فصلنامه پژوهش های سیاستگذاری و برنامه ریزی انرژی
سال نهم شماره 1 (بهار 1402)

Pakistan, with its large size and large population, is a target market for the export of goods and services. The existence of many borders between this country and Sistan and Baluchistan province in Iran is a suitable competitive advantage for the country. Also, the lack of proper relations with another neighboring country, India, as well as the unstable situation of Afghanistan, another neighbor of this country, can be an advantage for our country in exchanging goods and services with Pakistan. The suitable climate of Sistan and Baluchistan province is a suitable process for the construction of solar power plants and exporting the country's electrical energy from this unlimited and renewable source. In this research, using the capabilities of ArcGIS software, the most suitable places to install solar panels in the cities of Mirjaveh, Pishin and Rimdan have been determined, and the amount of energy produced in these pieces of land has been estimated using PVSOL software. The output results of the simulation have shown that the installation of panels in the east-west direction in these positions can lead to the establishment of 2 MW solar power plants per hectare of land and the annual export of electricity from this production is more than 400 billion Rials per year. Every hectare of installed solar panels generates income. In addition to sustainable development and employment in Sistan and Baluchistan provinces, this will lead to a reduction of social problems and an increase in security.

Optimum site selection for a solar power plant according to the opinion of connoisseur experts using multi-criteria decision making models and in GIS environment can play a significant role in the expansion of sustainable development. Therefore, the purpose of this study is to identify the suitability of lands for the construction of a solar power plant using AHP model, remote sensing resources and GIS techniques in Andimshek city located in Khuzestan province, Islamic Republic of Iran. For this purpose, 12 criteria that were important from economic, environmental and security aspects were weighted by AHP model, then linearly standardized in the GIS environment and finally combined weighted linearly together (WLC). The results indicated 8.68% (4933.72 hectares) of the study area have an excellent degree of suitability for constructing of a solar power plant. These lands are mainly located near of Andimeshk city. Also, the results indicated the distance from industrial/military regions and the distance from the railway network have the most positive and negative correlation with the suitability map of the solar power plant, respectively.

This research focuses on the effect of passive methods in the field of energy storage, produce energy by using renewable energies, and also to achieve the construction patterns of residential buildings in the climate conditions of Shiraz, with the aim reducing energy consumption. Statistics show that in Iran, fuel consumption in residential and commercial buildings with an average annual growth of 7. It is about 2.37% of the country's total fuel consumption. One way to minimize energy consumption in this sector is to increase the role of zero-energy buildings. Zero-energy buildings provide technical ways to consume less energy in buildings. These buildings are designed and built so that all or a large part of these provide the energy they need through the combination of energy saving and the use of renewable energy technology. In this research, after studying the climate condition of the city of Shiraz, a building in the Energy Plus software, the simulation and climatic data of the Shiraz station was introduced to the software. To achieve the most optimal conditions of energy consumption in the climatic conditions of Shiraz, each of the building elements Residential was optimized. The simulation shows that it is possible to reduce the energy consumption of the building by using passive building materials and designs, including double-glazed glass, Wall insulation, etc. On the other hand, by using solar energy, using pvsyst software, you can supply the energy needed by the building.

Considering the importance of investigating this issue, this research, focusing on the transportation sector, has estimated the return effect of improving energy efficiency (gasoline and diesel) on carbon dioxide emissions using the country's energy balance sheet data from 1367 to 1398. An ideal demand function (AIDS) and the method of apparently unrelated regressions (SUR) have been used to estimate the elasticities of demand functions. In the scenario of a 20% increase in energy efficiency, the return effect of the country's gasoline and diesel has been calculated between 65% and 73% (with an average of 68%). The 20% improvement in energy efficiency (gasoline and diesel) is again offset by higher consumption of gasoline and diesel and increased carbon dioxide emissions. In addition, the application of the self-explanatory vector model with time-varying coefficients (TVC-VAR) to investigate how the explanatory variables affect the return effect shows that the coefficients of the variables of urbanization growth and the growth of the number of vehicles in the fleet are positive and fluctuating over time. Also, the influence of the coefficients of the real price of gasoline and the real price of diesel has been negative and fluctuating over time. This key finding shows that the decrease in the real price of energy carriers over time increases the return effect. In the continuation of the sensitivity analysis of the rebound effect of carbon dioxide emission in the transportation sector of the country under the alternative scenarios of energy efficiency of the transportation sector.

Due to the trend of increasing demand for electricity consumption, the use of current fossil fuel-based electricity production technologies has led to frequent blackouts in the summer and fuel burning in the winter. Therefore, the use of renewable energy sources and especially the construction of solar power plants can be a solution to end the blackout and fuel burning crises. The purpose of this research is the multi-objective optimization of the allocation of solar power plant construction to meet the electricity demand. In the objective functions of the problem of system costs, the amount of disturbances in the lines and the amount of greenhouse gases were minimized, as well as the amount of covered areas was maximized. In this research, the LP metric method has been used to solve the problem of multi-objective optimization in GAMS software. In order to validate the presented mathematical model, the correctness of the presented model was checked by GAMS software.Then, by presenting a numerical example, the complexity of the problem, the effectiveness of the multi-objective genetic algorithm in small and large dimensions were investigated. Finally, a case study regarding the construction of a solar power plant in Kashan, Aran and Bidgol region was investigated  and  According to the given information and the input data of the problem, the situation of the candidate areas for the construction of solar power plants was determined and Also, different areas of demand were assigned to the built solar power plants.

Reducing CO2 emissions is one of the most critical research frontiers. Additional oil recovery through CO2 injection can play an important role in stimulating carbon sequestration and storage and help earn additional oil revenues. This article is paid, for by building a model of electricity production and carbon emissions from the country's thermal power plants, to identify and feasibility of carrying out the CO2-EOR project through the transfer of carbon from power plant activities through a dedicated pipeline and injecting it into oil fields. This model, which has been applied using system modeling tools to better understand the complexities of the studied problem, with the design of the main sub-systems of thermal and renewable electricity generation and the examination of the relationship between these sub-systems preliminary economic analysis, provides a plan for the feasibility of the project. The research results, while confirming the acceptable success in achieving environmental and economic goals, emphasize the need to conduct wider and deeper research and pay special attention to this approach as an outstanding opportunity to achieve the country's sustainable development goals.

A precise selection of suppliers for the oil industry and oil products requires consideration of essential and efficient criteria and sub-criteria, as well as the relationship between them. Supplier selection aims to identify suppliers with the most significant potential to provide customers with materials, machines, and spare parts at reasonable prices for the foreseeable future. In order to accomplish this, suppliers must be monitored according to the criteria that customers desire. This paper presents a stable method for evaluating and analyzing suppliers, and supplier selection problems are solved by combining Dematel fuzzy decision-making experiment and ANP[1]. Using a new approach, this study proposes a solution to the problem that enables decision makers to minimize the negative environmental effects and maximize the positive social effects while maximizing the supply chain's commercial performance by choosing a sustainable supplier. At first, the effects of the decision criteria are calculated by Fuzzy Dematel. Then the weights of each criterion related to sustainable supplier selection are extracted by the ANP method. It has been concluded in this study that when selecting suppliers for the oil industry, decision-makers should pay attention to both financial indicators and environmental indicators.