نشریه انرژی ایران
سال بیست و سوم شماره 2 (پیاپی 87، تابستان 1399)

In recent few years, some endogenous and exogenous barriers caused different challenges in oil and gas project financing. Since appearance and development of innovative ideas such as DLT and blockchain in financial business models, this methods are replacing with traditional models. A blockchain is a decentralized, distributed and oftentimes public, digital ledger consisting of records called blocks that is used to record transactions across many computers so that any involved block cannot be altered retroactively, without the alteration of all subsequent blocks. By storing data across its peer to peer network, the blockchain eliminates a number of risks that come with data being held centrally.  This idea has resolved the problems face economic firms in financing methods. Some international companies had issued oil – backed cryptocurrency for financing oil and gas upstream projects. This paper focused on financing Iranian oil and gas upstream projects by using oil – backed cryptocurrency in the form of conventional contract models. As the result, using this method will improve conventional oil and gas contracts fiscal regimes’ efficiency.

Three natural pigments including wild iris, black pomegranate bark and black grapes were used as sensitizer in dye sensitized solar cells (DSSCs) based on TiO2 nanoparticles. The results showed that the DSSC made of black pomegranate bark was more efficient than the other cells due to its strong bonding with TiO2 nanoparticles. Longer electron lifetime, lower electron recombination, and lower internal resistance were the other causes of this improvement. These factors produced greater efficacy (energy conversion efficiency of 1.70%, short circuit current density (JSC) of 4.08 mA/cm2, open circuit voltage (VOC) of 0.541 V and Fill Factor of 77%) in DSSCs sensitized with black pomegranates bark. Whereas, wild Lily pigment with corresponding values of 0.59%, 2.122 mA/cm2, 0.331V and 84% respectively, had the lowest efficiency. Also, black grape pigment sensitized cell with average conversion efficiency of 1.41%, current density of 4.57 mA/cm2, open circuit voltage of 0.377 V and Fill Factor of 82% had moderate performance.

Compared to the conventional methods, Artificial Neural Networks (ANN) are considered to be one of the reliable tools for modeling of complex phenomena such as demand. Aim of this study is to provide a model for gasoline demand in transportation section of Tehran metropolis through multilayered perceptron neural network and using the presented model in analyzing the sensitivity of the model to the input variables and forecasting gasoline demand. Seven social and economic indicators are considered on a monthly basis within 2010-2016: fuel price, population, median household income, Gini coefficient, hybrid/gasoline cars ratio, price index of goods and services, and average vehicles lifetime. The average percent error 3.8% and 4.6% for the training and test data were obtained respectively. Sensitivity analysis results showed that, hybrid/gasoline cars ratio SX6F= -2.580, population of Tehran SX1F= 1.596 and average lifetime of the vehicles SX7F = 0.698 have greater influence on gasoline demand in transportation section. Fuel consumption was predicted by three different scenarios of moderate, pessimistic and optimistic by 2022. The prediction results showed that in case of the continuation of the current trend of the descriptive variables of the model, gasoline demand in Tehran transportation section will be increased by 2022. Finally, the result of projection of the gasoline demand is presented based on three scenarios for future 48 months (4 years). These scenarios are based on the 3 baseline, pessimistic and optimistic views illustrating the demand of gasoline by 2020.

Today, how to use home energy is one of the most important fundamental challenges of modern societies, which raises the need for efficient use of energy. The purpose of this study is to investigate the social factors affecting household energy consumption in rural areas of Sari city in Mazandaran province. The method of this research was survey and data were collected using a questionnaire. . The statistical population of the study includes all residents of villages in Sari city in 1399 and using multi-stage cluster sampling method, the sample size based on Cochran sampling formula, 400 people has been met. Spss 22 software was used for data processing and descriptive and inferential statistics were used for description and analysis. In this research, Triandis theory of interpersonal behavior has been used. The results showed that household energy consumption has a significant and direct relationship with the following variables: Environmental beliefs, individual evaluation, formal norms, informal norms, Environmental responsibility, self-perception, feeling, habit of supportive behaviors and environmental conditions. Also, the results showed that the variable of habit to support behaviors is one of the most important and effective variables on home energy consumption, which had the most direct effect of 0.371 and a total effect of 0.586 in path analysis.

One of the methods for increasing the gain in the photovoltaic systems is using the solar tracker system which during the whole of day, align the solar panels in the proper position with respect to the sun position. In this study, a solar tracker in the form of smart light curtain was designed and prepared. This simple and smart tracker detects the direction of the sun radiation by using three photocells, regulates the motor to rotate and finally, arranges the solar panels in the possible proper position relative to the sun light. The performance of this tracker with its equipment was investigated in different conditions and the solar panel direction. The results showed that by using this system, the accessible voltage values from the solar panels can be achieved. The designed device was able to regulate its orientation to the sun light direction with the approximate good precision. The produced voltage by the plates in the automatic orientation state compared to the fixed one in the easternmost, the most central and the westernmost positions, has increased by 39, 3 and 31%, respectively; so that in the most of day hours, it has been in the maximum values. The deigned system has the capability to scale up and commercialize in the buildings.

The activities of human civilization have imposed a high burden on the environment since the beginning of history on a global scale. That is why energy producers and consumers need to think deeply about the role that energy plays to achieve sustainable development. In this context, the maintenance of the environment, which cannot be replaced, should be taken into account precisely. Rising energy prices and market volatility, industry towards the use of energy management systems has led in order to compete reliable. Pulp and paper industry is not exception from this rule, Because the production of paper and paperboard demand is rising significantly on a global scale, that These factors lead to increased energy consumption and greenhouse gas emissions such as CO2 in this sector. In this context, a review of previous research and integrate them with the views of the experts, new methods for selecting the most appropriate technology in different sectors of the pulp and paper plant are provided.

This paper aims to analyze the implementation of smart meters implementation based on the value engineering integration approach and the AHP hierarchical ranking method. Value engineering strives to identify unnecessary functions by identifying product or project functions and by removing them to focus on other ways that they can fulfill the essential functions. To this end, in this study, first, by examining the literature and theoretical foundations of research and supplementing information on existing smart electricity meters and existing implementation methods, we examine the processes of doing value engineering work to optimize life cycle cost savings. Save time, improve and improve quality, solve existing problems and optimize the use of resources. Then, by taking into consideration the experts and stakeholders of the electricity industry of the country, first the criteria and sub-criteria for measuring the methods and processes of implementing smart metering were summarized. Prioritization and sensitivity analysis of the final ideas for the implementation of smart meters after their development were carried out using Expert Choice software. Taking advantage of the results of this paper, based on a holistic approach to the hierarchical and value engineering approach, will lead to the improvement of the smart meter implementation project.