فصلنامه مطالعات اقتصاد انرژی
پیاپی 45 (تابستان 1394)

The energy sector is a most promising area for commercial interactions between Iran and India. India is expected to become the third biggest oil consumer in the World by 2035, thanks to the country’s high population and high rate of economic growth.  On the other hand, Iran holds the worldchr('39')s largest gas reserves and third largest oil reserves, as such is able to meet India’s energy needs for a long time. Energy thus offers huge potential for expansion of mutual relations between the two countries.  This potential, however, remains unrealized due to international sanctions against Iran and negative role of the USA.
 This paper tries to explore Indiachr('39')s long-term strategy for ensuring its energy security and Iran’s potential place in New Delhi’s future energy calculus? This paper contends that India cannot ignore Iran in meeting its energy needs,  particularly with respect to gas, in view of the uncertainty of other potential  sources in terms of price, security and sustainability of supply.

Economic sanctions have been and continue to be applied extensively against Iran.  It is therefore, important for us to analyze the economic and legal aspects of sanctions. The paper is organized around two questions. First, we seek to understand the impact of sanctions on Iranian crude oil production and subsequently on social welfare? In the next step, we examine the effects of changes in oil production on fundamental human rights.
Sanctioning countries claim that by imposing well targeted sanctions negative side effects, particularly impact on vulnerable populations can be minimized. However, this study indicates that sanctions against Iran particularly on the oil industry have many negative impacts on social welfare.
 In this study we have used econometrics tools and OLS methodology to determine the effect of sanctions as an explanatory variable on oil production as a dependent variable for the period 1970 to 2012.  We have resorted to resolving the problems found in the estimated regressions in order to increase their reliability.

Global development in terms of increased attention to environmental protection and the finite nature of fossil resources have accelerated the use of renewable energies. Renewable energy portfolio standard (RPS), is a government policy to promote the use of renewable energy in the energy consumption basket.  The RPS stipulates the minimum amount of renewable energy that each electricity supplier should produce.  This policy has been widely studied in different countries, but so far no such studies have been undertaken in Iran. This study introduces the experience of countries that have been successful in their RPS policies.  We then use linear programming techniques to study an RPS policy that requires regional power supply companies to produce at least 10 percent of their electricity from renewable energy sources. We focus on identifying the optimal combination of different renewable energy sources to meet the RPS.  The results indicate the maximum production of electricity from renewable sources is about 13/65559 TWh.  The optimal ratio of each renewable energy source is respectively 4.29, 9.19, 8.5, 30.9, 19.337 and 30.34 percent for solar energy, biomass, geothermal, wind, hydroelectric and tidal energy.

This paper tries to demonstrate the importance of non-economic exogenous factors (Underlying Energy Demand Trend) when we estimate the industrial energy demand for Iran. The Structural Time Series Model (STSM) approach is used to model these unobservable factors. The Kalman filter and Maximum Likelihood methods allow us to estimate the value of the UEDT. This approach enables us to obtain more reliable estimates of income and price elasticity as well.  We use the derived values of UEDT, and price and income elasticities to evaluate the impact of economic and non-economic exogenous factors on industrial energy demand. The results show that the UEDT has a positive trend and the industrial sector has become more energy intensive over time.  The results further indicate that technological improvement and other non-economic exogenous factors have no impact on energy efficiency in the Iranian industrial sector. Our model estimated short run income and price elasticity as respectively 0.33 and 0.08. The UEDT has a great impact on energy demand change over the time spam (1353-1391).  This impact is greater than that of the income and price impacts.  We also observe that demand for energy in the industrial sector is more sensitive to the level of activities (value added) than price.

The main aim of this survey is to investigate the evolution of the OPEC mode of behavior and link the evolution to some important events in the (global) crude oil market. The dominant conclusion of this survey confirms that the primary purpose of OPEC has been to coordinate and unify the petroleum policies of its member countries, in order to secure their individual and collective interests. OPEC has affected oil price fluctuations through changes in production and quotas. This influence, however, has been varying over time.  There are a few examples that indicate a loss in OPEC ability to control oil price fluctuations (whether up or down). Market conditions explain these changes in OPECchr('39')s influence on oil prices. Due to the volatile nature of OPEC actions, there is not a single model that can explain OPEC behavior.  Researchers have thus resorted to multiple models to explain some special events. Since these diverse models provide very similar predictions and results, empirical work has been unsuccessful in differentiating between them. The main finding of this study is that OPECchr('39')s impact on oil price fluctuations has not been the same over time and has been variable.

The way Energy, Economy and Environment systems correlate along with the appropriate policy will bring about a countries sustainable growth and economic development (E3 Models). The models deals with the relation between these aspects are generalized versions of economic growth models which take into account the energy and environmental factors.
This research analyses concurrent efffect of energy consuption equations, economic growh and CO2 emmision of 3 sectors; Energy, Economy, Environment in the MENA countries from 2000 to 2010 with method of 2SLS. Outcomes show the direct effect of energy consumption on economic growth and concurrent effect on CO2 emission in these countries. According to the existing systematic relation every politic has been taken in any sector, Energy, Economy or Environment, will affect other sectors, althought the amount of effect in not equal.
 

Keywords: Energy, Economy, Environment, E3 Models, Concurrent Equation, MENA region

One of the important energy consuming sectors of the country is buildings. In this research, we use the energy audit of the Atisaz complex in Tehran to evaluate the economic benefits of energy saving measures.  We evaluate measures such as: using the automatic damper, replacing the active existing chiller with the solar absorption one, using intelligent boiler-room and replacing the existing lighting system with the LED one.  We evaluate the economic benefits of these measures using FUZZY LOGIC. The results indicate that the economic benefits of energy saving measures exceed their costs will.  Our results confirm that energy saving measures in addition to having a societal value is beneficial for the concerned consumer.  However, some of the energy saving measures have to be undertaken while constructing a new building for them to be economically feasible.

The use of artificial neural networks (ANN) in forecasting has many applications. Appropriate design of ANN parameters enhances the performance and accuracy of neural network models.  Most studies use a trial and error approach in setting the value of ANN parameters. Other methods used to determine the best structure of a neural network only use a single evaluation criterion to determine the appropriate structure. In this study, the authors provide a new method to design the network structure. In this method, we use a combination of Taguchi experimental design and TOPSIS methods, to determine he optimal ANN structure, taking into account three evaluation criteria simultaneously. The  estimated demand for gasoline in the Hormozgan province produced using this method, confirms its efficiency and effectiveness. Analysis of variance (ANOVA) of the ANN variables indicates that contribution of the number of neurons in the first hidden layer to the changes in the network performance is about 54% while the contribution of the learning algorithm is about 27%.

One of the factors influencing the growth and development of any country depends on the development of its industries. This effective portion is one of the nationchr('39')s largest energy consumers. Study of energy consumption and energy intensity trends in various sectors is a Major step in the planning and policy-making in the energy sector and opens a wide horizon in front of policymakers in these issues. One of the methods used in this context is the analysis method. In this study, analysis of energy consumption and energy intensity changes have been investigated by multiplicative form of the Divisia index and Following the separation in different industries and sectors over a period of 16 years (90-75). The results showed that 120 peacent of the increase in consumption is due to the increase in industrial production. Structural effect caused 26 percent increase on energy consumption and intensity effect caused 30 percent reduction on it. Moreover, a reduction of 12 percent was observed in energy intensity of industry by energy intensity decomposition in industry between 1375 and 1390. The main reason for this decline is due to improvement in efficiency and technological conditions. Although the structural effect caused a considerable increase in Energy intensity this improvement in technical situation could made it up.