انرژی

The design and planning of cellular Manufacturing systems in most classical models is based on minimizing production costs or increasing producers' profits. With the expansion of production systems and the increase in demand for products, concerns about environmental issues and excessive consumption of non-renewable resources have increased. On the other hand, paying attention to workers and the safety of the work environment has been introduced as a vital issue in creating a sustainable Manufacturing system. In this article, a new multi-objective mathematical model for creating a sustainable cellular Manufacturing system is presented according to the mentioned items in order to minimize the production costs in the system in addition to optimizing the environmental effects of the Manufacturing system. In the following, the model was solved using the epsilon constraint method and various solutions were presented in the form of a Pareto front for decision making. Due to the NP-hardness of the proposed model and the inability of the GAMS software to find optimal solutions for large-scale problems, a non-dominant sorting genetic algorithm (NSGA-II) is presented to solve it. The results showed that the meta-heuristic method has reduced the solution time by at least three times compared to the epsilon constraint method; Also, reducing the level of environmental risks has led to an increase in production costs. Finally, the applicability of the proposed model in an agricultural equipment production workshop has been investigated as a case study.

Due to the increase in environmental pollutants, the damage to the ozone layer and the reduction of fossil fuel resources, the need to use renewable energy has increased. On the other hand, in many remote areas, it is not possible to provide electricity power or it will be very expensive. Therefore, due to the existence of favorable conditions for the use of renewable energies in many regions, promoting the use of these technologies in these regions can reduce fuel consumption and environmental pollutants, It also facilitates the provision of energy to many remote areas. In this research, the conditions for the use of wind and solar renewable energy in Jirande city of Gilan province have been investigated. The parameters of sunny hours, clearness index, possible of sunny hours, wind speed and wind power in the study area are evaluated and finally a plan for the use of these renewable energies for remote areas in this region is given. According to the surveys, the average monthly amount of daily sunny hours is estimated to be at least 6 hours during the day. The clearness index is also above 0.55 in most days of the year. Meanwhile, the possibility of sunny hours is also calculated as acceptable. By examining the data related to wind speed and power, the possibility of using this energy in 88% of the days of the year has been estimated

This paper presents a model-based technique for building retrofit planning. The approach is based on the building energy model. An algorithm has been developed to calibrate building energy model based on hourly data. The calibrated model is used to select candidate retrofit actions and assess the energy saving potential associated with each candidate action. The proposed technique has been applied for retrofit planning in Department of Energy Engineering (DOEE) at the Sharif University of Technology in 2015. An smart reading system has been also developed to capture the hourly gas consumption for DOEE. Building energy model for DOEE has been developed in EnergyPlus and calibrated using the proposed algorithm. A set of retrofit action has been selected and implemented in DOEE based on the proposed technique. The results showed that the average cooling energy use in summers was reduced by 20% compared to the 6-year average summer energy use before retrofit. The results showed that only HVAC control has more than 8% impact on cooling energy use.

Though 3D chips are a promising solution to deal with scalability problems at the integrated circuit level. However, the high temperature of these chips has increased the density of the chips due to increased power density, against three-dimensional or intermittent errors. On the other hand, the use of the fast vertical TSV connections in the three-dimensional integrated circuits opens up a new horizon for network design on the chip. In this dissertation, routers with vertical connections between the silicon provide the connection between the chip layers. Layers can be aligned vertically with TSV over a distance of several millimeters. Reducing wires will reduce the amount of power and delay, and ultimately lower the diameter of the 3DNoC. In this thesis, we study the heat loss in a grid on a three-dimensional chip by optimizing the TSV mapping. The number and location of TSVs is an effective parameter in the heat of new processors, which is very effective in reducing heat.

Electric power and power distribution are prominent infrastructures for economic development in any developing country like Iran. Also, the power distribution network is a very important supply chain that combines a variety of processes. Smart electrical energy distribution networks are one of the latest technologies in the world. The main goal of these networks is to provide reliable electricity, increase the reliability factor and network stability, and respond to the growing needs of customers with minimal damage to the environment, profit, and high efficiency. In the last three decades, the rapid evolution and prevalent adoption of information systems, distribution analysis tools, computational models, and more recently, the emergence of smart grid technologies have given utilities access to the data and tools required for improving these analyses and the possibility of increasing the efficiency of power distribution systems (by, for example, reducing losses and optimizing voltage profiles). Forecasting the future state of the network with the least error brings us closer to the smart network. Because electricity is a mortal product, a comprehensive approach to unplanned power extinction (outage) time is very valuable in preventing any power distribution losses. Various accidents disrupt (cause breakdowns in) the power distribution network, which can be repaired and restored without a hotline. One of the main reasons for customers' power outages is the blackouts in the distribution field, which are affected by technical and non-technical events in the electricity distribution networks. Forecasting these events and managing them can be effective in reducing unplanned power extinction (outage) time. The purpose of this article is to present a model for predicting the duration of unplanned power extinction (outage) and unsold energy based on the data recorded from 121 systems (controllers), the urban network of the three power distribution companies in Yazd province. The final result shows that the ARIMAX model(s) shows less error than the ARIMA model(s) and presents better prediction. Therefore, using exogenous variables in predictions and not being satisfied with the fluctuations of a variable can improve predictions. The model proposed for predicting unsold energy is ARIMAX(1,0,1)(0,0,0) considering the number of incidents and the time of unplanned outages as exogenous variables. The model also shows that in July 2022, the unplanned power extinction (outage) time of this network will be approximately ten hours and also the unsold power will be approximately 6 MWH. On the other hand, the community is without electricity and dissatisfaction has arisen, which lies in economic and social losses. Therefore, with this warning, managers should re-examine the factors of disruption and lack of electricity supply and think of measures to reduce these blackouts when planning for this month of the year

One of the common methods of removing iron oxide from the surface of hot rolled steel sheets is to wash the sheet with acid. The most common acid used in steel industry for this purpose is hydrochloric acid. One of the methods of recycling hydrochloric acid from acid leaching effluent used in steel industry is acid recycling method using fluidized bed reactor. To this end, the effect of this method on the reduction of g environmental challenges, an optimal use of energy, and an increase in efficiency and productivity in steel industry was investigated. In this research, the solvent extraction method as well as evaporation and crystallization method for acid recycling was proposed. The results showed that the solvent extraction method has low efficiency, requires strict system control as well as continuous monitoring; however, the evaporation and crystallization method with the least man power, energy consumption environmental pollution as well as with high efficiency has an acceptable preference. In the evaporation and crystallization method, 17.5% hydrochloric acid solution and iron chloride are recycled; such event has many uses and can be sold. The water from the evaporation and crystallization process can also be used as a product in the factory or used to irrigate the green space in the factory.

The process of roomchr('39')s air-conditioning system is used to enhance thermal comfort and to reduce energy consumption. Although most of the researches have concentrated more on flow rate and optimum temperature of inlet air, the present study software was used to obtain the best possible locations for inlet and outlet channels for 20 samples of room using Ansys Fluent. Three factors including ventilation efficiency, effective average temperature, and vertical temperature gradient were considered to find the best location for inlet and outlet port locations. As a result, model 20, where inlet channel placed in the middle of opposite wall from manikin and the outlet channel located at the bottom of the same wall, was approved. In this sample, the average temperature was 23.68; the ventilation efficiency was 2.36; and the average effective temperature was -1.01. Moreover, the analysis of rooms with area of 12 𝑚2, 16 𝑚2, and 20 𝑚2 showed that by increasing the area, the ventilation efficiency decreased by 11.86%, and by increasing the air flow from 0.045 to 0.134 m3/s, the average temperature room decreases 12.54%.

In this paper, a method for evaluating the impact of load response on microgrids is presented. Several different modes have been stimulated to better understand the problem. A hybrid optimization algorithm including gray wolf optimization algorithm and shark olfactory optimization algorithm to optimize the multi-purpose objective function under limited conditions and constraints. In addition, to determine the uncertainty in the production of renewable energy sources, the Monte Carlo method has been used to produce the scenario. The parameters considered in this method include technical parameters such as network losses, generation cost, and reliability index and voltage deviation. The proposed method is implemented using a hybrid optimization algorithm using MATLAB software on a modified 69-bus system, including wind turbines, solar power plants and energy storage systems. The results show that the proposed method will increase network productivity.

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.

Paying attention to the increasing concerns of global warming, environmental crisis and energy, International research and Development has extended to sustainable energy systems.In this research,Applied method for optimizing the installation space of photovoltaic system Due to the limited space in the buildings of the country's cities, As the effect of the shadow on the efficiency of the panel, The intensity and angle of radiation, In order to produce the maximum calculated energy, That using Meteorological data including sunny hours, cloudy and humid, cities in central Iran classification and Regression model of radiation intensity and sunny hours of each class were identified in SPSS simulation software.Five cities of Tehran, Ahvaz, Yazd,Gorgan and Ardabil were selected and their average radiation intensity was obtained.in order to Generating more photovoltaic energy and increasing the capacity of the distribution network,to minimize the space where the photovoltaic system is installed,Panel angle relative to horizontal surface, Reduce the shadow of each panel compared to the other panel,From the Bee Colony Metabolization Algorithm used in Matlab software and compared to its normal state,also simulation results In the optimal state, It is analyzed and presented with the installed system of electricity subscribers in Tehran. The results show with monthly recorded data of the designated photovoltaic system in Tehran, optimal panel installation space, service and maintenance, reducing shade increases energy production and capacity release and the stability of the distribution network becomes electricity.

The importance of energy in the sustainable development of societies and its role in the economic, social and political relations of today's world is indisputable. The availability and proper use of energy resources ensures the full development of any country. Because of the importance of this issue, the topic of energy literacy was introduced in science education in the recent years. Textbooks play an important role in conveying the concepts of energy resources, production of energy and consuming it. The purpose of this research is to analyze the content of the first-grade students' textbooks in terms of the amount of their attention to the topic of energy. The indicators were used to analyze the content of the textbooks are based on the Powers and De Waters definition of energy literacy. The data from the content analysis were analyzed using descriptive statistics, frequency and percentage of frequency. The results of data analysis show that the environmental issues and the importance of energy in the individual and social life of the people have not been paid much attention. Given the importance of the energy issue in the whole world and the limitation of non-renewable energy sources, such as oil and gas, their issues and problems, it appears this result is not desirable. The most focus of first secondary science textbooks is on the energy resource in the home, which is created a superfical view about main resource energy and does not create a general picture about issues and problems related to high energy consumption in the country. In the discussion of energy consumption, the hidden energy has not addressed, which is one of the main weaknesses of the first secondary science textbooks in energy education. Another noteworthy point is that the content of the first secondary science textbooks has paid little attention to the amount of inputs and exports, and the need for energy conservation.

Energy consumption is a significant factor in wireless sensor networks (WSNs) which are consists of so many tiny and battery-based sensors. These sensors are distributed in different environments to perform distinct duties and whenever they consume the whole energy of their batteries, some parts of the necessary data of the network or its efficiency can be missed. Recently, in order to enhance these networks, extra energy extraction nodes which can harvest the energy from the environment, are used between sensors and the base station. Due to the high cost of energy harvesting nodes, minimizing the number of these nodes without affecting the quality of the signals is an important aspect of the wireless sensor network design. Therefore, the challenge is determining the efficient number of energy harvest nodes and their coordinates. In this work, for the first time, the Imperialist Competitive Algorithm (ICA) as one of the most advanced evolutionary algorithms is used to determine the minimum number of the energy harvest node. Based on the ICA’s results, the K-Means algorithm is applied to clustering nodes. The simulation results show that the suggested method can improve the performance of the WSN by increasing its lifetime.

This paper presents a fault tolerant approach for overactuated-oversensed systems subject to multiplicative and additive faults. The main idea is to use a reconciliatory unit in charge to discover online the possibly faulty physical sensors and exclude their measures from the generation of the ”virtual” sensors. In the proposed approach, the energetic based approach has been used to estimate the actuator multiplicative faults. In the next step, an unknown input observer has been coupled with the energetic based estimator to estimate sensor multiplicative and additive faults. Finally, the control allocation approach has been used to reach the desire output. Finally, a simulation example is reported in details to show the effectiveness of the scheme.

In the present study, the energy and exergoeconomic analysis for all energy transmission systems from the primary energy source to the energy transfer from the building's envelope for a three-floor building with educational use is presented. The first step is to calculate the energy demand or the heating load required by the Carrier software for all the space. By writing the energy equations, exergy flows of the heating system and total exergy are calculated in different parts of energy dissipation and exergy, as well as the cost of each heating system component. The second stage identifies the undesirable thermodynamic processes of the system based on the determination of exergy losses and calculates the parameter Rex as the thermodynamic losses rate. The third step is to determine the most feasible reform based on the exergy-economic concepts, so that a parameter called the ECE is calculated as the effectiveness of the exergy cost for all energy transmission systems from the primary energy source to the energy transfer from the building's coatings. Consequently, the most energy dissipation and exergy is related to the production stage and are 188.80, 295.42 kW, respectively. Also, by calculating Rex and ECE, it is determined that hot water boilers and energy production stage need more to be optimized and improved.

Building is considered as one of the most effective factors in changing the environment and according to the energy balance sheet from 2005 to 2012, on average 17/38% of the total energy consumption of buildings is consumed in buildings each year. By acquiring some of the applied knowledge and responding to basic and environmental needs, we identify and investigate the sunken court yard trench element in traditional warm and dry climate homes, while maintaining past architectural values, explaining architectural criteria consistent with basic human needs.Therefore, the research method is a quantitative-qualitative-descriptive-analytical one using DT-982 thermal camera and several levels of flooring. It has conditions such as adjusting the ambient temperature to 15.2 ° C. By analyzing the findings and simulating two buildings, one of which lacks a sunken court yard and the other with a sunken court yard, we demonstrate in the design builder Program that the sunken court yard can save electricity by providing lighting, The heating and cooling system is 27%.

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.

The significant impact of information and communication technology (ICT) on Greenhouse Gas emissions has caused a considerable research interest in energy management of network devices in recent years. As the amount of power consumption in routers and switches is a function of their working frequency, one approach to energy saving is to adapt working frequency of such devices dynamically and proportional to their traffic load. This paper describes this approach in Software Defined Networking (SDN) framework by proposing a Mixed Integer Linear Programming (MILP) formulation for a network of FPGA based interconnected Openflow switches. The prerequisite information of switch power profile is obtained by running experimental tests. The proposed method is applied to an infrastructural dataset extracted from the standard SNDlib database. Simulation results show that frequency scaling technique reduces power consumption by more than 37% in comparison to other well-known power-saving approaches.

Abstract : The efficiency of a natural gas-fired aluminium melting furnace in a caster plant is examined using energy and exergy methods, to improve understanding of the burner system in the furnace and so that potential improvements can be identified. Such improvements not only reduce fuel consumtion, but also mitigate environmental emissions and impacts such as climate change. In this study, the energy efficiency of the Aluminum melting furnace obtained 10% and its exergy efficiency 6%. The results confirm that exergy analysis can be used beneficially to analyze and improve the furnace efficiency and that exergy efficiency is a more practical measure in reality. The insights gained through the assessments into the melting furnace are described and potential improvements indicated are discussed. By reviewing of results, It was suggested the solutions to optimize energy consumption include adding regenerative burners and regenerators, preheating ingots, using compressed natural gas, reclaiming heat from cooling water, and replacing combustion air. It is anticipated that the results will be of interest and benefit to designers of new and retrofit systems.

Today, energy and its consumption are the main strategic plan of organizations and also the development of urban transport systems by considering a variety of economic, scientific, industrial, climate and growing urbanization is essential. Analysis of past trends in energy is the key to predict future trends, with regard to the rate of development of metro, for planning and future-oriented macro economic policies.  in this research has been used to predict the energy consumption of Tehran Metro Line 1 from the GMDH Neural Network Model Which is capable of detecting and screening low-input input variables In the course of training the network and removing them during the exam period. and also Was compared To understand the accuracy of the prediction with the ARIMA model. in this research, was detected twelve variables affecting Tehran's metro energy consumptionand is considered as input variables of the model. The results indicate that The GMDH neural network model has a much lower error rate than the ARIMA model and has a higher predictive accuracy.