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Power plants are among the largest producers of GHGs. The fuel used in power plants is the main factor in the production of the emissions. Therefore, choosing a fuel that is environmentally optimal while being energy-efficient and economical is a key way to reduce GHG emissions. The addition of nanoparticles to biodiesel fuel not only improves the combustion efficiency of the fuel but also reduces the undesirable products. In this research, three supplementary fuels - fuel oil, diesel, and biodiesel-nanoparticles - are compared in terms of environmental, economic, and energy efficiency in a steam power plant. The changes in the power plant's self-consumption were measured by calculating the power consumption of the pump that delivers the fuel to the boiler. The results showed that diesel reduced the plant's efficiency by 0.00022 compared to using natural gas, which was the least of the other alternatives. The environmental analysis revealed that diesel produced the least amount of CO2 eq, but biodiesel-nanoparticle had a better CO2 footprint due to the higher absorption of CO2 in the cultivation phase of the raw material for biodiesel. The economic analysis for the fuels was carried out over ten years and based on the lifetime of the equipment purchased. Consequently, the total cost over the ten years for diesel was $967332.5161, which was $124475.8381 less than that for biodiesel-nanoparticle and $240935.3341 less than that for fuel oil. Finally, an overall comparison was made between the fuels using the AHP method. As the environmental criterion was the most important decision criterion, biodiesel-nanoparticle fuel was chosen with a marginal difference compared to diesel.

Regarding the growing demands for energy, depletion of fossil fuel resources, and the adverse environmental consequences associated with their utilization, especially global warming, it is imperative to increase the share of renewable resources within energy systems. During the summer season, the residential sector in Khuzestan province, Iran, experiences a significant surge in energy consumption. This elevated demand is mostly attributed to the region's severe temperatures, requiring the extensive use of cooling equipment. As a result, taking into account the high potential for solar energy in the nation, this research first uses TRNSYS software to calculate the cooling and heating loads of a residential area in the province of Khuzestan. Next, a solar-natural gas Combined Cooling, Heating and Power (CCHP) system is designed and modeled using Engineering Equation Solver (EES) software, with the goal of supplying the cooling load. Then, using the particle swarm optimization technique, the system's multi-objective optimization was completed. The results showed that a fuel consumption rate of 0.04274 kg/s is required in steady state conditions to supply a cooling load of 1446.2 kW for the region with 1000 m2 of solar collecting area. A total of 465.7 kW of electric power and 3336 kW of heating are produced. The system's energy and exergy efficiencies were determined to be 186.6 % and 27.81 %, respectively. Eventually, the findings of this study demonstrated that the proposed configuration has the potential to provide multiple positive outcomes with a high level of efficiency, and improve the share of renewable energy.

The increasing demand for energy and the efforts to meet this demand cleanly have drawn experts' attention towards renewable energy sources such as solar energy. In this article, a novel hybrid system consisting of a thermoelectric module for converting the heat from a solar module into electrical energy, coupled with a solar cell, has been utilized to maximize energy utilization. This unique integration of thermoelectric and photovoltaic technologies has been shown to take advantage of the fact that the thermoelectric module reduces the temperature of the solar module, consequently increasing its efficiency. The results of this study have been examined in five different cities and for five different climate types through three energy, exergy, and environmental analyses, which were conducted under two distinct scenarios. The PVSyst software was used to simulate environmental conditions and solar cell performance, while MATLAB was employed to code and connect the solar cell and thermoelectric modules. In the first scenario, by varying the thermoelectric merit constant and the intensity of solar radiation, it has been observed that the placement of the thermoelectric module increases the energy and exergy efficiency by approximately 5 % and 4 % respectively, and carbon dioxide pollution is reduced by 194 tons on a specific day of the month (July). Moreover, in the second scenario, by examining the hybrid system in the city of Ahvaz and determining the material and quantity of the thermoelectric and solar cell modules, it has been found that the energy and exergy efficiency of the hybrid system (in the maximum state) reach 20.12 % and 21.23 % respectively, in May. This system in the city reduces carbon dioxide pollution by approximately 41 tons on a specific day of the month (maximum reduction).

This article delves into the intricacies of waste management in Tehran, offering insights into the structured framework governing the control of solid waste materials. As collected, the average daily generation of municipal solid waste (MSW) in the region is 0.645 kg per inhabitant. Unexpectedly, the impact of socio-economic factors on processes such as garbage sorting, creating products from recyclable waste, and composting was shown to be comparatively weaker than that of supporting elements. The initial approach entails providing environmental cadres and the community with more comprehensive MSW reduction training, which will cultivate a nuanced comprehension of waste management. The second strategy focuses on amplifying information dissemination through mass media and targeted campaigns, emphasizing effective MSW practices. The objective of the third endeavor is to augment the quantity of environmental cadres, which will be comprised of community and local leaders, in order to inspire and direct endeavors to reduce MSW. The fourth and final strategy underscores the expansion and diversification of waste storages, positioning them as customer-centric institutions dedicated to environmental campaigns and training. Ultimately, the collaborative implementation of these strategies is poised to instigate a positive shift towards heightened community participation in MSW reduction practices.

Abstract With climate change concerns on the rise, finding efficient and sustainable ways to separate carbon dioxide from industrial gas mixtures has become increasingly important. Membrane‐based gas separation technologies offer a promising solution due to their low energy consumption, low emissions, and ease of operation. In this study, we dug deep into theoretical energy consumption and practical optimization strategies for CO2 separation using such technologies. Our results showed that CO2 separation can be achieved with relatively low specific energy consumption, ranging from 0.09 to 0.27 MJe/kg CO2, depending on feed CO2 concentration. By conducting process simulations, we determined the optimal feed gas pressure and membrane surface area required to achieve a CO2 absorption ratio of 90% (mol). We also analyzed the effects of CO2 permeation and selectivity on energy consumption and membrane area, revealing that increasing both can significantly reduce energy consumption, albeit with more membrane surface area required. Using seepage flow circulation was found to be a particularly effective way to improve feed CO2 concentration and reduce energy consumption. To optimize and improve the capturing process, we conducted exergy analysis in each of the five stages of optimization, reporting Cooling Utilities (MW), Heating Utilities (MW), and Total Utilities (MW) for each step. Our results showed that in the optimal mode, Total Utilities (MW) were reported as 228.1, highlighting the potential of membrane‐based CO2 separation for carbon capture and storage applications. This study provides valuable insights and practical strategies for achieving efficient and sustainable CO2 separation.

Nowadays, a significant amount of non-recyclable solid waste is buried, causing numerous environmental issues. In addition, today’s developing world has increased energy demand. The production of fuel from waste, also known as Refuse Derived Fuel (RDF), is the optimal solution for both issues mentioned. This study aims to produce usable RDF pellets from the residual waste of the Tehran Kahrizak waste center and examines the effect of variables including die temperature, retention time, and three additives with specified weight percentages (0.03% bentonite, 0.04% diatomite, and 0.03% zeolite) on pellets characteristics. The results indicated that temperature and retention time effects, and additives combination was significant at the 0.01% level for all factors. In general, greater temperatures and longer retention durations result in more reliable, higher-quality pellets, but they also cost more energy to create. Scanning electron microscopy (SEM) analysis revealed that pellets containing zeolite contained the greatest number of adhesion bridges. Furthermore, the addition of zeolite and bentonite increased the pellet density. For volume expansion, the synergistic effects of temperature and retention time duration were substantial. The rate decreased by 22.5% after the addition of diatomaceous. The pellets made at 110 °C resisted more than 150 min in water. At high temperatures, pellets containing diatomite additive became brittle, whereas zeolite additive had the highest toughness at all temperatures. All additives were moisture absorbers that increased the pellets’ moisture content. Among the additives, bentonite is the most absorptive of moisture. Additionally, bentonite increased the amount of ash by 17.1% and decreased the amount of volatile matter, whereas diatomite induced ash reduction. The addition of zeolite increased the fixed carbon content. The thermal value of pellets made from bentonite increased by 39.5% due to agglomeration processing. All additives decreased the pellet manufacturing process’ energy consumption. Zeolite had the most significant effect. In addition, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was used to select the optimal scenario in the current investigation. It was observed that zeolite and diatomite additives positively impacted the pellet, whereas bentonite had a negative effect.

Abstract Solar collectors utilize solar energy, a sustainable and renewable source, to cater to both household and industrial needs. This paper investigated the usage of mono and binary nanoparticles in parabolic trough collectors. This paper used multiwalled carbon nanotube/Fe3O4 nanoparticles as the additives to the collector heat transfer fluid (in Syltherm 800 oil) and also evaluated the performance implications of energy systems in six scenarios. A MATLAB‐based computational model is provided to investigate the influence of employing binary nanoparticles on a solar collector's performance. The influence of nanoparticle modifications and volume percentages on energy, exergy, economic, and environmental aspects is studied. Finally, the impact of nanoparticles on each of the four mentioned areas is examined. At the same total energy rate, in the best case, adding 4% by volume of Fe3O4 (Case 2) to the base fluid increases the valuable energy rate absorbed from 7.32 kW in the base state to 7.50 kW (2.5%). The carbon dioxide produced in the system life cycle by using useful energy is called EnergoEnvironmental, and the carbon dioxide produced in the system life cycle by using useful exergy is called ExergoEnvironmental. At last, the calculation of the parameters EnergoEnviroEconomic and ExergoEnviroEconomic are done, the penalty policy is considered, and the calculations are generalized to solar collector power plants due to the carbon dioxide cost policies.

Renewable energy sources are in focus for environment-friendly power generation when compared to non-renewable sources. Modeling an energy system of a statistical population can shed light on the possibilities and potential of using renewable resources. In this study, energy modeling of 4 provinces of Iran with different climates is done for 2020 and 2032. The lack of energy caused by seasonal climatic impacts is compensated for by using renewable energy systems. The modeling of three different scenarios is considered to indicate different policies in each energy system strategy. The energy system's past data is gathered and analyzed to predict future data, and then the 2032 energy system is modeled using EnergyPLAN. The results show that there will be a shortage of electrical energy in summers in hot & humid and hot & dry climates, while the energy shortage for cold and temperate & humid climates is the heating demand in winters. Three scenarios of business as usual (BAU), using maximum possible renewable energy (S1), and changing the structure of the energy supply system (S2) are considered with their specification. The results indicate that by using S1, 61.42 TWh of primary energy sources (PES), and by using S2, 136.7 TWh of PES consumption is reduced. Also, for the same scenarios, 29.98 Mt less CO2 is emitted for all climates. The climatic analysis illustrates that using solar in hot & humid and hot & dry, wind and geothermal in cold, and hydropower in hot & humid and temperate & humid climates produce the most amount of renewable potential which not only compensates the lack of seasonal energy but also replace 8% of the total energy needed, previously supplied by fossil fuels. Totally for the 4 provinces, 3250 MW of hydropower, 5625 MW of solar, 650 MW of wind, and 100 MW of geothermal energy are considered while other provinces with the same climate could benefit too based on their geographical specification.

Abstract A novel DC‐Excited Flux‐Switching Linear Motor (DC‐FSLM) is investigated in this paper, where a simple secondary is used as the machine stator. The phases and excitation windings are placed on the primary, which contributes to a low‐cost and simple structure linear motor with acceptable dynamic performance. The motor operation under dynamic load is analysed by a parametric Magnetic Equivalent Circuit (MEC), and the core saturation is modelled by the non‐linear reluctance of the flux tubes. Moreover, the end‐effect is considered by virtual zones at both entrance and exit ends of the primary. In the considered MEC, the model accuracy can be selected as desired as well as different DC‐FSLMs with various properties can be modelled. Finally, the machine capabilities and performance characteristics are discussed by simulation results, and validation is performed by the Finite Element Method (FEM).

Due primarily to environmental concerns, attention to renewable energy sources has increased significantly in recent years. Of these sources, solar energy and wind energy have received the most study. With the improvement in photovoltaic (PV) panels’ efficiency, photovoltaic (PV) panels have grown significantly in popularity among the various solar energy methods. One hybrid system that uses these panels is the concentrating photovoltaic thermal (CPVT) system. Throughout the present study, an analysis of energy, exergy, environmental, and economic (4E analysis) aspects have been conducted. In addition, the life cycle assessment (LCA) method has been used to evaluate the system’s performance. Moreover, the effects of the working fluid flow type regime and the concentration ratio (CR) have been evaluated. The results indicate that CPVT will have about 63% of the total energy efficiency and 9% of the total exergy efficiency. CO2 emissions for the system could cost as much as 20 cents a year in a worst-case scenario.

Incineration is a suitable method for municipal solid waste disposal; however, many developing countries have not yet effectively used incineration technologies. In some of these communities, the high humidity of waste is one of the primary problems. This paper aimed to evaluate the feasibility of generating energy from the incineration of MSW with auxiliary feed in the north of Iran. This study demonstrates how an incinerator waste-to-energy system is possible in northern Iran and provides major benefits by dramatically improving waste management. The total amount of waste and lower calorific values was used to estimate power and energy generation. According to the calorific value of the waste, a proper waste incineration system was designed. The results indicate that the estimated energy produced in the desired state is 62,000 MWh. Economic feasibility was evaluated using levelized cost of energy (LCOE), net present value (NPV), and internal rate of return (IRR). The NPV of this technology is estimated to be approximately 96.4 m$, and the uniform cost of the electricity unit is 0.1 $kWh. Moreover, the obtained data showed that by substituting landfilling with incineration technology and generating electricity through it, an annual reduction of CO2 pollution of 2,440,000 tons can be achieved.

Abstract Off‐grid renewable energy systems are a solution for power generation in areas where access to the grid is not possible or cost‐effective; in particular, low population rural areas located far away from grid lines or in rugged terrains. Furthermore, over‐reliance on fossil fuels for supplying global energy demand has led to the depletion of nonrenewable resources and environmental issues. This paper presents a feasibility assessment of an off‐grid hybrid renewable energy system for a remote rural area in Kohgiluye and Boyer‐Ahmad Province in Iran. Regarding the available energy resources in the region, a photovoltaic (PV)‐biomass energy system is considered. HOMER Pro software is utilized to find the optimized sizing of the PV‐biomass system to fulfill this load demand. The objective function in this optimization is the system's total net present cost. Due to the rapid fluctuation of economic factors in the country, several rates of inflation and discount rate are considered to investigate their influence on the costs of the system. The optimization result for the current inflation rate of 40% and the discount rate of 18% in the country proposes a hybrid energy system consisting of a 3 kW biogas‐fueled generator, 4.74 kW PV, 10 kWh battery, and 2.07 kW converter to meet the 2.64 kW peak load and 14.53 kWh/day consumption of the community. The total net present cost and cost of energy are $93,057 and 0.0933 $/kWh, respectively. Finally, the environmental assessment of the proposed hybrid system shows an annual CO2 emission of 2.95 kg, which means 99.9% CO2 emissions mitigation compared to a conventional coal‐based electrical plant.

The emission intensity is considered important data in determining technical and environmental efficiency in power plants. In this research, the goal is to determine the intensity of greenhouse gas emissions in the electricity production sector in Iran under the influence of new energies. To achieve this goal, the total greenhouse gases produced in a year in the electricity sector in fossil and renewable power plants are divided by the total electricity produced and obtained quantitatively in terms of tCO2/kWh. Also, the effect of each primary source of electricity generation is analyzed separately in terms of emission intensity. The results showed that the participation of renewable sources in the highest situation was about 9.5%, and their emission intensity was 2.2 tCO2/kWh. The fossil fuel-based power plant had an estimated emission intensity of 506 tCO2/kWh in the same year. Although the environmental policies in Iran seek to reduce the intensity of emissions, and generally, the growth of this index is negative, there are many fluctuations in this process. With the reduction of rainfall in Iran and the reduction of water behind the dams, the dependence of electricity production on water sources has decreased significantly So that in the year when the precipitation is significant, the intensity of emission has increased from its minimum value of 613.6 tCO2/kWh to 654.34 tCO2/kWh in the year of low rainfall. As a result, it has been suggested that the potential of solar resources, which emission intensity is lower than other renewable sources and is one of the most reliable and stable primary sources, should be used more effectively to reduce the emissions of electricity production sector.

Abstract The population growth, causing the increasing energy demand, the lack of fossil fuels, and its pollution, has become the most important human challenges in years. One of the main goals in using fossil fuels is electricity generation in the utilities, as they can be used in many different types. Gas power plants are one of the ways of generating electricity in many areas, and they are based on gas turbines. The current study aims to define a novel biodiesel fuel named, Sepanta; to improve the combustion conditions of diesel fuel in a gas turbine by using an Iranian endemic plant: Salvia leriifolia seeds oil. In the present research, Sepanta biodiesel has been added to the diesel Euro 4 in different concentrations (20%, 40%, and 60%). Firstly, to determine the differentiation of Sepanta fuel from pure diesel, experiments were carried out such as determining the thermal value and carbon percentage, hydrogen, nitrogen, and oxygen determination in the fuel mixed with Sepanta, and then, in the lake of Sepanta, using the pure diesel, determination of the optimal points has been carried out. The results showed the use of 60% Sepanta reduced the 27% release of unburned hydrocarbons and the use of 40% Sepanta reduced 33% nitrogen oxides in the way to approve the ideal Sepanta performance as an additive to the defined biodiesel.

Abstract The environmental taxes, such as carbon tax, also affect other economic variables in a different way in addition to the main goal of politicians. The carbon tax aims to reduce energy consumption and pollutant emissions, while it can also reduce labor tax and labor costs which are incentives to create new jobs. It is necessary to evaluate the carbon taxation policy in Iran due to the special circumstances of the budget deficit mainly caused by the decline of exports and oil revenues. The present study is based on a general equilibrium model in the form of a nonlinear equations system. The model has been calibrated for the 2017 reference year using the data table adopted from Iran's economy. It has been shown that if the carbon tax revenue is employed to decrease the labor income tax, the environmental quality will be improved by reducing pollutant emissions on the one hand, and it will lead to positive effects on the welfare and employment on the other hand. In the present paper, the effect of applying this tax on two policies with redistribution (compensation) and without redistribution (no compensation) of income tax among the households is examined. Maximum, minimum, and optimal values of pollutant emissions reduction under the influence of carbon tax policies were calculated in both scenarios. The simulation results show that the taxation without redistribution of tax revenues decreases the welfare and household's actual consumed budget by 6.2%, but in policy with compensation of tax revenue, these indices will increase by 0.8%. The gross domestic product (GDP) decreases by about 1.7% and 2.1% in both policies, respectively, while the consumer price index (CPI) in both scenarios will increase by about 6.4% and 8%, respectively. According to this research findings, carbon taxation with the redistribution of revenue is a suitable policy to reduce greenhouse gas emissions and adhere to international commitments at the same time.

Due to its location in arid and semi-arid climates, Iran is one of the countries with the highest water stress, and the need for a study that states a solution for using salt water is felt more than ever. For the first time in this paper, an indirect method is presented to identify areas prone to salty water in the entire country of Iran, which simultaneously have the potential of wind energy to supply electricity for reverse osmosis desalination devices. Simultaneously economic, environmental, technical, and geological parameters have been considered. The proposed methodology provides a structured decision aid, which can be used in other countries to identify the mentioned areas and produce fresh water using reverse osmosis devices. Geographic Information Systems (GIS) are used to generate layers of data and to apply the elimination criteria and constraints. Multiple Criteria Decision Analysis (MCDA) is then used to rank and sort the grids via the identified evaluation criteria. Seventy-eight cities in Iran, mainly located in the east of the country, were identified as potential areas, and 16 cities with the best conditions for using wind energy in the supply of reverse osmosis energy were identified, which are areas with operational potential. For each cubic meter of saltwater desalination at 25 °C, about 0.38 kWh of electricity is consumed, the amount of water that can be desalinated depends on the amount of electricity produced by wind turbines. If the total amount of water that can be operationally extracted through 550 kW turbines can be exploited, it can supply 63.8475% of the country's water needs . About 11658552.6321 cubic meters of water can be desalinated and used. Torbat-e-Jam, located in Khorasan Razavi province, can produce 2244868.421 cubic meters of fresh water, the most prone among other areas.

Increasing the power grid peak in the summer time causes power outages in industries and residential areas in Iran. The most obvious example of this issue is the power outages in the summer of 2018. Management of the demand-side is the most important strategy to reduce the grid peak due to the high cost of the development of the power plant capacity (500$ per kilowatt). In the present study, the effect of behavioral parameters in decreasing the power grid peak was identified. The behavioral simulation was done as an agent-based model using the raw data of the time-use survey (TUS) of the Statistics Center of Iran. 4228 urban households were surveyed, and the quality of people’s behavior was determined in each time step of 15 minutes during the day and night with 2 deterministic and stochastic approaches. In the stochastic approach, the Markov chain method was used. It showed that the power grid peak can only be reduced by 10% with behavioral flexibility and up to 25% by upgrading technology. In addition, based on the power deficit in 2018, 2000 megawatts of solar power capacity must be added to the network at peak times to meet grid demand.

In recent years, energy predicament and environmental problems in the world caused by fossil fuels combustion make us to pay serious attention to optimizing energy consumption and using renewable energies. One of the potential renewable energies which can be helpful in electricity generation is harness wind and water energy or using these two kinds of energy simultaneously. In this study, to provide a part of electricity in Azadi complex, 2 wind turbines with 12 different scenarios are used. In addition to provide some parts of the consumed electricity, they provide consumed electricity for water pumps which pump the sport complex lake water to a reservoir with 30000 cubic meters capacity and 20 meters height which provides remainder the consumed electricity. In this model, with regard to the uncertain amount of electricity consumption, 3consumption scenarios with three probabilities are pumped every day into a pool and a few of it is used for electricity consumption and the surplus is sold to the agricultural sector and irrigation of green spaces. The GAMS software and two stage optimization methods in two states, with and without considering the risk for optimization are used and in both states, profit and net profit in each scenario are computed.