Sharif Digital Repository

The energy section has a significant share in the emission of environmental pollutants. Based on the recent investigations about 80 percent of greenhouse gases are emitted into the environment from this sector. This present research has focused on estimating costs of pollution control, using the energy system model. In order to have a better understanding of the relationship between energy and environment, the reference energy system for Guilan Province has been developed; then by having energy demand data, historical capacity data for each technologies and potential of energy resources as well as, the development of provincial energy system has been studied. After the model verification and... 

Estimating electricity demand elasticity in different sectors has been an essential research topic. Considering the fact that pricing electricity in various countries does not follow the same rules, many econometrics methods have been developed to estimate this crucial parameter. Electricity demand elasticity is defined as the percent change in electricity consumption in response to one percentage change in electricity price. Having a correct estimate of this parameter would help policymakers to price electricity properly in order to reach desirable goals in electricity consumption optimization and many other aspects of electricity consumption. In Iran, Tavanir Co. which is a subsidiary of... 

In this thesis, an optimum structure of electricity supply system will be presented that consumer and producer interests are provided in order to reducing greenhouse emissions in achieving targets Paris Accord. So, at first, subsidy of fossil and renewable power plants were determined with considering Iran’s energy rules and applying variables such as efficiency, FOB price of oil and natural gas, inflation rate, energy conversion price and FIT in renewable power plants. At second, electricity price will be estimated by System Dynamics (SD) method and Pay as bid pricing mechanism in energy market on years between at 2018 to 2030 (time period of Paris Accord). Based on the subsidy of fossil... 

Heating demand required for greenhouses is mainly met by fossil fuels. On the other hand, anxieties over usage of fossil fuels have led the societies to move toward renewable energies. With this in mind, the purpose of this research is to analyze using both solar energy for satisfying the heating demand of greenhouses and heat storage for compensating the intermittence of renewable energy.Considering the mentioned points, in the current research, a linear optimization framework has been developed for design and operation of energy systems including long-term heat storage to meet heating demand of greenhouses. The objective of this framework is to minimize annual cost. The developed method... 

The purpose of this study is to develop a new optimal solution method for controlling the greenhouse climate and minimizing energy demand for heating and cooling the greenhouse. As greenhouses move towards more advanced structures and technologies, the need for advanced control will be more important in order to reduce energy consumption. More comprehensive and accurate mathematical models are needed for complex systems, multiple inputs and multiple outputs to make system behavior perform better and more efficiently. In this research, a new method has been developed for optimal control of the greenhouse and a specific greenhouse climate model is used which is based on optimal closed loop... 

The rapid increasment of energy carriers and investment expenses in recent years, has increased the costs of energy demand and attracted those interested in consume reduction and efficiency using modern cutting-edge technologies. This research intends to design a general framework for optimization and energy and water demanding management studies in a sample region, regarding the new concept, energy hub.Thus as the first step, the existing industries and technologies with their thermal and electrical demands is considered as the first hub and wastewater treatment plant with its other equipments and thermal and electrical demands is considered as the second hub. The main issue in the modeling... 

According to increasing energy demand in Iran and the world, the role of natural gas as a relatively clean and cost-effective source has received more attention. Given the high share of the residential sector in the country's natural gas consumption, providing a model for forecasting the demand of this sector is of great importance for policy makers and decision makers in this field. In the present study, we employ three popular methods of machine learning, support vector regression, artificial neural network and decision tree to predict the consumption of natural gas in the residential sector in Tehran according to meteorological parameters (including temperature, precipitation and wind... 

The water and energy demand increase as the population grows. Increased usage of energy leads to scarcity of available resources and limited absorption capacity of environment. Development of efficient and environmentally compatible energy conversion technologies are conceived as an important option for resolving pressing challenges. Compatibility with environment requires considerable reduction in the share of fossil fuels and efficient utilization of renewable energy sources. Hence, development of high-efficiency solar energy systems is becoming an important challenge in the energy sector. The present study is involved with development an integrated solar system based on the application of... 

Abstract In this study, by using panel instrumental variable quantile regression method (IVQP) and household budget data during the years 2011-2018, income elasticity of Housing energy has been estimated at different levels of energy expenditure. This method helps to study the whole energy expenditure distribution instead of focusing on the average effects. The study results show that income elasticity has a downward trend with increasing energy consumption quantiles. In other words, households with higher consumption have less income elasticity, so that the income elasticity is estimated for 10, 90 percentage, 0.47, and 0.32 quantiles, respectively. Also, in another part of the research,... 

Electricity consumption has increased dramatically in recent decades, and this increase has severely affected electricity distribution. Therefore, forecasting electricity demand can provide a precondition for distributors. Predicting power consumption requires many parameters to be considered.In this research, machine learning, and deep learning methods such as recursive neural networks, long short-term memory networks, etc., as well as the ARIMA model will be used. These models have been tested on the London Smart Measurement Database. In order to evaluate the capability of the models in forecasting electricity consumption, each has been used to predict the electricity consumption of a... 

Given the growth of the world's population along with the increase in the percentage of urban population by 2050, the way of responding to food consumption will change in the future. Controlled Environment Agriculture will largely account for future food supply. Vertical Farming is one of these systems. But despite the efficiency of these systems in terms of land and water and also not being affected by weather conditions, the main challenge in these systems is the consumption of energy use per unit of crop production. The cost of energy is about 25 to 40 percent of the total costs. The purpose of this study is to develop an integrated dynamic model for the determination of vertical farm... 

With the daily increasing demand for energy, we are facing many crises, such as environmental pollution and global warming, etc. Geopolitical issues can also lead to problems for some countries in reaching the energy demand considered in their development plan of them. For this purpose, a part of the global research is focused on removing these obstacles. One of the methods that can be used to produce cleaner fuel, or more precisely "biofuel", is the gaseous fermentation of synthesis gas by microorganisms and algae. A rod-shaped, anaerobic microorganism called Clostridium ljungdahlii uses synthesis gas for its reproduction. In other words, this bacterium can ferment carbon monoxide, carbon...