JOURNAL OF ENERGY PLANNING AND POLICY RESEARCH
Year:2018 | Volume:4 | Issue:12|Papers Count:7

Growing demand for electricity, reduction of fossil fuels, pollution from fossil fuels, and the importance of energy security have made it essential to plan for the use of alternative power generation technologies. In this paper using a mathematical programming and power industry data, the optimal share of different technologies for power generation consists of combined cycle gas turbine, steam, gas turbine, small wind, big wind, small photovoltaic, large photovoltaic, solar-thermal, small hydroelectric, large hydroelectric, nuclear and geothermal has been determined during 2016-2040. The purpose of the mathematical modeling is to determine the combination of possible supply options at the lowest cost so that they are able to meet the energy demand. The results showed that the share of gas consuming technologies will decrease dramatically, replacing mainly with renewable technologies. Solar and wind power plants will be the most important renewable technologies and will have a significant share in the last years.

The amount of gas lift from the common field of South Pars highly depends on the pattern field development the by each party. This paper models the optimum production of gas from a reservoir block of the South Pars field and analyzes the effects of the economic parameters on the optimum path. Dynamic programming has been used to solve the optimization problem. To solve the problem numerically, state variables have been considered as discrete variables. According to the results, economic parameters including projected path of natural gas prices and the government discount factor play important role in determining the optimum path of gas production from the field. Therefore, for the gas field under investigation, despite being a common field between Iran and Qatar, the maximum potential production by the field is not necessarily the optimum production for the field. In this way, maximizing the return of the reservoir is not necessarily equivalent to maximizing the recovery factor of the field. Accordingly, maximizing the economic return should be considered in the development of hydrocarbon fields.

Technological innovation system and the multilevel perspective are the concepts that have been considered as systematic tools for assessing technological development problems and the study of technological changes. Technological innovation system has been criticized by researchers for being intrinsic and insufficient attention to macro factors. The multilevel approach is considered as a complementary concept that is capable of examining macro factors. Hence, in this paper, based on the multilevel approach, the macro factors affecting the technological innovation system and the path of technology development and how they affect them, was investigated. After identifying the major factors influencing the innovation system, the importance of each of them was determined by empirical study of these factors in the technology innovation technology in Iran, using ISM model and MICMAC method. The results show that government policies, oil crises, economic growth and recession are the main factors behind the macroeconomic framework that are important and influential on Iran's photovoltaic technology innovation system.

One of the most important challenges for the future energy supply of Iran is its dependence on oil resources and underdevelopment of renewable energies. In recent years, biofuel has been widely used as a substitute for fossil fuels around the world. Although the production of biofuels from food crops has been proved to be economically viable in some countries such as Brazil, due to its negative side-effects on agricultural markets it has been facing practical limitations. An alternative to solve this problem is using non-food crops such as corn pods to produce fuel. Urban wastewater containing a significant amount of lipid that could be used to produce biodiesel has grabbed a lot of attention in recent years. Moreover, this would partly solve the problem of sewage sludge burial which is a serious concern in wastewater treatment plants. In order to study the deployment of such fuels, this paper focuses on the design of a supply chain for the production of fuel from wastewater, which optimally integrates all supply chain stages including the supply and transfer of wastewater from refiners, converting them to fuel and distribution of fuel. Given the nonlinearity of the resulting model, exact algorithms fail to solve it. Therefore, a hybrid meta-analysis model based on GA and PSO algorithms has been developed. The hybrid algorithm has proved to be superior to GA and PSO algorithms. The results also indicate that although the fuel from wastewater is not currently cost competitive, but with removing the subsidy of fossil fuels in the future and improving the conversion rate of wastewater to fuel, it can compete with alternative fuels.

In this paper, the biogas produced from a fermentation livestock waste tank with 443 cubic meter volume, in an animal farm in Iran is investigated. The farm has 3055 dairy cows and the produced biogas is supposed to be used to run a CHP system. Every day 30 cubic meters of livestock is processed in the digester. Using the developed model and data obtained from the farm it was found that, the monthly 53910 cubic meter of produced biogas can operate a 350 kW dual fuel compression ignition engine CHP system. The annual cost saving, percentages of system profitability index and payback period are 1142. 2, 34% and 3. 7 year, respectively. Finally, a sensitivity analysis is carried out to show how the profitability of biogas CHP plants would vary due to changes of some key parameters such as prices of diesel fuel, electricity and electricity buyback. It should be noted that this study is carried out for the year 2017.

This research aimed to investigate the greenhouse gas emissions (GHG), energy consumption and production costs of dominant citrus produced in Mazandaran province of Iran. The relationship between input and output energies was investigated using the Cobb-Douglas model and sensitivity analysis. The results showed that two inputs including chemical fertilizer and diesel fuel with a share of 48. 50% and 16. 90% were widely consumed in the production of energy resources. Two inputs of animal manure and diesel fuel with 43. 30% and 18. 50% had the most greenhouse gas emissions in citrus production. The results of the sensitivity analysis showed that increasing 1 MJ in energy inputs, the machinery and fuel inputs had a positive effective on citrus yield, respectively. The results of economic analysis revealed that three inputs of human labor, chemicals and chemical fertilizers were allocated the highest of variable costs as 39. 32%, 28. 51% and 22. 89%, respectively. In order to improve the sustainablility of citrus production, some practical solutions are suggested.

Achieving high productivity and efficiency in the electricity distribution industry is one of the main missions of Power Distribution Companies in Iran. The main problem in incentive regulation of Power Distribution Companies to fulfill this target is to develop an appropriate benchmark for efficiency and productivity growth dubbed as "X-factor". This paper aims at measuring X-factor for the Iranian power distribution industry. Data of Power Distribution Companies for the period of 2003-2014 and a DEA model including desirable and undesirable outputs and controllable and uncontrollable inputs have been used. According to the results, efficient companies must improve their total factor productivity at an annual rate of 3. 06 percent; and inefficient companies most improve it at higher rates. The maximum X-factor is 0. 0703 percent belonging to Power Distribution Company of North of Kerman Province, meaning that the Regular.