Abstract An examination of international political economy history shows that discovery of huge oil reservoirs has been playing an important role in defining and supporting the countries national interest. Undoubtedly, oil reserves in Iran are considered as intergenerational resources and maintaining intergenerational justice as well as enhancing national interest in the long run. These are indisputable commitments which are the main goals and missions of Iran governors. In this research, focusing on the economic aspect of the national interest and by using systems dynamic methodology, dynamics changes of Iran’s national interest are modelled considering developments in the oil industry and market. The structure of production capacity formation, amount of production and revenues of domestic and international sale of oil and oil products are investigated and modeled and variables related to economic national interest are formulated. Simulation results described in five scenarios as follows: growth in the oil market, current status, downturn in the oil market, OPEC market share target, and OPEC revenue target. According to results, increase in domestic prices of energy carriers to international prices and the increase of the budget share for investment in more value added areas in the oil industry are recommended to increase national economic benefits.

Abstract In this paper, the energy demand of transport sector from 1386 to 1400 was forecasted using artificial neural networks (ANN) approach considering economic and social indicators. Feed forward supervised neural networks to forecast and back propagation algorithm to train networks were used. In order to analyze the influence of economic and social indicators on energy demand of transport sector, Gross Domestic Product (GDP), population and the total number of vehicles in 1347-1385 were taken into consideration. The obtained results as compared with the multiple regression method, revealed much less mistakes. The average absolute error percentage was decreased from 15.52% to 6.05%. .

Abstract In this paper, with the priority of measuring and promoting productivity in energy sector, we presented a model for evaluating the technical efficiency of oil refineries, as huge producers of energy and different fuels. The basis of evaluation in this research was Math modeling by using new and advanced operational research techniques such as data envelopment analysis, goal programming, analytical hierarchy process and designing combined models. The formulating process was made under two different scenarios and assumptions: consumption-production and cost-income. The final results ranked the order and sort of each refinery as a decision making unit. In addition to calculation of each unit’s score, we also made a comparison between the units, their weaknesses and the favorite score of each unit in real situation. This research focuses on the optimized utilization of refining processes with less refining cost and ability to make more valuable products considering the present availabilities and capacities