فصلنامه پژوهش های سیاستگذاری و برنامه ریزی انرژی
سال هشتم شماره 4 (زمستان 1401)

This study aims to optimize the energy supply system of a greenhouse considering twelve different climate conditions in Iran. For this purpose, an integrated two-objective linear energy optimization model has been developed to control the inside temperature and provide the required heating, cooling, and electricity by receiving electricity, gas, and water. The mentioned goals are to minimize operating costs (taking into account the discount rate over twenty years) and the initial cost and minimize the deviation of the inside temperature from the desired value. The initial cost of energy equipment is the result of examining data from domestic manufacturers and obtaining the equipment cost curve. The analysis of the results shows that the best areas for greenhouses construction are Kerman, Tehran, and Arak, respectively, for which the total cost is around ten thousand dollars.

The growth and development of human societies has always been parallel to the production and consumption of energy. Rapid and sustainable development in any country requires establishing a dynamic and stable balance between technical, economic, social and environmental categories while taking into account conditions that do not cause risks or reduce opportunities for progress. Energy and clean water are two of the essential human needs, which have long been the concern of societies for sustainable supply of these resources. Currently, due to the limitations of fossil fuels, the limited resources of fossil fuels and the ever-increasing growth of energy demand, the increase in living standards, global warming and environmental problems have caused governments to use fossil fuels in their long-term plans. Reduce or eliminate and replace fossil fuels with renewable energy. Also, due to continuous droughts and lack of water resources, optimal use of water resources and wastewater treatment are of special importance as valuable resources. In this research, a floating photovoltaic solar power plant is used to supply power to the wastewater treatment plant. The cooling effect of water increases the efficiency of the power plant by about 5 to 15, and the power plant prevents surface evaporation by about 90% by covering the surface of water.

Photovoltaic energy, as a renewable energy, can generate electricity. Deployment of photovoltaic equipment in different areas is determined by the type of climate. The main issue with this system is energy efficiency and reduction of electricity generation costs. Systems engineering of photovoltaic panels to achieve such a goal is an optimization problem that in several areas and interdisciplinary can provide an optimal method to meet the challenges and meet the basic needs of research. Given the range of potential areas in this field of energy in the country, the proper deployment of photovoltaic panels can be a prerequisite for the production leap in each region. The study city of this study is Asadabad in Kermanshah province, as a cold and dry mountainous regions in the foothills of the Zagros. The simulation results show that reducing costs and energy efficiency, by considering the amount of radiation, provides an optimal controller that uses deep learning. The simulation results show that the most important factor in the Zagros region of Iran is the cost of oil. In addition, other factors such as carbon dioxide emissions, high technology exports, regulatory criteria and institutions and social criteria are also relevant.

The main target of this of this research is to present the general architectural sub-system model of household's gas demand and to identify different variables affecting gas demand. The factors and variables identified from the subject literature have been analyzed using metasynthesize methodology and appropriate classification and prioritization has been done through content analysis. The statistical population in this research consists of scientific research articles published in reputable scientific databases and centers. Among the 127 articles found in the period from 1992 to 2022 for foreign studies and 1382 to 1401 for domestic studies, 53 articles were selected for analysis. The articles were import to the MAXQDA software and the variables in the form of 98 codes and 437 Coded Segments coding and 79 variables were identified. Then; using Shannon's entropy, the Priority and influence of each variable was determined. After analyzing and synthesis the variables, finally 10 subsystems were identified in the form of 49 variables. The results of the research show that the important variables affecting to natural gas demand are price, price elasticity, temperature, technical and technological factors, per capita income, social factors and consumption history. In order to manage gas demand in the household sector, all sub-systems should be considered by policymakers and balanced development between these sub-systems, otherwise the implemented policies will lose their effectiveness in the short time.

The nature and structure of relationship between state, energy management and sustainable development are cross- cutting issues and play a critical role to deal with the problems of electricity consumption. Governance as a new perspective in public service is taken into consideration as a framework to describe and explanation patterns for electricity energy management with respect to those issues. Governance perspective is focused on reconsideration the role of the stakeholders in the process of public policy making. The aim of this article is to figure out, explanation and analysis some of the most important governance theories which can be used in electricity energy consumption management in order to reach the sustainable development goals in this sector. A meta – synthesis method has been used to a systematic review on some of the qualified studies which have been done during the years between 2001 – 2021, considering related topics. A conceptual model has been presented as result of this study which is based on the literature of governance perspective in electricity sector and the findings of this  meta-synthesis. This model proposed five distinct  roles for citizens (as society), five roles for state and two roles for private sector, by considering two main strategies for electricity management and three governance theories in order to reach the four main index identified for sustainable development in electricity sector by united nations development plan.

il markets are one of the most important international markets. Oil markets play an important role for Iran as an oil exporting country with a budget dependent on oil. Most of Iran's budget is obtained from the sale of oil. So, oil markets are one of the important markets that affect the budgets of countries that supply and demand oil. In this research, the spread of risk in international oil markets was investigated using complex network theory and Pearson's correlation coefficient for the time period from 10/1991 to 12/2021. According to the obtained results, the OPEC oil market has the highest amount of node power in spreading risk in the network of international oil markets And this node will have the most influence in the network of oil markets. The Indonesian oil market has the weakest node strength in the risk diffusion network in oil markets. The degree of weight of the nodes is the highest value for the Brent oil market and it means that the Brent oil market has the highest correlation with other oil markets in the network of oil markets. The node degree was the same for all the nodes of the oil markets. According to the results of the Pearson correlation test, there is correlation in the oil markets and the highest correlation in the oil markets is in the markets of Nigeria and Algeria and the markets of Norway and Algeria.

As an oil exporter and an important member of OPEC and an oil-dependent economy, Iran is also essential to the Iranian oil embargo and its impact on oil markets. The purpose of this study is to investigate Iranian oil on the oil market correlation network. The period of this research is 1-1991 to 12-2019 AD with a complex network method. According to the results of this complex network, the correlation between the Iranian oil market and other oil markets has decreased after the sanction on Iranian oil. In the complex network before the sanctions against Iran, the most weighted Degree related to the Libya oil market and the Indonesian oil market will have the lowest Weighted Degree. In the post-Iranian oil market volatility correlation network, the largest amount of weighted debt is related to the Indonesian oil market. The lowest amount of Weighted Degree is related to the Algeria oil market. There is a correlation between the volatility of returns for the Iranian oil market in the network after the Iranian oil sanction and the network before the Iranian oil sanction. before sanction Iranian oil, the Iranian oil market is most correlated with the Russia and UAE oil markets. After the sanction on Iranian oil, the most correlation between the Iranian oil market and the oil market of Oman and Russia.