accurate short-term natural gas (NG) demand estimation and forecasting is vital for policy and decision-making process in energy sector. Moreover, conventional methods may not provide accurate results. This paper presents an adaptive network-based fuzzy inference system (ANFIS) for estimation of NG demand. Standard input variables are used which are day of the week, demand of the same day in previous year, demand of a day before and demand of 2 days before. The proposed ANFIS approach is equipped with pre-processing and post-processing concepts. Moreover, input data are pre-processed (scaled) and finally output data are post-processed (returned to its original scale). The superiority and applicability of the ANFIS approach is shown for Iranian NG consumption from 22/12/2007 to 30/6/2008. Results show that ANFIS provides more accurate results than artificial neural network (ANN) and conventional time series approach. The results of this study provide policy makers with an appropriate tool to make more accurate predictions on future short-term NG demand. This is because the proposed approach is capable of handling non-linearity, complexity as well as uncertainty that may exist in actual data sets due to erratic responses and measurement errors.     

GDP and environment pressure: The role of energy in Latin America and the Caribbean

This paper analyzes the relationship between economic growth and energy consumption for a sample of 21 Latin American and Caribbean countries during the 1970–2007 period. The investigation is made on the bases of the Energy Environmental Kuznets Curve (EEKC) hypothesis, using a panel data analysis. Energy consumption at aggregate level is used as an indicator of human environmental pressure and GDP per capita as an indicator of economic activity. Based in a cointegration approach, our results does not support the existence of a stable long run relationship between the series, rejecting the validity of such hypothesis for the selected sample over the 1970–2007 period.     

Impacts and implications of implementing voluntary greenhouse gas emission reduction targets in major countries and Korea

This study analyses the pledges submitted by Korea and other major parties to the UNFCCC secretariat as part of the Copenhagen Accord, using the global CGE model. The analysis shows that the greenhouse gas (GHG) emissions of the developed countries decrease by up to 14.0% by 2020 compared to the 1990 level. These results show the need to raise the targets amongst developed countries in order to reach to the reduction levels (25–40%) recommended by the IPCC to meet 450 ppm CO₂ eq. On the other hand, the full implementation of those pledges of Annex I and non-Annex I countries was found to contribute to the decrease of the global GHG emissions by about 15.9% compared to Business as Usual (BaU). Such results imply the need for developed countries to step up their reduction targets, as well as for developing ones to participate comprehensively and to reduce GHG emissions at a considerable level in order to enhance the environmental effectiveness of the Post-Kyoto framework hereafter. Meanwhile, it is analyzed that the implementation of voluntary target among major countries would reduce the global real GDP by 1.2%, and in the case of Korea, the real GDP was projected to diminish by 1.5%.     

An evaluation of energy-environment-economic efficiency for EU,APEC and ASEAN countries: Design of a Target-Oriented DFM model with fixed factors in Data Envelopment Analysis

This paper aims to offer an advanced assessment methodology for sustainable national energy-environment-economic efficiency strategies, based on an extended Data Envelopment Analysis (DEA). The use of novel efficiency-improving approaches based on DEA originates from the so-called Distance Friction Minimisation (DFM) method. To design a feasible improvement strategy for low-efficiency DMUs, we develop here a Target-Oriented (TO) DFM model. However, in many real-world cases input factors may not be flexibly adjusted in the short run. In this study, we integrate the TO-DFM model with a fixed (inflexible) factor (FF) approach to cope with such more realistic circumstances. Super-efficiency DEA is next used in our comparative study on the efficiency assessment of energy-environment-economic targets for the EU, APEC and ASEAN (A&A) countries, employing appropriate data sets from the years 2003 to 2012. We consider two inputs (primary energy consumption and population) and two outputs (CO₂ and GDP), including a fixed input factor (viz. population). On the basis of our DEA analysis results, EU countries appear to exhibit generally a higher efficiency than A&A countries. The above-mentioned TO-DFM-FF projection model is able to address realistic circumstances and requirements in an operational sustainability strategy for efficiency improvement in inefficient countries in the A&A region.     

Prospective national and regional environmental performance: Boundary estimations using a combined data envelopment – stochastic frontier analysis approach

The environmental performance of regions and largest economies of the world – actually, the efficiency of their energy sectors – is estimated for the period 2010–2030 by using forecasted values of main economic indicators. Two essentially different methodologies, data envelopment analysis and stochastic frontier analysis, are used to obtain upper and lower boundaries of the environmental efficiency index. Greenhouse gas emission per unit of area is used as a resulting indicator, with GDP, energy consumption, and population forming a background of comparable estimations. The dynamics of the upper and lower boundaries and their average is analyzed. Regions and national economies having low level or negative dynamics of environmental efficiency are determined.     

Greek long-term energy consumption prediction using artificial neural networks

In this paper artificial neural networks (ANN) are addressed in order the Greek long-term energy consumption to be predicted. The multilayer perceptron model (MLP) has been used for this purpose by testing several possible architectures in order to be selected the one with the best generalizing ability. Actual recorded input and output data that influence long-term energy consumption were used in the training, validation and testing process. The developed ANN model is used for the prediction of 2005–2008, 2010, 2012 and 2015 Greek energy consumption. The produced ANN results for years 2005–2008 were compared with the results produced by a linear regression method, a support vector machine method and with real energy consumption records showing a great accuracy. The proposed approach can be useful in the effective implementation of energy policies, since accurate predictions of energy consumption affect the capital investment, the environmental quality, the revenue analysis, the market research management, while conserve at the same time the supply security. Furthermore it constitutes an accurate tool for the Greek long-term energy consumption prediction problem, which up today has not been faced effectively.     

Forecasting future oil demand in Iran using GSA (Gravitational Search Algorithm)

Growing energy demand of the world, made the major oil and gas exporting countries to have critical role in the energy supply. The geostrategic situation of Iran and its access to the huge hydrocarbon resources placed the country among important areas and resulted in the investment development of oil and gas industry.In this study, a novel approach for oil consumption modeling is presented. Three demand estimation models are developed to forecast oil consumption based on socio-economic indicators using GSA (Gravitational Search Algorithm). In first model (PGIE) oil consumption is estimated based on population, GDP, import and export. In second model (PGML) population, GDP, export minus import, and number of LDVs (light-duty vehicles) are used to forecast oil consumption and in third one (PGMH) population, GDP, export minus import, and number of HDVs (heavy-duty vehicles) are used to estimate oil consumption. Linear and non-linear forms of equations are developed for each model.In order to show the accuracy of the algorithm, a comparison is made with the GA (Genetic Algorithm) and PSO (Particle Swarm Optimization) estimation models which are developed for the same problem. Oil demand in Iran is forecasted up to year 2030.     

Causality relationship between coal consumption and GDP: Difference of major OECD and non-OECD countries

This paper uses Granger causality tests to examine the differences of causal relationships between coal consumption and GDP in major OECD and non-OECD countries, using data for the period of 1980–2005. What we discovered is that unidirectional causality running from GDP to coal consumption exists in Japan and China, and no causality relationship between coal consumption and GDP in India, South Korea and South Africa while the series are not cointegrated in USA. The major OECD or non-OECD countries especially China, India and South Africa should reduce their CO₂ emissions in coal consumption to reach sustainable development.     

Update of indicators for climate change mitigation in Greece

This paper analyses the factors affecting greenhouse gas (GHG) emissions in Greece, (i.e. the drivers of pressures on climate change), using environmental indicators related to energy, demographics and economic growth. The analysis is based on the data of 2008 and considers types of fuel and sectors. The Kaya identity is used to identify the relationship between drivers and pressures, using annual time series data of National GHG emissions, population, energy consumption and gross domestic product. The analysis shows that over the period 2000–2008, GHG emissions show a slight variation, but they are almost stabilised, with a total increase of 1.6%. Despite the economic growth over that period, this stabilisation may be considered as a combination of reductions in the energy intensity of GDP and the carbon intensity of energy, which are affected by improvements in energy efficiency and introduction of “cleaner” fuels, such as natural gas and renewables in the energy mixture of the country.     

The natural gas potential of Saudi Arabia

Kingdom of Saudi Arabia (KSA) has the fourth largest natural gas (NG) reserves in the world. One third of these reserves are located in the Ghawar region of Eastern Province. NG production is controlled tightly due to close conjunction with oil production until recently. KSA’s NG production of 85 billion cubic meters in 2015 from 70 billion cubic meters in 2008 sets an average annual increase of 2.7%. More than half of the annual KSA’s NG production has been accompanied by gas. The Saudi Gas Initiative (SGI) aims to increase foreign investment in the NG development sector through petrochemicals, power generation, and gas development while integrating with salt water desalination. The barriers in the success of motor fuel policies include high initial capital costs, lack of information or skills, less market acceptance, technology limitations, and financing risks. This article aims to review the potential of NG as an alternative to oil and coal in KSA in meeting the country’s high energy requirements.     

Natural gas consumption and economic growth: A panel investigation of 67 countries

This study examines the relationship between natural gas consumption and economic growth for a panel of 67 countries within a multivariate framework over the period 1992–2005. Pedroni’s 24 and 26 heterogeneous panel cointegration test reveals there is a long-run equilibrium relationship between real GDP, natural gas consumption, real gross fixed capital formation, and the labor force. The results of the panel vector error correction model reveal bidirectional causality between natural gas consumption and economic growth in both the short- and long-run.     

A structural VAR analysis of electricity consumption and real GDP: Evidence from the G7 countries

In this paper, we depart from the literature on electricity consumption–real GDP in that for the first time we examine the reaction of real GDP to shocks in electricity consumption. To achieve this goal, we use the structural vector autoregressive (SVAR) model and examine the impact of electricity consumption shocks on real GDP for the G7 countries. We find that except for the USA, electricity consumption has a statistically significant positive impact on real GDP over short horizons. This finding implies that except for the USA, electricity conservation policies will hurt real GDP in the G7 countries.     

Projection of future transport energy demand of Thailand

The objective of this study is to project transport energy consumption in Thailand for the next 20 years. The study develops log-linear regression models and feed-forward neural network models, using the as independent variables national gross domestic product, population and the numbers of registered vehicles. The models are based on 20-year historical data between years 1989 and 2008, and are used to project the trends in future transport energy consumption for years 2010–2030. The final log-linear models include only gross domestic product, since all independent variables are highly correlated. It was found that the projection results of this study were in the range of 54.84–59.05 million tonnes of oil equivalent, 2.5 times the 2008 consumption. The projected demand is only 61–65% of that predicted in a previous study, which used the LEAP model. This major discrepancy in transport energy demand projections suggests that projects related to this key indicator should take into account alternative projections, because these numbers greatly affect plans, policies and budget allocation for national energy management.     

Energy consumption,economic growth and prices: A reassessment using panel VECM for developed and developing countries

This paper reinvestigates the energy consumption–GDP growth nexus in a panel error correction model using data on 20 net energy importers and exporters from 1971 to 2002. Among the energy exporters, there was bidirectional causality between economic growth and energy consumption in the developed countries in both the short and long run, while in the developing countries energy consumption stimulates growth only in the short run. The former result is also found for energy importers and the latter result exists only for the developed countries within this category. In addition, compared to the developing countries, the developed countries’ elasticity response in terms of economic growth from an increase in energy consumption is larger although its income elasticity is lower and less than unitary. Lastly, the implications for energy policy calling for a more holistic approach are discussed.     

Energy prices,multiple structural breaks,and efficient market hypothesis

This paper investigates the efficient market hypothesis using total energy price and four kinds of various disaggregated energy prices – coal, oil, gas, and electricity – for OECD countries over the period 1978–2006. We employ a highly flexible panel data stationarity test of Carrion-i-Silvestre et al. [Carrion-i-Silvestre JL, Del Barrio-Castro T, Lopez-Bazo E. Breaking the panels: an application to GDP per capita. J Econometrics 2005;8:159–75], which incorporates multiple shifts in level and slope, thereby controlling for cross-sectional dependence through bootstrap methods. Overwhelming evidence in favor of the broken stationarity hypothesis is found, implying that energy prices are not characterized by an efficient market. Thus, it shows the presence of profitable arbitrage opportunities among energy prices. The estimated breaks are meaningful and coincide with the most critical events which affected the energy prices.     

Power generation and cooling capacity enhancement of natural gas processing facilities in harsh environmental conditions through waste heat utilization

Most natural gas (NG) producers in the Persian Gulf face increasing challenges in meeting their domestic gas demands and therefore seek to reduce their NG consumption. Concurrently, the on‐site power generation and cooling capacities of local NG processing facilities are constrained by extreme climatic conditions. A combined cooling and power scheme based on gas turbine (GT) waste heat‐powered absorption refrigeration is techno‐economically assessed to reduce the NG consumption of a major gas processing plant in the Persian Gulf. The scheme utilizes double‐effect water‐lithium bromide absorption refrigeration activated by steam generated from GT exhaust gas waste heat to provide both GT compressor inlet air and process gas cooling. Based on a thermodynamic analysis, recovery of 150 MW of GT waste heat is found to enhance the plant cooling capacity by 195 MW, thereby permitting elimination of a 32.6 MW GT and existing cooling equipment. On‐site power generation is enhanced by 196 GWh annually through GT compressor inlet air cooling, with energy efficiency (i.e., 64%) improved by 35% using cogeneration relative to the existing power generation plant. The overall net annual operating expenditure savings contributed by the combined cooling and power system are of $US13 million to 34 million based on present and projected local utility prices, with an economic payback period estimated at 2 to 5 years. These savings translate to approximately 94 to 241 MMSCM of NG per year, highlighting the potential of absorption refrigeration to both enhance the power generation and cooling capacity of hydrocarbon processing plants exposed to harsh environmental conditions and to realize substantial primary energy savings. Copyright © 2014 John Wiley & Sons, Ltd.     

Energy consumption and economic growth revisited: Does the size of unrecorded economy matter?

We analyze the long-run relationship between energy consumption and real gross domestic product (GDP) in Turkey taking into account the size of unrecorded economy. Since in developing countries, mainly due to the unrecorded economic activities, the official GDP is not measured correctly, the investigation of the linkage between energy consumption and official GDP may not give reliable results. In this study, empirical results for the case of Turkey over the period 1970–2005 suggest that there is a long-run equilibrium relationship between the officially calculated GDP and energy consumption. Besides, using the error-correction modeling technique, we find out that unidirectional causality runs from official GDP to energy in both short and long runs. However, when we take into account unrecorded economy, we detect neither cointegration nor causality between energy consumption and true GDP. These empirical findings imply that: first, energy conservation policies can be implemented in order to reduce greenhouse gas emissions without any adverse effect on the recorded economic activities; second the production function in the unrecorded economy is not stable. Furthermore, economic policies to combat unrecorded economy may not serve as a complement to energy conservation policies.     

Economic growth-electricity consumption causality in 12 European countries: A dynamic panel data approach

This paper applies recent panel methodology to investigate the long-run and causal relationship between electricity consumption and real GDP for a set of 12 European countries using annual data for the period 1970–2007. The sample countries have moved faster than other neighboring countries towards the creation of a single electricity market over the past 30 years. Energy prices are also included in the study due to their important role in affecting the above variables, thus avoiding the problem of omitted variable bias. Tests for panel unit roots, cointegration in heterogeneous panels and panel causality are employed in a trivariate VECM estimated by system GMM. The results show evidence of a long-run equilibrium relationship between the three series and a negative short-run and strong causality from electricity consumption to GDP. As expected, there is bidirectional causality between energy prices and GDP and weaker evidence between electricity consumption and energy prices. These results support the policies implemented towards the creation of a common European electricity market.     

The relationship between electricity consumption,electricity prices and GDP in Pakistan

This study analyzes the relationship among electricity consumption, its price and real GDP at the aggregate and sectoral level in Pakistan. Using annual data for the period 1960–2008, the study finds the presence of unidirectional causality from real economic activity to electricity consumption. In particular, growth in output in commercial, manufacturing and agricultural sectors tend to increase electricity consumption, while in residential sector, growth in private expenditures is the cause of rising electricity consumption. The study concludes that electricity production and management needs to be better integrated with overall economic planning exercises. This is essential to avoid electricity shortfalls and unplanned load shedding.     

Spatial relationship between economic growth and renewable energy consumption in 26 European countries

The relationship between economic growth (GDP) and renewable energy consumption in different regions has been studied using diverse methods and data. However, most of these studies focus on the temporal aspect but do not explain the spatial relationship between GDP and renewable energy since they assume that each country is an island unto itself and do not consider the possible spatial relationship between neighbouring countries. In this study, we have used a spatial Durbin model with panel data to investigate the spatial dependence between GDP and renewable energy consumption for 26 European countries over the period 1991–2015. We conclude that spatial dependence leads to a change in renewable energy consumption that affects the GDP of neighbouring countries. Specifically, a 1% increase in the renewable energy consumption of one country will increase economic growth by up to 0.054% in the GDP of its neighbouring countries.