نشریه مهندسی مکانیک تبدیل انرژی
سال دهم شماره 3 (پیاپی 37، پاییز 1402)

In this paper, a new biomass multi-generation system based on micro-CCHP using an absorption refrigeration cycle and a desalination system, are presented to increase the performance of the basic cycle and to reduce the thermal wastes. A thermodynamic comprehensive modeling was done on the proposed system. also validation of subsystems and optimization of the system was done by genetic algorithm method with EES software. The results show that the dehumidifier has the highest exergy destruction among the other components of the system. The impact of the various system parameters such as; Evaprator1 temperature, Ammonia mass fraction, Absorber temperature, Difference temperature of heater, Generator1 pressure and heat source temperature is also done on the performance of the system. The parametric study show that by increasing the evaprator1 temperature, the energy efficiency of the system is increased. The maximum amount of energy and exergy efficiency of the system is 74.2% and 47.7%, respectively that occur at the 750-740 kelvin of heat source temperature. The energy and exergy efficiency of the base and MOOD case is 68.7% and 44.32%, 91.87% and 49.3%, respectively

In this article, a new framework has been developed based on the modeling of the energy system and related greenhouse gas emissions, which aims to predict and provide a perspective of energy and environment correlation for economic sub-sectors under possible scenarios. Nexus modeling has been done by the bottom-up method using the Long-range Energy Alternative Planning (LEAP) software from 2016 to 2040. Demographic and economic data of Urmia watershed, which is one of the drivers of energy demand, was collected and used as a case study. The results based on the analysis of energy and greenhouse gas emissions under different scenarios have shown that the greatest potential for saving energy and reducing emissions is 27.76 million barrels of crude oil equivalent and 11.3 million tons of carbon dioxide equivalents respectively under the scenario of integrated policies. Analysis of the sensitivity of the total energy demand to social and economic changes shows an average increase of 3 and 2 percent per unit of increase in population and GDP. A cost-benefit analysis for productive measures under the mentioned scenario results in the maximum net present value if the interest rate remains below 8%.

In recent years, reducing energy consumption and greenhouse gas emissions in the building sector has attracted a lot of attention. As in other parts of the world, the construction sector in Iran also has a large share of energy consumption. As a result, low consumption and even zero energy buildings, as an alternative solution in solving this problem, have attracted the attention of scientists, researchers and policy makers. One of the main challenges in designing a zero energy building is to find the best combination of passive solutions to reduce consumption and optimize energy performance in the building in such a way that the energy performance of the building and the thermal comfort of the residents are not negatively affected. This article presents a method for multi-objective and multi-variable optimization based on building simulation, which is carried out in three main stages: building energy consumption simulation, two-objective optimization process and multi-criteria decision making for zero energy building design using renewable energy sources. Reproducible. The studied design parameters are: direction of the building, angle and depth and length of the protrusion of the shades, insulation thickness of external walls, temperature adjustment points for cooling and heating, ratio of window to wall area, heat transfer coefficient of windows and thickness of roof insulation. In addition, the considered renewable energy sources are: photovoltaic panels and wind turbines. In order to achieve a net zero energy building, considering maintaining the thermal comfort of the residents, a multi-objective genetic algorithm with non-dominated sorting has been used. Finally, in order to determine the most optimal answer in the Pareto diagram, the elimination and selection method compatible with reality has been used. The results show that climatic conditions and the appropriate selection of architectural parameters are very important and vital in reducing building energy consumption. Based on the results, the use of energy optimization solutions in Tehran leads to a 25.3% reduction in energy consumption. In addition, there is a significant potential for the use of photovoltaic systems in Tehran to provide energy for homes.

Nowadays different kind of active and passive methods used in order to reduce energy consumption and air pollution in buildings. Simultaneous use of phase-change material (PCM) and green roofs with triple-skin facades (TSF) and triple glazed windows (TGW) in residential buildings equipped with Building-integrated photovoltaics (BIPV) can lead to 70% annual energy saving. On the other hand, PCM type and applying methods in different climate conditions impacts energy saving in these conditions. So for the first time, in this research Multi objective optimization of a residential buildings equipped with above technologies was done by the help of genetic algorithm. Reduction of required heating and cooling loads was chosen as optimization’s objectives and three climate conditions of Iran was selected. Results indicate that maximum energy saving is 73.3%. Maximum Cooling load reduction is 92.2% which is happened in biome-dry tropical climate conditions. In addition, Maximum reduce in Co2 emission is 60.6% for Tehran.

Considering the importance of improving heat transfer in heat exchangers, the effect of simultaneous use of agitators and also zirconium oxide nanoparticles on the heat transfer of tubular heat exchanger is studied numerically. For this purpose, at first, a new type of incomplete conical agitator with two parallel rows of holes is presented. Then, using the computational fluid dynamics method, heat transfer equations have been solved in the range of Reynolds numbers 4000 to 24000 and also the amount of zirconium oxide nanoparticles from 0.01% to 0.2%. In order to increase the modeling accuracy, the nanofluid has been simulated in a two-phase form. The effect of parameters such as the number of agitators, the number of holes and the volume fraction of nanoparticles on the flow field, the average Nusselt number, the friction factor and the thermal performance coefficient have been investigated. The results show that the use of perforated agitators in the flow path leads to significant changes in the flow characteristics and heat transfer. Perforated conical agitators improve heat transfer by creating recirculation and separation currents in the presence of nanofluid as a result of disrupting the thermal boundary layer and causing more disturbance in the fluid flow during the tubular heat exchanger. The agitators presented in this research can increase the thermal performance by 76% compared to the smooth pipe if the parameters are determined properly. The maximum coefficient of thermal performance is 1.76 in the case of M=1, N=1 and Re=4000.

In the current research, a renewable system based on wind, solar, and geothermal energy was analyzed with a targeted combination of fuel cell units, heat pump, proton exchange membrane electrolyzer, steam turbine and reverse osmosis. Transient modeling and simulation of the proposed system was done using TRNSYS software. This system was designed and evaluated to meet the needs of a residential complex with 80 residential units and 320 people for electrical energy, cooling, and heating. A case study was conducted for the feasibility of setting up the proposed system in the coastal city of Bandar Anzali in Iran. Optimization of system performance was done by determining two objective functions of production power and system life cycle cost with response surface method and Design Expert software. Five parameters affecting the system performance including the number of wind turbines, number of solar panels, fuel cell capacity, steam turbine capacity, and proton exchange membrane electrolyzer capacity were selected as optimization variables. In its most optimal state, the system can reach a production power of 3036105.022 kWh and a life cycle cost of 781944.254 $. The environmental results showed that by setting up the system in an optimal mode in Bandar Anzali city and producing electricity at the rate of 3036.1 MW per year, it is possible to help expand 3 hectares of green space per year. It also helped reduce carbon dioxide emissions by 619.36 tons of CO2 at a cost of 14,864.74 $.