نشریه انرژی ایران
سال بیست و دوم شماره 1 (پیاپی 82، بهار 1398)

The important defect of the previous  models , is assumed that consumer behavior is based on logic and with a rise in the price their consumption decreased and they accurately have no problems with their control. However, various parameters such as lifestyle, habits and emotions and something like that can be effective. In this paper, we use the new model called the OLG model and the CRRA function, which is one of the economists' favorite functions, to solve these problems with the help of the theory of consumer choice and its two important tools, the utility function and the budget constraint. In order to overcome the problem of existing models, the above three coefficients ρ1 and ρ2  (rate of time preferences) and θ (Constant Relative Risk Aversion) are obtained that show the lifestyle coefficients and the tendency of each household to transfer and reduce load. In this study, it was determined that by setting the Constant Relative Risk Aversion and the consumer rate of time preferences, in addition to reducing the consumer cost, the flat load profile will be created. Also, through this model, the inappropriate performance of the TOU demand response was demonstrated in Tehran.

In this investigation, by the time series data of exchange rate and petrochemical industry stock index in the Tehran Stock Market from March 2009 to April 2019, a new Hybrid Model (resulting from the use of Exponential Generalized Autoregressive Conditional Heteroscedasticity, EGARCH, Model and Markov Switching Regime Model) is used. The results of study, in addition to confirming the idea of ​​using the Hybrid Model, the MS-EGARCH (1.1) framework, have illustrated that relying on the mentioned framework that is based on the results of Aloui and Jommazi (2009) study, provides a situation based on which the risk of a time series can be more accurately analyzed. This way, the assessed risks can be divided into two regimes include High-Volatile and Low-Volatile; consequently, examining the impacts of effective factors on the risks that can be investigated with more efficiency. Based on this analysis, the impacts of foreign exchange market movements on the risk of investment in the petrochemical industry have been far higher during the high-volatile periods than the low-volatile one.

The purpose of this study was to rank the obstacles to the establishment of smart cities projects in terms of energy in Iran, based on the DEMATEL technique. The purpose of this research is applied and is descriptive-survey based on research method. The statistical population of the study was senior managers and experienced experts in the Tehran Electric Power Distribution Company and the gas company of Tehran province. The sample consisted of 20 individuals and the sampling method was census. Data were collected using a questionnaire and analyzed using DEMATEL software. The findings on the main question showed that financial barriers with R + J equal to 14.81 have the highest interaction (first priority) and political barriers with market R + J equal to 11.87 has the seventh priority on the rate of interaction (influence and impact). In specific questions, the component of "non-committal and political support - local in the long run" with R + J value of 40.92, has the highest interaction among the political components and the market, the component of the "lack of institutions / mechanisms for the dissemination of information and non-disclosure" Public Participation "with the R + J value of 13.68, with the highest interaction among the administrative components (executive), the component of inadequate or insecure financial incentives with the value of R + J equal to 6.23 has the highest interaction among Legal components (regulatory), component of "risk and uncertainty as well as; economic crisis" with R + J equal to 23.83 has the highest interaction among financial components, the component of Problem K Renewal in residential and in use houses with a R + J value of 12.33 has the highest interaction among the technical components, the component of "lack of value and interest in energy optimization measurements" with R + J equal to 15.24 has the highest interaction among the social and environmental components. Finally, the "lack of awareness among the general public about the benefits of intelligent urbanization in terms of energy" with the R + J value of 9.79 has the most interacting between the components of information and informing.

In recent years, the use of modeling methods that directly utilize empirical data is increasing due to the high accuracy in predicting the results of the process, rather than statistical methods. In this paper, the ability of Artificial Neural Network (ANN) and Adaptive Fuzzy-Neural Inference System (ANFIS) models in the prediction of the thermal performance of Al2O3 nanofluid that is measured by thermal resistance is investigated. The laboratory data was extracted from a valid paper that examined the thermal performance of Al2O3 nanoparticles in an oscillating tube. For modeling by ANN, a multi-layered perceptron network was used and for ANFIS a sugeno fuzzy model was used that are both the most accurate and most commonly used modeling methods. Comparison of target values ​​with predicted values ​​by both models was highly satisfactory, and the correlation coefficient for both of them was more than 0.99, which indicates that the accuracy of these two models is high. Finally, the performance of both models was compared with each other, which was very good and close, but in general ANN showed better performance than ANFIS.

For managing the discharge of water resource, utilizing high precision measuring instruments and workers is necessary that can be lead to high cost on the governments. The purpose of this paper is to present a new approach that can provide a good estimation of the well water discharge without human intervention and the use of measuring equipment. In this research, 38 wells with suitable conditions (with different categories of pumping head) were selected in South Khorasan province, Iran. Then a mathematical equation for estimating the well water discharge in a confidence interval was obtained and developed by recording the data of water discharge and the energy consumption of the pump (during a time interval) and finally fitting them statistically to the selected wells. This new approach is beneficial to minimize human and equipment costs to control the discharge of water wells. This approach can be as a suitable and alternative method that guarantees the reliability of the system in some cases such as crashing the measuring equipment and etc.  The Proposed equation was verified on 162 wells (randomly selected in mentioned province) and according to the results, the error of this equation by considering all external error factors is between 5 % and 19.8% compared to the values measured by the water meter. The efficiency criteria of correlation coefficient (R) applied to evaluate the proposed equation for training and testing data was 0.89 and 0.802 respectively.

Optimization tools as a method have gained vast application to achieve best results in reducing buildings’ energy consumption. In this paper optimization tools in conjunction with energy simulation software, as a powerful mechanism in design phase are studied. This is an applied research in nature and evaluates the capabilities and limitations of optimization algorithms in the beginning of the design phase with the aim of reducing energy consumption in buildings. In this regard the most used softwares in building’s energy simulation and optimization are studied and compared to find and analyze their locus in the field and their gaps in optimization algorithms within design process and simulation. At first, the five most used software in design, energy optimization and simulation in buildings are defined through literature review. Then, several criteria are introduced to compare these software in terms of capabilities and limitations.  The results show that these methods have solved many problems during design and operational phases in buildings, but many studies show that there still is a meaningful distance between an optimized design and base design (pre-optimization). Additionally, findings represent that there is a wide distance between the requirements of designers in professional research and capabilities of existing tools. Also, the lack of education and skill creation in architectural society will result in limited usage of these new tools within the design process. This is one of the main problems in utilization of optimization during architectural design process. Then, extend of optimization knowledge at large scale in educational and professional fields considering the needs and abilities of architects is necessary.

Biogas is a proven and valuable energy source today for combined production of heat and electricity (CHP). In this paper, a novel CHP system installation based on a 500 kW micro humid air turbine (mHAT) in a wastewater treatment plant (WWTP) is presented and discussed. Furthermore, some considerations regarding an appropriate biogas treatment system and heat recovery module is discussed. The results presented in this paper show how the proposed biogas-fed plant can reach an electrical efficiency of 46.6 % and CHP efficiency of 81.2%. The impact of integration with WWTPs is beneficial where both biogas and required water for inlet air humidification are available.