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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Many efforts have been made to increase the utilization of renewable energy resources (RESs) in Iran. This paper aimed to evaluate the techno‐economic performance of an introduced hybrid microgrid (HMG) in eight climate zones of Iran. Therefore, ten cities are selected from the eight climate conditions of Iran. An electricity pricing strategy is also implemented according to the electricity tariffs defined by the Ministry of Energy (MOE) of Iran. The proposed electricity pricing strategy is applied to the HOMER software for investigating the optimal system configuration, RES electricity generation, and the economics of each understudy city. Optimization results indicate that Urmia (in moderate and rainy climate zone) has the least net present cost (NPC) (−5839$) and levelized cost of energy (COE) (−0.0122 $/kWh), whereas Golestan (in semimoderate and rainy climate zone) has the highest NPC (4520 $) and COE (0.012 $/kWh). It is shown that the combination of photovoltaic (PV)/wind turbine (WT)/converter in the grid‐connected operation mode is the most economical configuration. Moreover, the cities with higher potentials of wind speed and solar irradiance have lower NPC and COE. It is concluded that the utilization of the battery energy storage (BES) is technically and economically infeasible for all eight climate zones, even if the stored electricity is sold to the grid. Two sensitivity analyses are conducted to the electricity feed‐in‐tariff (FiT) and solar module price, respectively. The first sensitivity analysis indicates that by increasing FiT, more contribution of RESs is seen, which leads to lower COE and NPC. Furthermore, the two cities of Urmia and Yazd have the highest NPC and COE reductions. The second sensitivity analysis studies the module price impacts on the NPC and COE of each understudy city. It is revealed that the PV module price has a considerable effect on NPC and COE. However, this effect is more significant in some cities such as Bam, where a linear relationship is seen between the module price and economic results (NPC and COE). [ABSTRACT FROM AUTHOR]

In this paper, the efficient amounts of radiation received by a flat‐plate collector and top heat loss coefficient along with affecting parameters are investigated using measured data in different climates of Iran. Coded program in MATLAB software is then distributed to calculate the optimum tilt angle for extracting the highest solar radiation in different months of the year for five cities of Iran with different geographic latitudes. An optimal annual slope is obtained for maximum utilization and for conditions where the collector can only be adjusted at an angle during the year. Using an interpolation, an equation has been derived for obtaining the optimal tilt angle of collector for areas with latitude between 27° and 37°. Inasmuch as the top heat loss coefficient is required for evaluating the thermal performance of solar collectors, the value for different temperatures is obtained at ambient temperature up to 200°C for the absorber plate. Effects of key parameters such as collector slope, number of covers, wind speed, emittance coefficient of adsorption plate, and cover spacing on top heat loss coefficient are investigated. In the end, the particle swarm optimization (PSO) method is employed to minimize the top heat loss coefficient. The minimum amount of top heat loss coefficient is obtained with the amount of 0.99 W/m2K. [ABSTRACT FROM AUTHOR]

As climate issues gradually attract public attention worldwide, the operation of crude oil pipelines has been attached with new emission‐reduction targets. Though previous studies concerning life cycle assessment (LCA) of oil and gas pipelines have estimated the carbon footprint to some extent, there is a lack of research on life cycle carbon emissions that take the process of crude oil pipelines transportation. the main objective of this study is to build a comprehensive LCA model of carbon footprint for crude oil pipeline systems. A gate‐to‐gate analysis is provided for the LCA model, which means that the entire pipeline's life cycle from the extraction to disposal is considered. The LCA approach used both midpoint and endpoint impact assessment methods to evaluate the environmental impacts of crude oil pipeline transportation in Iran. The study analyzed the major environmental impact categories, such as greenhouse gas emissions, energy consumption, water usage, and solid waste generation. The results showed that the crude oil pipelines transportation has significant environmental impacts in Iran. The three highest impacts on the midpoint scale are marine ecotoxicity by 61.54 kg 1,4‐DCB, terrestrial ecotoxicity by 52.26 kg 1,4‐DCB and fossil resource scarcity by 40.22 kg oil eq. The endpoint impacts of three stations were also compared. The Chamran, Abadan and Zanganeh stations have 95.44%, 94.22%, and 6% impacts on human health, respectively. Also, Abadan station has the largest amount of damage to ecosystems and resources with 96.65% and 80.02%, respectively. The findings of this study could be used by policymakers, oil companies, and other stakeholders to make informed decisions and implement strategies to reduce the environmental impact of oil transportation in Iran. [ABSTRACT FROM AUTHOR]

Aerodynamic optimization of a horizontal axis wind turbine blade is performed for maximizing total annual energy production in three different sites located in the east part of Iran. While most researches have focused on the optimization of wind turbine blades for a specific location or air velocity, the main objective in practical problems is to find the best single design for multiple locations giving the highest energy output. The current paper addresses this issue and shows that multi‐site optimization of wind turbine blades is the key to maximizing energy extraction at multiple sites while reducing the manufacturing costs by proposing one optimum blade for all sites. In order to achieve this goal, the known Riso wind turbine blade is used as the base geometry and is optimized using a modified blade element momentum (BEM) theory and genetic algorithm. The objective function is maximizing sum of energy production at the selected sites. Blade twist and chord length distributions are chosen as design parameters. By running various optimization cases, it is shown that the multi‐site optimum blade has the highest sum of annual energy production by 4.45% increase compared with the Riso wind turbine blade. [ABSTRACT FROM AUTHOR]

Uncertainties of renewable energy sources (RESs) such as wind turbine (WT) and photovoltaic (PV) units are one of the considerable challenges of prosumer microgrids (PMGs) for the optimal day‐ahead operation. In this study, a new probabilistic scenario‐based method of optimal scheduling and operation of PMGs is developed. In this regard, different scenarios are generated using Monte Carlo Simulations (MCS). Furthermore, k‐means, k‐medoids, and differential evolution algorithms (DEA) are deployed to cluster the scenarios in the proposed method. A realistic commercial PMG in Iran is selected to apply the introduced method. The validity of the developed probabilistic optimization method for PMG operation is examined by comparing the results under various scenario reduction algorithms and MCS ones. The comparison of the obtained results and those of other existing deterministic methods highlights the advantages of the presented method. Furthermore, the sensitivity analyses are carried out to investigate the robustness of the developed method against the increase in the system uncertainty level. According to the test results, it is concluded that the k‐medoids algorithm has the best performance in comparison with the k‐means and the DEA‐based clustering under various conditions. [ABSTRACT FROM AUTHOR]

In order to attain an efficient path into the enhancement of the sustainable conservation and management of energy resources in the buildings and residential sections, efforts by all relevant institutions in the area of energy are essential and primitive. Hence, the development of the energy supply model in the building and the provision of fundamental solutions in this area is rudimentary. The key to any program related to this matter is to boost and extend energy efficiency and energy resource management. According to the global statistics and processed data, the residential sector accounts for 34 percent of the total energy consumption in Iran, which is the highest energy consumption compared to all existing sectors; therefore, immeasurable research has been done on optimizing energy usage in the building sector. One of the most efficient energy optimization methods can be achieved by using energy storage materials in the outer walls of the buildings. In this project, a research‐based residential building is considered as a case to investigate for energy optimization. In the first stage, the building is simulated and the energy consumption of the building is measured. Afterward, with actual measurements, real consumption is approximated and compared with the results of the software. After verifying the software data, the insulation is simulated in the software and the outcomes of using this insulator are investigated to reduce energy consumption. Energy storage materials are considered as a type of phase‐change material. These materials have the same characteristics which is having a different melting point and, by capturing and losing heat at design temperatures, they can help maintain energy inside the building that is how they can be considered as an insulator. Within the appropriate software which is Design‐Builder, miscellaneous types of these materials are available with various features. The final results point out that the use of this material saves up to 30% of the heating energy and about 8% in the cooling load of the building. [ABSTRACT FROM AUTHOR]