ENERGY ECONOMICS REVIEW
Year:2012 | Volume:9 | Issue:34|Papers Count:9

The increased share of CNG in the country's energy use, in response to the policy of removal of fuel subsidies, is contingent upon construction of an adequate number of CNG fuel stations to service the increased number of dual-fuel vehicles in use. The required heavy investment would have to come largely from the private sector, whose actions are dependent on profitability of the operation of such CNG fuel stations. The profitability of CNG fuel stations in turn depends on the margin allowed for the operators. Currently, the private sector does not have adequate incentives for constructing CNG fuel stations due to high land prices and low margins allowed on CNG sales do not provide the needed incentives. In order to provide adequate incentives for investment by the private sector, the mark-up allowed per unit of CNG has to be increased to a level that would render construction of CNG fuel stations economically feasible.The present study aims to study the economic feasibility of construction of single & multipurpose CNG fuel stations of different capacities under various scenarios, taking into account impact of fuel subsidy removal measures on the cost of construction and operation of such fuel stations. The results indicate that most CNG fuel stations (especially stations with low capacities) are non-economic. To resolve this problem mark-up amounts should be raised under a differential system that would allow for different mark-ups in different zones of the country.

Establishment of the Gas Exporting Countries Forum in Tehran in 2001 has been one of the most important changes in the gas market. Member countries have had the following three main objectives: creating an organized structure for the global gas market, creating consistency in their export policies and increasing gas prices. Establishment of the forum has sparked concerns amongst gas importers that a cartel is being formed, on the model of OPEC for the oil market, which would disrupt security of supply security and increase gas prices. Our study indicates that while the forum has good potential for impacting the gas market it faces many challenges for its transformation into a cartel or any other effective player on the gas market. We can thus conclude that given the current structure of the gas market and the forum and problems faced by the forum, at least in the near term one can not expect a cartel to be formed in the gas market.

High domestic natural gas consumption and major differences between demand in cold and warm seasons pose major challenges in Iran. The seasonal nature of demand for natural gas seasonality has created many problems for honoring export commitments, injection of gas into oil fields and meeting peak demand of domestic users. To respond to high demand for natural gas in the cold season the country has to store excess natural gas during the warm season for use in winter. Optimal storage capacity, in turn is dependent on a solid projection of future peak seasonal demand. This paper is prepared with the objective of projecting future peak demand and associated need for storage facilities. In this paper we use Neural Network and Seasonal ARIMA methods to forecast seasonal natural gas consumption over Iran's 5th development plan period and calculate the requited storage capacity. The results show that neural network methodology has superior predictive power compared to the ARIMA method.The seasonal nature of demand for natural gas is expected to continue. The model results indicated that in addition to the already planned 4BCM/Y of storage capacity, the country needs to build an additional 10BCM/Y of gas storage facilities in order to effectively respond to peak demand for domestic consumption and to ensure optimal management of gas supply and demand.

The goal of this study is to measure the effect of daylight saving time on electricity consumption in the four provinces of Tehran, Yazd, Esfahan and Fars. A system of 24 equations, one for each hour of the day is estimated using the SUR method.The equations are estimated for the years 1382 to 1384 during which daylight saving time was in force. Then the model is solved for the years 1385 and 1386 during which daylight saving time was not in use. Comparing the results of simulated electricity consumption with actual electricity consumption, the potential amount of saved electricity is estimated. The results show that use of daylight saving time in the four provinces mentioned above, could have reduced electricity consumption by respectively 1,259,227 MW (equal to 3.2% of total electricity use) in 1385 and 1,555,273 MW (equal to 3.7% of total electricity use) in 1386. The monetary value of potential savings equals to 192,384,736,665 Iranian Rials in 1385 and 237,614,546,427 rials in 1386.  In addition, use of daylight saving time can cause a reduction in the mean peak electricity consumption of the four provinces.

In this study, we evaluate the effect of electricity pricing policies on employment and general price index of different economic sectors in Iran, through use of the computable general equilibrium model (CGE) and the Social Accounting Matrix (SAM) for 2006. The study makes use of the GAMS software. The results of this study show that the general price index of different economic sectors increases as the controlled electricity prices are raised. Our simulations indicate that in the case of a sudden increase in electricity prices by 400 percent or even more, there would not be sufficient time for substituting one production factor with another. As a result in this scenario the model foresees a substantial decrease in employment in all the three sectors of industry, agriculture and services. However, a gradual increase in prices allows time for economic agents to find substitutes for higher cost production inputs and hence is actually accompanied by an overall increase in employment with minimal disturbances to the equilibrium point of every sector. We can therefore conclude that gradual increases in prices are preferable to a sudden increase.

Many researchers are interested in forecasting oil prices and understanding its behavior over time, given the importance of oil as a strategic factor in many industries and markets. Nowadays, non-classic approaches such as Artificial Intelligence and Machine Learning methods are used in modeling and forecasting complex systems. Recently, one of the Machine Learning techniques, entitled Suort Vector Machine, is extensively used in classification, regression and time series forecasting. This method, which is based on statistical learning theory, has attracted the interest of many researchers. This is due to some of its properties such as: simple geometric interpretation, unique general solution, ability to model non-linear behavior and minimization of generalization error instead of training error. In this paper we study and evaluate the ability of SVR in predicting oil price volatility in Iran.  We then compare the performance of this model with the GARCH models. In this research, we have used monthly prices of Iranian crude oil for the period April 1981 to December 2011. The results indicate that the SVR method is superior to the GARCH models based on MSE, MAE, NMSE and TIC criteria.

The long-term nature of petroleum contracts creates scope for conflict of interest between foreign oil companies and host states. This long-term nature of contracts means that unforeseeable political and economic changes can necessitate renegotiation. The parties to the contract try to use various mechanisms to maintain the equilibrium of interests that the parties have managed to reach at the end of usually protracted negotiation processes. One such mechanism is allowing for renegotiation of contracts. This article aims to examine the concept and practice of renegotiation and addressing how oil investment contracts can have the required stability while allowing a reasonable level of flexibility.

Rebound effects refer to the phenomenon whereby part of the impact of a change in a system is negated by subsequent changes that tend to move the value of the target variable back towards its ealier level. With introduction of new technology, as motor vehicles become more fuel-efficient, there is an initial decline in the demand for fuel. However, these efficiency gains can be partially offset by increased usage of the more efficient cars, thus partially negating some of the initial decline in demand. This is what is referred to as the rebound effect.In this study we estimate the rebound effect through use of the following equation for own price elasticity of energy demand. To this end we define a double logarithmic functional form to study fuel demand over the 34 year period of 1976 to 2009. The results reveal a long-run rebound effect of about 9%. In the better words, the rebound effect of 9% means that only 9% of the potential energy savings is lost due to increased use of vehicles, producing a net saving equal to 91% of the efficiency gain. This implies that the policy of increasing fuel efficiency of vehicles has been successful in reducing energy consumption.