Energy Consumption In Iran Research Articles

Analysis of asymmetries in air pollution with water resources, and energy consumption in Iran.

Iran should pay special attention to its excessive consumption of energy and air pollution due to the limited availability of water resources. This study explores the effects of the consumption of energy and water resources on air pollution in Iran from 1971 to 2014. It utilizes the non-linear autoregressive distributed lag approach to establish a robust relationship between the variables which show that both long- and short-run coefficients are asymmetrical. The positive and negative aspects of the long-run coefficients of energy consumption and water resources were found to be 0.19, - 1.63, 0.18, and 2.36, respectively, while only the negative ones were significant for energy consumption. Based on the cumulative effects, it can be established that there are important and significant differences in the responses of air pollution to positive and negative changes in water productivity and energy consumption. In particular, CO2 gas emissions are affected by negative changes in H2O productivity both in terms of the total and the GDP per unit of energy use in Iran. In regard to short-run results, considerable asymmetric effects occur on all the variables for CO2 emissions. Based on the results obtained, some recommendations are presented, which policymakers can adopt in efforts to address the issues of pollution and consumption.

Analytical solution for the study of time lag and decrement factor for building walls in climate of Iran

More than 40% of energy consumption in Iran associated with the building sector. Among the factors affecting energy consumption, time lag and decrement factor of the walls can be mentioned, which usually are not considered in the design of building of Iran. Therefore, in the present study, time lags and decrement factor for different building materials that prevalently are utilized in Iran have been investigated. In this research, the transient heat conduction equation is solved analytically using Green function under time-dependent convection boundary conditions. The effect of different parameters such as wall thickness and both inner and outer heat transfer coefficients as well as the effect of the thermal insulation layer in sandwich wall on time lag and decrement factor is investigated. The results indicate that the thickness and the type of the building material have a significant effect on the time lag and decrement factor of the wall. Also, it is shown that inside combined convection and radiation heat transfer coefficients affects time lag and decrement factor of the walls. The results of the present study are applicable for designing more effective passive solar buildings in Iran and optimal design of walls and other related areas resulting in energy saving.

Economic growth and energy consumption in Iran: an ARDL approach including renewable and non-renewable energies

Iran experiences a high level of energy consumption which is threatening not only economically but also politically and environmentally. This study aims to estimate the relationship between the economic growth with the various kinds of energies, non-hydroelectric, renewable, non-renewable, and total energies in Iran during 1967–2012, using an autoregressive distributed lags (ARDL) model. The results show the ineffective relationship between the economic growth and energy consumption in Iran, considering non-hydroelectric energy, renewable energy, non-renewable energy, and total energy, one by one as the energy proxy. It implies the ineffectiveness of both the quantitative and qualitative deflationary policies over the energy sector. In another word, neither decreasing energy consumption nor changing energy portfolio affects the economic growth. Therefore, the policy makers are advised to formulate those policies which reduce the quantity of energy consumption or increase the segment of renewable energies in the portfolio of energy consumption because they do not lead to the considerable negative consequence on the economic growth, while they increase both the environmental quality and energy security.

Review of sustainable energy sources in Kerman

Purpose This paper aims to identify and introduce areas in Kerman with a very high potential for produce energy from renewable energy. In this paper, with studying renewable energy resources of the world and Iran, and with the introduction of renewable energy resources in Kerman Province and its counties as a proper supplier of energy in Iran and regions. At the end of this discussion, it is seen that the positive impact of clean energies on the economy, the environment and the health of the region and the country and the potential of the Kerman Province in this rare energy place are considered well. Design methodology/approach To study the energy consumption in Iran and based on universal reports, this area is the largest renewable energy production region in Iran. Findings Currently, electricity used in Kerman is nearly 2,000 MW, while the capacity of production is 1,500 MW which is almost the share of renewable energy in electricity production rate is zero. With regard to industrial development plans in Kerman Province, 5,000 MW of electricity will be needed in the near future, so the province will face an energy crisis. Iran is also a developing country and economy; agriculture and the production of this country is extremely dependent on energy and electricity, and it seems that using renewable energy sources is a way to prevent an energy crisis in the country. Originality/value This paper introduces the Kerman Province and examines the potential of this province as a massive source of energy in Iran and the world. Specific qualifications of this region include the climate variability, existing water dams, suitable areas for utilization of biomass and the high potential that this area has for the development of geothermal energy. These qualifications all contribute to make this region a hub for great production of energy from renewable energy sources in Iran.

Forecasting energy consumption using ensemble ARIMA–ANFIS hybrid algorithm

Energy consumption is on the rise in developing economies. In order to improve present and future energy supplies, forecasting energy demands is essential. However, lack of accurate and comprehensive data set to predict the future demand is one of big problems in these countries. Therefore, using ensemble hybrid forecasting models that can deal with shortage of data set could be a suitable solution. In this paper, the annual energy consumption in Iran is forecasted using 3 patterns of ARIMA–ANFIS model. In the first pattern, ARIMA (Auto Regressive Integrated Moving Average) model is implemented on 4 input features, where its nonlinear residuals are forecasted by 6 different ANFIS (Adaptive Neuro Fuzzy Inference System) structures including grid partitioning, sub clustering, and fuzzy c means clustering (each with 2 training algorithms). In the second pattern, the forecasting of ARIMA in addition to 4 input features is assumed as input variables for ANFIS prediction. Therefore, four mentioned inputs beside ARIMA’s output are used in energy prediction with 6 different ANFIS structures. In the third pattern, due to dealing with data insufficiency, the second pattern is applied with AdaBoost (Adaptive Boosting) data diversification model and a novel ensemble methodology is presented.The results indicate that proposed hybrid patterns improve the accuracy of single ARIMA and ANFIS models in forecasting energy consumption, though third pattern, used diversification model, acts better than others and model’s MSE criterion was decreased to 0.026% from 0.058% of second hybrid pattern. Finally, a comprehensive comparison between other hybrid prediction models is done.

Evaluating Energy and Exergy Efficiencies in Transportation Sector of Iran

Considering the increasing energy demands, energy has gained an important role in planning and policies of many countries. This study presented the status of overall energy consumption in the transportation sector of Iran. According to most of the recently issued statistics, the annual transportation energy consumption of Iran is more than 296×106 barrels of oil equivalent, which is about 25% of Iran’s total annual energy consumption. So, it is logical to analyze energy consumption in transportation sector for the purpose of better planning. Statistics of energy consumption in Iran’s transportation sector was presented for a period of 24 years (1988 to 2011) in this paper. Different transportation sub-sectors (highways, airways, railways, and waterways) and different energy forms were considered separately in the presented statistics. Using these data, energy and exergy efficiencies of the transportation sector were derived. Analyzing the efficiency values in the mentioned 24 year period resulted in concluding some considerable points, which could be used in Iran’s transportation principle policies in the future.

CO2 emissions and output in Iran: Environmental Kuznets Curve approaches

This paper evaluates the dynamic causal relationships between CO2 emissions and energy consumption in Iran for the period 1965–2008 based on the EKC Hypothesis. The VECM technique is exploited for the empirical analysis. This study has been completed in two stages. In the first stage, we examine how the variables are related in the long-run, and at the second stage, survey the dynamic causal relationships between the variables. The empirical results have provided evidence for the existence of a strong long-run relationship between CO2 emissions, energy consumption and real GDP in Iran. Moreover, the results indicate that the increase of GDP and energy consumption simultaneously will increases CO2 emissions and also based on preliminary results, the energy consumption effects are greater than GDP effects on CO2 emission. A short run Granger causality test suggests bidirectional causality between CO2 emissions and energy consumption, unidirectional causality from GDP to CO2 emissions, and unidirectional causality from GDP to energy consumption. In addition, these causalities confirmed that in the long run there are unidirectional relations from CO2 emissions to GDP and from energy consumption to GDP.

SCENARIO ANALYSIS OF IRAN'S FUTURE ENERGY DEMAND AND ITS ENVIRONMENTAL ISSUES FOR THE YEAR 2041

This paper analyzes the structure of energy consumption in Iran. The demand side is divided into five major categories. Each category is further classified into subcategories and modelling is accomplished for the time horizon of 2012 to 2041. In order to determine final results, six technical and economic scenarios have been considered, entailing economic development scenarios and governmental energy management programs. Results show that final energy demand in Iran in all scenarios has an ever growing trend. It is expected that the total emission on demand side reaches to the range of 572 to 856 million tons in 2041. Results also indicate that there is a high potential for carbon reduction in energy demand side up to 5.68% annually.

An analysis of the implementation of energy efficiency measures in the vegetable oil industry of Iran: a data envelopment analysis approach

The vegetable oil industry is considered as one of the major industries contributing to energy consumption in Iran. Despite the increasing need to improve energy efficiency in this industry, previous studies show that energy-efficient technologies have not been applied in most plants and other energy efficiency measures have not yet been adopted. Accordingly, this paper addresses the implementation of energy efficiency measures in the vegetable oil industry. Using a data envelopment analysis (DEA), the relative efficiency of plants in the vegetable oil industry is compared at different stages of the implementation of energy efficiency measures. The most effective indices for improving energy efficiency were identified and a model was designed to implement energy efficiency measures in industrial plants. In the model, the implementation process consisted of 5 stages, each of which had its own inputs and outputs. A multi-stage DEA model was employed to evaluate the performance of vegetable oil plants at each individual stage as well as the aggregate efficiency of each plant. After estimating the total efficiency of all plants and evaluating performance at the individual stages for each plant, the plants with ideal conditions for implementing energy efficiency measures were identified. These plants can serve as a benchmark for other plants. Estimation of the average efficiency across plants at each stage indicated that the plants suffered from poor performance in the first and fourth stages. Therefore, the results of this study indicate a need to develop new strategies for improving energy efficiency at these two stages.

Energy consumption in Iran with Bayesian approach1

AbstractEnergy is one of the most important influential factors on economic growth. In recent decades, upward trend of energy consumption has caused many concerns about decrease in energy source and increase in pollution and global warming. Iran as one of the greatest oil and natural gas exporters with high consumption of gas, oil and electricity faces with pollution problems in cities and hence the necessity of a plan to decrease the energy consumption. In this paper, we study demand of energy consumption and predict consumption of diverse kinds of energy during 2010–2018. In this regard, by adopting Bayesian approach and with concern to data of 1970–2009, we forecast the trends of energy consumption. The result showed that during recent years, up to the average growth rate of energy consumption is equal to 1.8 per cent. The slower growth of energy consumption leads to a slower economic growth and in turn, causes a decline in energy consumption due to the structural changes in the Iran economy.

Energy Consumption in Iran: Past Trends and Future Directions

Energy is one of the most significant presented factors in economic literature. Today, the consumption and efficiency of ener gy have affected all the economical and industrial activities. Our world is the world of economical and industrial development and the process of this development has even been accelerated through the recent decades. Considering the especial situation of I ran in the world and in the region as well, energy sector is more important in this country. The energy of Iran, as one of the most powerful import-export energy of the world, is very potent in the world economy. While Iran is benefited from energy exportation, it can also affect the economy of importer countries. Energy resources in Iran consist of the third largest oil reserves and the second largest natural gas reserves in the world. Iran is in a constant battle to use its energy resources more effec tively in the face of subsidization and the need for technological advances in energy exploration and production. The energy consumption in the country is extraordinarily higher than international standards. Iran recycles 28 percent of its used oil and gas where as the figure for certain countries stands at 60 percent. With an economy which is expected to maintain a rate of growth of 2 to 5 per cent for decades, Iran's role in the world energy market becomes increasingly influential. This makes it important to predict Iran's future demand and supply for energy. The objective of this paper is to apply the Bayesian vector autoregressive methodology to forecast Iran's energy consumption and to discuss potential implications. The slower growth reflects an expect ed slower economic growth and the decline in energy consumption due to structural changes in the Iran economy. Iran's dwindling crude oil production will also put pressure on the internal use of refined products, as consumption and exports come to vie f or the same barrel.

Forecasting Energy Demand in Iran Using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) Methods

The main objective of this research is to estimate energy demand in Iran using intelligence techniques based on the structure of Iran's industry and economic conditions. This study develops a scenario to analyze energy consumption and makes future projections based on particle swarm optimization (PSO) and genetic algorithm (GA) methods. The models are developed in two forms (exponential and linear) and applied to forecast energy demand in Iran. PSO and GA demand estimation models are developed to estimate the future energy demand values based on population, gross domestic product, import, and export data. Energy consumption in Iran from 1981–2005 is considered as the case of this study. The available data is partly used for finding the optimal, or near optimal, values of the weighting parameters (1981–1999) and partly for testing the models (2000–2005). Energy demand in Iran is forecasted up to year 2030.

Energy Consumption Forecasting of Iran Using Recurrent Neural Networks

In this paper, a recurrent neural network model is developed in order to forecast the energy consumption as a complex nonlinear function of gross domestic product (GDP) and population in Iran. This intelligent model is trained by total energy consumption data as output and the population and GDP as inputs during 1976–2001, while 5 annual data points of the following years (2002–2006) are used to validate the model. It can describe time dependencies efficiently and the convergence rate is much faster. This model forecasts the trend of energy consumption annually. Simulation results show that this model can predict energy consumption in Iran with acceptable accuracy. It is expected that this study will be helpful in developing highly applicable energy policies.

Total Energy Demand Estimation in Iran Using Bees Algorithm

Many studies are performed by researchers to estimate energy demand but the bees algorithm (BA) technique has never been used for such a study. This paper presents application of the BA technique to estimate total energy demand in Iran, based on socioeconomic indicators. The BA demand estimation models (BA-DEM) are first developed in two forms (exponential and linear) in order to estimate energy demand based on population, gross domestic product, import and export data. Then, two scenarios are designed for forecasting each socioeconomic indicator in the years 2006–2030. Finally, these two scenarios are used to forecast energy demand up to year 2030 using demand estimation models. Energy consumption in Iran from 1981–2005 is considered as the case of this study. The available data is partly used for finding the optimal, or near optimal, values of the weighting parameters (1981–1999) and partly for testing the models (2000–2005). In order to show the accuracy of the BA, obtained results of BA-DEM models are compared with particle swarm optimization and genetic algorithm demand estimation models which are developed for the same problem.

Prospect of Natural Gas Industry in Iran

Iran holds the second largest gas reserves in the word with over 27.5 trillion cubic meters (TCM) of natural gas. Due to lack of geological surveys in certain geographical regions in Iran. It is likely to explore further reserves in the future. Hence, for utilizing this energy carrier, it is essential to have comprehensive and explicit planning knowledge. The study of gas industry development policies is indicative of certain barriers in utilizing prospective opportunities. Iran is one of the largest gas rich countries in the world that production capacity exceeds domestic consumption and gas injection requirements. Gas can be utilized as feed stock in petrochemical plants and refineries or exported through pipeline or LNG. Through reinjection of gas to oil reservoirs, while increasing the oil recovery ratios, the produced gases from fields shared with other countries could be stored into domestic gas fields.Gas consumption in domestic markets and its substitution with oil products, in addition to providing environmental benefits, will also result in optimum consumption of these products and relieving the government from the heavy burden of existing and heavy expenditures of importing these products from foreign countries.The need for energy sources in the world along with the enormous natural gas reserves in the country opens broad economical/political dialogue scene towards us and contributes an outstanding strategic significance to our gas resources. Supplying gas requirements, proper and timely production and operation of joint reservoirs such as the south pars with the intention of supplying gas requirements and providing balance of supply and demand as well as maximum utilization of our share in these fields are other development requirements of this significant industry.For planning and policy making regarding the development of gas industry, it is essential to manage all aspects of gas from exploration and production to consumption, injection and exports and etc. through a sole administrative institution so that prearranged plans could be implemented without becoming subjected to such problems as lack of coordination parallel activities and organization al problems. Gas fuels consumption occupies one half of Iran's energy consumption, and to increment this share, the government should increase investment in the gas sector.Natural gas while being utilized as a clean fuel in domestic markets can become a device to implement gas injection to oil production from the countries reserves as well as gas exports towards presence in international venues and commercializing gas globally.Prediction indicates that natural gas being the favorable fuel of the present century, will enjoy the largest growth among items within the energy basket and during the next twenty years as well, the growth of natural gas demand in the world will exceed other conventional energy sources. In the future, due to various factors such as vaster accessible sources and reserves, developed technologies which in effect reduce project expenditure and construction periods and consequently improve the economy of developing gas transmission projects, as well as global endeavors to curtail emission of green house gases, are the major reasons for gas consumption growth.Iran, in respect to her geographical and political strategic situation, can play a leading role in global gas supply and act in Europe and Asia. Natural gas still maintains the fastest consumption growth rate among the world's primary energies and is realized to have the highest consumption growth among the developing countries.Gas has been recognizing as the fuel for the future. This is entirely evident as a result of decreasing global resources due to environmental considerations. According to IEA estimates, in year 2015, oil demand will reach 93 million barrels and natural gas demand will reach 64 million barrels of oil equivalent. This in effect is a 20% increase for oil and 45% for gas in regard to current figures in conclusion. It could be stated that more than ever before, gas has gained significance and is the leading basis for modern services in energy, and in the long term is considered a bridge towards a hydrogen resource based economy.Gas as a new fuel, provides the modern technology of fuel cell construction for vehicles possible. To portray the enormity of Iran gas reserves it is enough to consider that Iran's natural gas reserves alone exceeds the total volume of natural gas reserves in USA, Canada, Europe and the entire Asia pacific.

Reinvestigation of Relationship Between Macroeconomic Indexes and Energy Consumption in Iran

Reinvestigation of Relationship Between Macroeconomic Indexes and Energy Consumption in Iran

A simulated-based neural network algorithm for forecasting electrical energy consumption in Iran

This study presents an integrated algorithm for forecasting monthly electrical energy consumption based on artificial neural network (ANN), computer simulation and design of experiments using stochastic procedures. First, an ANN approach is illustrated based on supervised multi-layer perceptron (MLP) network for the electrical consumption forecasting. The chosen model, therefore, can be compared to that of estimated by time series model. Computer simulation is developed to generate random variables for monthly electricity consumption. This is achieved to foresee the effects of probabilistic distribution on monthly electricity consumption. The simulated-based ANN model is then developed. Therefore, there are four treatments to be considered in analysis of variance (ANOVA), which are actual data, time series, ANN and simulated-based ANN. Furthermore, ANOVA is used to test the null hypothesis of the above four alternatives being statistically equal. If the null hypothesis is accepted, then the lowest mean absolute percentage error (MAPE) value is used to select the best model, otherwise the Duncan method (DMRT) of paired comparison is used to select the optimum model which could be time series, ANN or simulated-based ANN. In case of ties the lowest MAPE value is considered as the benchmark. The integrated algorithm has several unique features. First, it is flexible and identifies the best model based on the results of ANOVA and MAPE, whereas previous studies consider the best fitted ANN model based on MAPE or relative error results. Second, the proposed algorithm may identify conventional time series as the best model for future electricity consumption forecasting because of its dynamic structure, whereas previous studies assume that ANN always provide the best solutions and estimation. To show the applicability and superiority of the proposed algorithm, the monthly electricity consumption in Iran from March 1994 to February 2005 (131 months) is used and applied to the proposed algorithm.

Sustainability of energy production and use in Iran

The issue of oil and gas policies in Iran is rather complex. In the present investigation, it is aimed to formulate plans for increasing the capacity of the country's energy production. Analysis of energy consumption pattern over last decades is indicative of inefficient usage. The low energy prices in Iran do not reflect economic costs. Further distortions exist in the tariff structures of most energy sources and in their relative prices. It is recognized that price reform is a key policy element for promotion of energy conservation and fuel substitution with renewable energies. Mitigation policies in the energy sector are crucial to Iran's overall policies. Emission of greenhouse gases can be reduced from 752,156 to 560,791 Gg CO 2 equivalents in 2010 by implementing the policies proposed for the energy sub-sectors. Enhancing energy efficiency, including combined cycle power generation, has proved to be the most economic option for greenhouse gases reduction in energy sector. Iran's energy consumption pattern is unsustainable and consumption oriented.

Simulation of energy saving in Iranian buildings using integrative modelling for insulation

According to one survey on energy consumption in Iran, commercial and building sector consume more energy than any other economic sectors. For example, about 38% of total energy that consumed in year 2001 has been used for space heating. Insulation in external walls of buildings has an important role to reduce the environmental effects on indoor space condition. Therefore, always using insulation is an alternative to avoid from the energy loss. In this paper, the effects of the using of a proper insulation on the energy saving in Iranian buildings are studied. For this purpose, an integrative modelling is used for simulation of the energy consumption in buildings. It is shown that energy consumption per square meter of buildings can be reduced up to 35.2% when insulation is used for external walls.

05/01372 Sectoral energy consumption in Iran

Although somewhat neglected in the housing literature, the progress of whole sector housing development very much depends upon long-term development policies and performances over periods of some 30 years and more. Housing sector development is also dependent upon shorter term macro-economic policies and performances. Countries which have developmental instability and highly fluctuating macro-economic performances are likely to experience generally significant constraints and even some setbacks in housing sector development, with policies becoming fragmented and detached from an appropriate integration with development. Such has been the experience in Iran. Instabilities arose in the redirection of political power with the overthrow of the Shah's regime in 1979 and the installation of the Islamic Republic of Iran. Political revolution and change also affected economic policies for development. The Shah's regime had sought a quick route to modernization by way of selected development of industry, but at risk and with rural-urban imbalance. Then under the Islamic Republic regime, development policies have sought to achieve the multiple objectives of social justice, modernization, and ‘politically correct’ Islamic institutional conditions. These objectives have not been readily reconciled with each other, and Iran has experienced the further instabilities of war with Iraq in the years 1980–1988 and the severe earthquake of 1990. Housing sector development has consequently experienced significant constraints, notwithstanding the post-1979 regime's necessity to try to maintain some degree of popular support, with housing being significant in this. Issues of developmental (in)stability are relevant to the UN Centre for Human Settlements (UNCHS-Habitat) and World Bank's Global Strategy for Shelter (GSS), developed in the years 1986 to 1993.