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In this research paper, comprehensive thermodynamic modeling of an integrated energy system consisting of a multi-effect desalination system, geothermal energy system, and hydrogen production unit is considered and the system performance is investigated. The system's primary fuel is a geothermal two-phase flow. The system consists of a single flash steam-based power system, ORC, double effect water–lithium bromide absorption cooling system, PEM electrolyzer, and MED with six effects. The effect of numerous design parameters such as geothermal temperature and pressure on the net power of steam turbine and ORC cycle, the cooling capacity of an absorption chiller, the amount of produced hydrogen in PEM electrolyzer, the mass flow rate of distillate water from MED and the total cost rate of the system are studied. The simulation is carried out by both EES and Matlab software. The results indicate the key role of geothermal temperature and show that both total exergy efficiency and total cost rate of the system elevate with increasing geothermal temperature. Also, the impact of changing absorption chiller parameters like evaporator and absorber temperatures on the COP and GOR of the system is investigated. Since some of these parameters have various effects on cost and efficiency as objective functions, a multi-objective optimization is applied based on a Genetic algorithm for this system and a Pareto-Frontier diagram is presented. The results show that geothermal main temperature has a significant effect on both system exergy efficiency and cost of the system. An increase in this temperature from 260 C to 300 C can increase the exergy efficiency of the system for an average of 12% at various working pressure and also increase the cost of the system by 13%.

The current work proposes and investigates a novel multigeneration system (power, hydrogen, and energy) comprising a flash-binary geothermal power plant, a modified Kalian cycle, a low-temperature electrolyzer, and a reverse osmosis desalination setup. Indeed, the whole system has been devised regarding the multi-heat recovery technique and smart management of products through a structural modification. To emphasize the ability of the newly designed system in this work, the data of the Sabalan geothermal plant in Iran has been used as a case study. Subsequently, the feasibility of the proposed multigeneration system has been examined by the modified specific exergy costing (M-SPECO) method, characterizing the exergetic and cost aspects of the system. The M-SPECO method is recognized as an energy level-based cost scrutiny technique to evaluate energy conversion systems. Accordingly, the sensitivity study through single and dual parametric analyses has been implemented, wherein separator 1 pressure was the main parameter. Likewise, the non-dominated sorting genetic algorithm-II (NSGA-II) method has been applied to optimize the calculations and reveal the optimum conditions and results. In this way, the achieved optimum exergy efficiency of the system was calculated as 47.25%, followed by a value of 7.66 $/GJ for the modified overall unit cost of products.

Due to its inherent ability of augmenting power system stability limit while maintaining good electric Power Quality (PQ), Power System Stabilizer (PSS) is envisaged to be an effective device in numerous Distributed Generation (DG) applications. It becomes a paramount work to maintain stable frequency, and alleviate the utility-grid collapse. Owing to this, this paper evaluates the performance of generic, and Multiband (MB)-PSSs for a hybrid 9 MW wind farm connected with mini/micro hydro power plant. The proposed system is interfaced with 200 MVA, 25 kV utility-grid system. A comparative analysis in the performance of a generic-PSS is presented with a MB-PSS at various voltage level points and power flows at various Point of Common Couplings (PCC) are analysed. Transient analysis is carried out during the presence of various unsymmetrical faults. It is envisaged that transients and unbalanced voltage sag-swells are mitigated at various PCCs while maintaining uninterruptable real and reactive power flows. The superiority of MB-PSS is established over generic-PSS in maintaining optimal PQ flow. Consequently, the reactive power requirement of the connected load is compensated by wind and mini/micro hydro controlling schemes using MB-PSS. Overall, the accurateness of the developed simulink models is demonstrated and satisfactory results are obtained in comparative analysis of both stabilizers.

Metal-organic frameworks are a new class of materials for hydrogen adsorption/storage applications. The hydrogen storage capacity of this structure is typically related to pressure, temperature, surface area, and adsorption enthalpy. Literature provides no reliable correlation for estimating the hydrogen uptake capacity of MOFs from these easy-measured variables. Therefore, this study introduces several straightforward and accurate artificial intelligence (AI) techniques to fill this gap, initially determining the appropriate topology of AI-based methods, then comparing their performances by statistical criteria, and introducing the most accurate. This study used artificial neural networks, hybrid neuro-fuzzy systems, and support vector machines as estimators. The general regression neural networks (GRNN) with a spread of 7.92 × 10−4 shows the highest correlation with the literature data and provides a relative absolute deviation of 5.34%, mean squared error of 0.059, and coefficient of determination of 0.9946.

As people’s living standards are high, the interior design requirements for green ecological residences are increasing. Based on this, the effective application of marine design concept in the design of green ecological residential indoor environment is studied. Firstly, the basic application elements of the marine design concept are analysed, so that under the guidance of the concept of marine design, the optimal design model of the green ecological residential indoor environment is constructed. Through relevant algorithms, the influencing factors of the concept of marine design in the effective application of green ecological residential indoor environment design are tested. The experimental results show that the marine design concept is affected by economic and environmental factors. At the same time , this concept can also be effectively applied to the optimal design of indoor environment of green ecological residence. Ocean design concept is effectively applied in the interior environment design of green ecological residence, which improves people’s living standard.

High efficiency of perovskite solar cell can be obtained through various approaches, including materials and interface engineering, device modification and fabrication techniques. In all approaches, the quality of the perovskite layer has a significant impact on the efficiency of the perovskite solar cell. Antisolvent dripping is widely used in almost all fabrication methodologies to achieve a high-quality perovskite layer. However, in the conventional antisolvent dripping, there are several factors (antisolvent volume, time and point of dripping, etc.) to be strictly followed. Due to these difficult and critical tricks, researchers often get perovskite layers with pinholes, small grains, and wide grain boundaries that deteriorate the performance of the perovskite solar cells. In order to produce perovskite films with large-scale grains, narrow boundaries and smooth surface morphology, a sealed antisolvent-fumigated process is implemented. There is no need to make any substantial efforts to achieve optimal conditions for the fabrication of high-quality perovskite layers using the antisolvent-fumigated strategy. Consequently, the efficiency of perovskite solar cell improves dramatically from 18.65% to 21.45%. Our findings present a new and convenient method for fabricating highly efficient perovskite solar cells.

The energy supply system of Uzbekistan is not well positioned to meet the rapidly rising domestic energy demand of this country. Uzbekistan's current energy supply system is outdated and has very low diversity, as most of its energy comes from natural gas. In addition to producing immense amounts of greenhouse gas and environmental pollution, this situation is untenable considering the eventual depletion of fossil fuel reserves of this country. Uzbekistan's renewable energy sector is highly undeveloped, a situation that can be attributed to the lack of coherent policies for the advancement of renewable power and the low price of natural gas. However, this country has significant untapped renewable potentials, especially wind energy, that can perform a significant performance in the country's power generation plans. Also, producing hydrogen from renewable power can provide a good alternative to fossil fuels and help meet the needs of the Uzbek industrial sector, especially oil, gas, and petrochemical industries. In this study, the suitability of 17 regions in Uzbekistan for wind-powered hydrogen production was analyzed in terms of 16 sub-criteria in four categories of technical, economic, social, and environmental factors. To obtain robust results, the ranking was performed using a hybrid of BWM and EDAS, as well as WASPAS, ARAS, and WSM techniques. The weighting results exhibited the Levelized Cost of Electricity (LCOE), Levelized Cost of Hydrogen (LCOH), and Annual Energy Production (AEP) to be the most important sub-criteria for this evaluation. Nukus, Buhara, and Kungrad were introduced as the top three most appropriate locations for hydrogen development from wind plants. It was estimated that using 2000 kW turbines, a wind-powered hydrogen production plant built in the Nukus region can achieve an annual power output of 4432.7 MW and annual hydrogen output of 71.752 tons.

Network intrusion detection systems analyze traffic in a medical IoT system to detect abnormal behaviors. Machine learning and artificial intelligence (AI) algorithms are widely used in designing intrusion detection systems to prevent attacks on a medical IoT system. In this paper, an artificial neural network is employed to detect abnormal behavior in a medical IoT system. The accuracy of the detection depends heavily on the features that are fed into the artificial neural network. Selecting the important and discriminative features of network traffic is a crucial and challenging issue because it has a significant impact on the learning process. In the proposed method, the butterfly optimization algorithm which is a meta-heuristic optimization algorithm is employed to select the optimal features for the learning process in an artificial neural network. The results achieved, 93.27% accuracy, indicate the capability of the butterfly optimization algorithm to determine discriminative features of network traffic data. The proposed algorithm outperformed the decision tree, support vector machine, and ant colony optimization, which was proposed in previous researches for the same goal.

One of the essential steps to design energy conversion-based systems is choosing an efficient working fluid under the design goals to access stable products with high efficiency and overcome environmental issues. In this regard, the current paper is motivated to devise and evaluate a novel geothermal-driven multigeneration system under the effect of various working fluids. The proposed system consists of a flash-binary geothermal power plant, an organic flash cycle (OFC), a power/cooling subsystem (an organic Rankine cycle (ORC) and a thermoelectric generator incorporated with a compression refrigeration cycle), and freshwater and hydrogen production units utilizing a humidification-dehumidification desalination unit and a low-temperature electrolyzer. Considering the design potential of the OFC and ORC, four different environmentally-friendly working fluids, i.e., R123 and R600 in the OFC and R1234yf and R1234ze(e) in the ORC are selected and classified in four groups to introduce the best one, under the energy, exergy, and economic (3E analysis) approaches. Also, the whole system is optimized through a genetic algorithm, respecting the optimal solution for the energy efficiency and unit exergy cost of the products. According to the results, R123/R1234ze(e) shows the highest cooling, hydrogen, freshwater production rates, and energy efficiency. Likewise, the maximum power generation and exergy efficiency belong to R600/R1234ze(e). Moreover, R600/R1234yf has the lowest unit exergy cost of products.

Smart use of clean energy sources for achieving higher performance and designing cost-effective systems is recognized as an essential solution for reducing fossil fuel consumption. In this regard, this study supports a comprehensive evaluation and multi-criteria optimization of a novel poly-generation plant embracing geothermal energy from thermodynamic and thermoeconomic perspectives. Hence, the utilization of modified subsystems and smart use of multi heat recovery processes are projected and appraised. In this regard, the plant consists of a double-flash binary geothermal subsystem, an organic Rankine cycle in combination with an ejector refrigeration cycle considering a zeotropic working fluid (a mixture of pentane and R142b), a heating production heat exchanger, and a proton exchange membrane electrolyzer with the combined production of cooling, heating, power, and hydrogen. The crucial thermodynamic and thermoeconomic variables are investigated against key parameters and concluded that the sensitivity of outcomes is more evident with the variation in zeotropic working fluid composition and the vapor quality at the heating production heat exchanger's outlet. The attained results at the optimum mode demonstrated, the energy and exergy efficiencies of the plant as well as total unit costs of products are as being 44.5%, 35.8%, and 18.8 $/GJ, respectively.

Power consumption of wellbore drilling in oil and gas exploitations count for 40% of total costs, hence power saving of WBM (water-based mud) by adding different concentrations of Al2O3, TiO2 and SiO2 nanoparticles is investigated here. A high-speed Taylor–Couette system (TCS) was devised to operate at speeds 0–1600 RPM to simulate power consumption of wellbore drilling using nanofluids in laminar to turbulent flow conditions. The TCS control unit uses several sensors to record current, voltage and rotational speed and Arduino microprocessors to process outputs including rheological properties and power consumption. Total power consumption of the TCS was correlated with a second-order polynomial function of rotational speed for different nanofluids, and the correlated parameters were found using an optimization technique. For the first time, energy saving of three nanofluids at four low volume concentrations 0.05, 0.1, 0.5 and 1% is investigated in the TCS simulating wellbore drilling operation. It is interesting to observe that the lower concentration nanofluids (0.05%) have better power savings. In average, for the lower concentration nanofluids (0.05%), power was saved by 39%, 30% and 26% for TiO2, Al2O3 and SiO2 WBM nanofluids, respectively. TiO2 nanofluids have better power saving at lower concentrations of 0.05 and 0.1%, while Al2O3 nanofluids have saved more power at higher concentrations of 0.5 and 1.0% compared with their counterpart nanofluids.

In this study, the performance of a system consisting of an organic Rankine cycle (ORC) for generating power and an electrolyzer for producing hydrogen with a zeotropic mixture as working fluid to recover waste heat in a geothermal flash-binary cycle is investigated from energy and exergy point of view. The study also investigates the effect of using zeotropic mixtures with different compositions as the ORC's working fluid rather than pure fluids. Using the particle swarm optimization (PSO) algorithm, the optimization is performed to maximize the power production of the entire system. The results show that using the combination of pentane with other pure fluids as working fluid led to improved system performance in terms of power and hydrogen output. In view of ORC unit power output (31.51 kW), overall system power output (128.16 kW), and hydrogen output (0.39626 kg h−1 per kilogram of geothermal water), the pentane (0.54)/butene (0.46) mixture produces the best results. Under optimal operating conditions, the rate of exergy destruction, exergy and energy efficiency for the whole system is equal to 95.81 kW, 37.25% and 20.17%, respectively. It is also found that the composition of the zeotropic mixture has a significant impact on the performance of the ORC as well as hydrogen production, which is associated with the extent of temperature glide in the mixture. When pentane (0.54)/butene (0.46) is used as the working fluid, the highest improvement related to use of zeotropic mixture instead of pure fluid is observed, which increases the power output of the ORC unit and the hydrogen output of the system by, respectively, 22.53% and 23.02%. In the end, the effect of flash chamber pressure on the total power and hydrogen output is also investigated. This investigation shows that as this pressure increases, the total power output decreases. However, although a lower chamber pressure is more desirable, given the impact on the hydrogen production and the turbine size, it is preferable to keep the flash chamber pressure moderate.

A solar air heater (SAH) is a heat exchanger that is capable of converting radiations (solar) into thermal energy, which is further utilized for heating purposes. But due to poor thermal conductivity of air, SAH has poor thermal performance. Roughness is one of the effective techniques used to improve the performance of SAH. Two different roughness geometries, semicircular and square, were used in the present article, and the effect of different parameters on the exergy efficiency of a SAH is investigated. The flow passage used for the solar air heater has a triangular cross section with an equal side length of 160 mm. The positive impact of various roughness parameters (relative roughness height, e/D and relative roughness pitch, p/e) and operating parameters (Reynolds number) has been obtained on the exergetic efficiency of the SAH. Comparing both the roughness geometries, it is concluded that the exergetic efficiency found in semicircular ribbed SAH is 26% higher than that of square roughness at e/D and p/e value of 0.04 and 10, respectively. The exergetic efficiency of a SAH is suitable for design as it includes the quality of useful energy and its associated pumping power. The design plots are also developed and based upon that recommendations are made to develop an efficient solar air heater.

Increasing energy demand has led to a substantial growth in the use of wind energy across the world, which can be attributed to the low initial and running costs and rapid and easy deployment of this technology. The development of hydrogen from wind energy is an excellent way to store the excess wind power produced, as the produced hydrogen can be used not only as clean fuel but also as input for various industries. Considering the good wind potentials of Yazd province, the variety of industries that are active in this area, and the central location of this province in Iran, which gives it ample access to major transport routes and other industrial hubs, hydrogen production from wind power in this province could benefit not only this region but the entire country. Given these considerations, we conducted a technical, economic, and environmental assessment of the potential for wind power generation and hydrogen production in Yazd province. Overall, the assessments showed that the best locations for harvesting wind energy in this province are Bahabad and Halvan stations. For these two stations, it is recommended to use EWT DW 52-900 turbine to take advantage of its higher nominal capacity to achieve higher electricity and hydrogen output and emission reduction. For Abarkoh and Kerit stations, which have a low wind energy potential, it is recommended to use small turbines such as Eovent EVA120 H-Darrieus. Also, economic and technical assessments showed that it is not economically justified to harvest wind energy in Ardakan station. The results of ranking the stations with the Step-wise Weight Assessment Ratio Analysis (SWARA) and Evaluation based on Distance from Average Solution (EDAS) techniques showed that Bahabad station was introduced as the best place to produce hydrogen from wind energy.

This paper unveils a sustainable energy plan for optimal utilization of available electrical energy resources for an energy-deficient village. The chosen village is Nangal, near Barnala, Punjab, India. Primarily, the requirements of electric energy are recorded and elaborated for around 450 households. Aiming this, the potential to harness electric power and its effective utilization has been identified from the available resources of energy: biomass, agriculture waste and solar photovoltaic (PV) technology. In order to achieve this, a hybrid renewable energy system (HRES) model is proposed whose performance is evaluated by implementing it in hybrid optimization model for electric renewable (HOMER) software. HOMER software provides optimal solution for a commercial biogas plant for catering cooking gas demand. Also, a coordinated solution for solar PV-operated water pumps used for irrigation, village water supply and solar PV street lights is presented and analyzed. In this way, the accurateness of proposed model is investigated by estimating the optimal electric power demand and its economic benefits. It has been revealed that the computed cost of energy and total net present cost are $0.032/KWh and $76,837, respectively, by the parametric assessment of proposed HRES system. It is envisaged that the proposed model can be a road map for future research engineers in designing an effective energy utilization for villages.

Ensuring efficient operation of energy conversion systems in terms of economics and ecology is a prime objective that should be addressed within the design, optimization, and development stages of such systems. Adopting appropriate measures for accurate assessment and comprehensive evaluation of thermodynamic systems is a sheer necessity for accomplishing this purpose. In this study, the newly developed emergy-based exergoeconomic (i.e., emergoeconomic) and emergy-based exergoenvironmental (i.e., emergoenvironmental) analyses have been employed to assess a combined power and cooling system, including a gas turbine cycle, a steam Rankine cycle, and an integrated organic Rankine cycle-vapor compression refrigeration (ORC-VCR) subsystem serving as a waste heat recovery unit. The merit of emergy-based methods is that they can evaluate and express results by an identical unit of measurement (i.e., sej) which enables us to undertake a fair and accurate comparison between the methods in question. The results showed that the combustion chamber, with the total economic emergy rate of 6.83E13 (sej h−1) and the total ecological emergy rate of 6.05E14 (sej h−1), was the most critical component in the entire system from both the economic and ecological viewpoints. Moreover, a parametric study was carried out on the entire system, as well as the ORC-VCR unit, to examine the effect of design parameters on the emergy-based monetary and ecological performances. Increasing the air compressor pressure ratio from 6 to 11 enhanced the entire system’s both emergy-based performances by almost 8%, followed by improvements made by the gas turbine isentropic efficiency and combustor inlet temperature, with 6.5% and 5.5%, respectively. However, other design parameters exerted limited impact. Regarding the ORC-VCR, raising the ORC turbine inlet temperature and the isentropic efficiencies associated with the ORC turbine and VCR compressor improved the emergy-based performances, while the reverse was observed for the ORC condenser and evaporator temperature rise.

New and innovative solutions are being developed to overcome the challenges of detrimental effects that the traditional energy systems cause. This means that sustainable methods are implemented to do so, noting that when such developments are taken into consideration and are studied, this leads to a significant drop in the cost of renewable energy systems. In this work, a hybrid system consisting of a single flash steam geothermal power plant and a solar thermal system using a parabolic trough collector (PTC) is studied. Based on the available works in literature, the required design materials and modeling equations are chosen and discussed. The heat transfer fluid (HTF) as water is chosen as the working fluid for the PTC due to its low cost and high specific heat capacity. The calculations are carried out for the PTC on a specific day, time and location, and the simulations for the geothermal power plant (GPP) are carried out using System Advisor Model (SAM) software, assuming a specific increase in the temperature of the geofluid due to the additional heat transfer from the HTF of the PTC. The power plant output is 20 MW powered by four production wells. The results show that the energy production is ~15 GWh in January, which is the highest during the year due to the required energy demand for electricity consumption and district heating. Moreover, a mini review of the mathematical modeling of PTC and single flash geothermal power plant is presented.

In the view of the latest status and the potential of developing wind energy in South Africa, the present study aims to perform technical–economic–environmental​ analysis on a wind turbine system with HOMER software using the 20-years average data of the wind speed obtained from NASA’s database, for providing the electricity to residential buildings. The results showed that the Port Elizabeth station, had the lowest levelized cost of electricity (LCOE) with the value of -0.363 $/kWh when using the EOLO wind turbine, and the Bloemfontein station had the highest LCOE with the value of 1.601 $/kWh when using the Turby wind turbine. The results from the step-wise assessment ratio analysis (SWARA) weighting method demonstrated the wind penetration, total production, and capital cost as the most important sub-indices with the weights of 0.106, 0.095, and 0.091, respectively. Using the additive ratio assessment (ARAS), weighted sum method (WSM), and weighted aggregated sum product assessment (WASPAS) techniques, the cities under study were ranked, and the cities of East London and Bloemfontein were identified as the most suitable and the most unsuitable stations for the use of household-scale wind turbines, respectively.

The emerging environmental consequences of overdependence on fossil fuels have pushed many countries to invest in clean and renewable sources of power. Countries like Iran where these sources can be found in abundance can take advantage of this potential to reduce their dependence on fossil fuels. This study investigated the feasibility of the standalone use of a hybrid renewable energy system (HRES) to power buildings in the Bostegan village in the Hormozgan province of Iran. Technical, economic, and environmental assessments were performed with the help of the Hybrid Optimization of Multiple Energy Resources (HOMER) software, and the optimal configuration for the system components was determined accordingly. The results showed that the simultaneous use of wind and solar systems with a converter and a backup system comprised of a diesel generator and batteries will be the most economic option, offering electricity at a cost of 1.058 USD/kWh and with a renewable fraction of 64%. After selecting the most optimal system using the step-wise weight assessment ratio analysis (SWARA) and weighted aggregated sum product assessment (WASPAS) techniques, a sensitivity analysis with 27 parameter settings was performed to determine the effect of fuel price fluctuations and the uncertainty in the renewable energy potentials on the results. This analysis showed that in the worst-case scenario, the price of electricity will reach as high as 1.343 $/kWh. In the end, the study investigated an alternative scenario where the generated power is used for hydrogen production, which showed that the system output can be used to produce 643.63 ton-H2/year.

Solar energy is a free and environmentally friendly supply of power that has negligible impact on the environment, and it has long been used by humans through different methods. However, solar energy technology would use for heating water for buildings as an alternative resource, which would help reduce CO2 reduction and safe environment. A data analysis was performed using the RETScreen software, and the financial outcomes that were calculated using two methods showed a benefit-to-cost ratio of more than 1, a payback period of 11 years, and a reduction in the cost of greenhouse gas emissions of as much as $562 using Method 1; and a benefit-to-cost ratio of more than 1, a payback period of 15 years, and a reduction in the cost of greenhouse gas emissions of as much as $192 using Method 2. Both methods indicated that this project is economically feasible. The aim of this study was to evaluate the utilization of solar energy for household and commercial purposes. The first goal was to explore the technical, economic, and environmental aspects of using evacuated glass tube solar collectors to heat water in an indoor pool in the building, having an area of 50 m2, in the city of Yazd, Iran. The second goal was to evaluate the amount of hydrogen that can be obtained from the installation photovoltaic systems in the province. The results also showed that this project will decrease greenhouse gas emissions by 142 ton-CO2 over 20 years of the useful life of a collector, thereby indicating the possible significant role of such collectors in the reduction of greenhouse gas emissions. Furthermore, the findings indicated that installing a single X21-345 photovoltaic system with a performance rate of 20% can result in the production of 2.1 kg of hydrogen annually.

The electricity consumption in residential/office buildings corresponded to 45% of the total annual electricity demand in hot-arid climates. This accounted for 27.2 TWh of electricity consumption with 14.2 MWh/capita/year in Kuwait. In this research, four offices in an educational building were equipped with a meteorological data logging system using temperature, humidity, and illuminance sensors. All four offices had double-glazed windows. Moreover, two offices were equipped with two types of commercially available window films. Two million data were stored in iCloud using Wi-Fi and an Internet of Things (IoT) system for the 3 months of June, July, and August 2019. Here, histograms and the kernel density estimation (KDE) of temperature/humidity were analyzed and compared for the two offices with/without 3M Neutral 20 window films. Two floors of the same building consisting of 31 offices were also modeled and simulated to study energy saving and CO2 footprint reduction using various window films. The results of simulations for the month of July 2019 using SOL 101 and SOL 102 window films, respectively, showed that about 250 kg and 255 kg of production of CO2 could be reduced and energy saving counted for 416 and 422 kWh. Measurements from offices with 3M Neutral 20% and 3M Neutral 70% window films for the month of July 2019 indicated that the carbon footprint could be reduced by about 82 kg and 0.43 kg and energy saving counted for 147.11 and 0.71 kWh, respectively. It was observed that an annual energy saving and CO2 footprint reduction of 2.76% could be achieved using window films in a hot-arid climate.

With the rising demand for food products and the direct impact of climate change on food production in many parts of the world, recent years have seen growing interest in the subject of food security and the role of rainfed farming in this area. Machine learning methods can be used to predict crop yield based on a combination of remote sensing data and data collected by ground weather stations. This paper argues that forecasting drylands farming yield can be reliable for management purpose under uncertain conditions using machine learning methods and remote sensing data and determines which indicators are most important in predicting the yield of chickpea. In this study, the yield of rainfed chickpea farms in 11 top chickpea producing counties in Kermanshah province, Iran, was predicted using three machine learning methods, namely support vector regression (SVR), random forest (RF), and K-nearest neighbors (KNN). To improve prediction accuracy, for each county, remote sensing data were overlaid by the satellite images of rainfed farms with a suitable slope and altitude for rainfed farming. An integrated database was created by combining weather data, remote sensing data, and chickpea yield statistics. The methods were evaluated using the leave-one-out cross-validation (LOOCV) technique and compared in terms of multiple measures. Given the sensitivity of rainfed chickpea yield to the time of data, the predictions were made in two scenarios: (1) using the averages of the data of all growing months, and (2) using the data of a combination of months. The results showed that RF provides more accurate yield predictions than other methods. The predictions of this method were 7–8% different from the statistics reported by the Statistical Center and the Ministry of Agriculture of Iran. It was found that for pre-harvest prediction of rainfed chickpea yield, using the data of the March–April period (the averages of two months) offers the best result in terms of the correlation coefficient for the relationship between the yield and the predictor indices.

The present experimental work is performed to investigate the convection heat transfer (HT), pressure drop (PD), irreversibility, exergy efficiency and thermal performance for turbulent flow inside a uniformly heated circular channel fitted with novel geometry of hybrid tape. Air is taken as the working fluid and the Reynolds number is varied from 10,000 to 80,000. Hybrid tape is made up of a combination of grooved spring tape and wavy tape. The results obtained with the novel hybrid tape show significantly better performance over individual tapes. A correlation has been developed for predicting the friction factor (f) and Nusselt number (Nu) with novel hybrid tape. The results of this investigation can be used in designing heat exchangers. This paper also presented a statistical analysis of the heat transfer and fluid flow by developing an artificial neural network (ANN)-based machine learning (ML) model. The model is trained based on the features of experimental data, which provide an estimation of experimental output based on user-defined input parameters. The model is evaluated to have an accuracy of 98.00% on unknown test data. These models will help the researchers working in heat transfer enhancement-based experiments to understand and predict the output. As a result, the time and cost of the experiments will reduce.

Water-energy nexus is a crucial and challenging concern that addressing it is noteworthy for the future of human beings. In addition, freshwater production is a highly energy-intensive procedure. Therefore, developing a suitable solution for this problem is of importance. In the present scenario, solar energy is one of the suitable options for desalination because solar energy is available at a low cost, is clean for the environment, and is widely available. Generally, solar collectors such as flat plate collectors (FPC) and evacuated tube collectors were experimented for desalination applications. This work presents an experimental investigation of a single-stage hybrid (ETC-CPC) groundwater solar desalination system. A compound parabolic concentrator (CPC) is placed below the evacuated tube collector (ETC) for collecting solar radiations to transfer heat to evacuated tubes which improves performance in the case of different weather conditions of Pune city in India. Experimental results show that the hybrid solar groundwater desalination system, by maintaining the optimum distance of 20 mm between ETC and CPC with Mylar as the reflecting material, could offer a drinking water production rate of up to 3.4 l/(m2h)/day. However, the proposed single-stage hybrid (ETC+CPC) groundwater solar desalination system with aluminum foil as a reflecting material could generate 1.9 liters of soft water per day. Further, the use of Mylar as a reflecting material could generate 3.5 liters of soft water per day.

Due to the reduction of fossil resources, the replacement of renewable energy sources such as solar energy has become mandatory. Solar energy does not contain pollution and widely available in all parts of the world, especially in warm regions. Our country (IRAN) is geographically located in a hot and dry region, and with more than 280 sunny days per year, one of the nonpower applications of solar energy is heating space and water consumption of the building using solar thermal energy. Solar water heaters can be used to heat the water used in buildings, which is the main purpose of this study. Water heating consumes an average of 20% to 30% of the total energy consumption in the residential building. Therefore, using solar water heaters annually can provide 70% of the energy needed for water heating. The system designed in this research is able to provide 75% of the hot water consumption needs. If an auxiliary heat source is used next to this system, all hot water needs of the building can be met throughout the year. In this case, as much as 237.3 kWh, energy will be saved from fossil energy sources.

COVID-19 was identified all over the world as a pandemic in December 2019. This novel coronavirus affects the lower respiratory area, which causes pneumonia in the human body and transfers from human to human. Every day, the number of new patients and the number of deaths are increasing immensely, while specific drugs for this virus are still being developed. Hospitals are struggling to accommodate patients, resulting in a large number of temporary hospitals. These makeshift hospitals need an uninterrupted power supply to continuously maintain all the electrical facilities. Fuel cells, especially solid oxide fuel cells, play an essential role in meeting the additional energy needs of humankind during this critical moment. SOFCs are able to supply power to those makeshift hospitals from the main hospital building, as well as supplying electricity to locked-down residential areas to ease the strain on the electrical grid during this pandemic situation. As a result of their extensive applicability and numerous uses, SOFCs can be used to address electrical needs challenges in various sectors. [ABSTRACT FROM AUTHOR] Copyright of International Journal of Chemical Engineering (1687806X) is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The largest amount of energy in buildings is consumed to provide heating, cooling, and ventilation. Therefore, a practical solution such as using renewable energy sources can be considered to reduce energy costs and pollutants. In addition, architecture principles must be varied to utilize passive solar energy and also to reduce energy losses. In this research, a numerical study is presented to investigate the thermal behavior of TW-FR (Trombe wall placed in a fenestrated room) in the semiarid region of Tunisia. Computational fluid dynamic (CFD) simulation of fluid flow and heat transfer shows good agreement with published data in literature. The thermal comfort level was calculated according to ASHRAE (55-2013). The results show that (i) the normal Trombe wall cannot assure a satisfactory comfort level even in summer conditions and a higher vertical temperature gradient can take a value of 15°C, and the Trombe wall is shown to be more efficient in heating mode in the studied semi-arid region compared to cooling; (ii) the operative temperature for the coldest winter is between 17.85 and 19.85°C. The air temperature gradient in the comfort ranges between the head and feet is 2.3°C; and (iii) the Trombe wall is an excellent solution for Sousse city weather; it is suggested that the passive system (TW-FR) will be examined for a whole year to have a precise evaluation of its efficiency.

Microbial fuel cells (MFCs) are the rising modern equipment for the generation of bioelectricity from organic matters. In this study, MFCs in two formats are assembled and concurrently operated for a 30-day period in a batch mode manner. Natural biowaste cattle dung slurry with mediators is used as a substrate persistently for the enhancement of electron transfer rate and additionally for the augmentation of required electrical parameters. Under similar conditions, the MFC setups are experimented with a variety of anode-cathode material combinations, namely carbon-carbon, copper-carbon, and zinc-carbon. The performance of these MFCs during the testing period is evaluated independently and compared by plotting polarization data generated by them. It is revealed that maximum current and power densities are achieved from all these MFCs and the best attained values are 1858 mA/m2 and 1465 mW/m2, respectively, for the novel single-chamber zinc-carbon electrode MFC. The corresponding findings present that the MFC with zinc-carbon electrodes has the better power density than other MFCs. Being conductive and higher standard potential metal electrodes have improved the capability to act in place of carbon family electrodes for MFC-based power applications. Although the MFC power generation is low, but modifications in configurations, electrodes, microbe-rich biowaste, mediators, and power management may enhance the power output to a significant level for commercialization of this technology. The unique feature of this research is to explore the pertinent use of conductive metal electrodes to enhance the power generation capability of MFCs through biowaste as an alternative power source for small applications. The novelty of this research is presented through usage of conductive metal electrodes for the performance analysis of MFCs.

Researches in many laboratories on solar still desalination are concerned with increasing efficiency using only solar energy. One of the techniques is the difference in the thickness of the glass cover of the distiller. In order to see the influence of this parameter on efficiency, three similar stills with three different glass coverings were investigated. The flow of heat goes through the cover, and higher glass temperature leads to solar still productivity becoming lower. This paper presents an optimization of glass thickness ( G t ) of a conventional solar still (CSS) in El Oued climate, Algeria. Based on the experimental results, the distilled water production rate, energy, and energy efficiency of the CSS have been discussed. The results showed that the suitable G t of the CSS was 3 mm. The distilled water of around 3.15, 2.02, and 1.13 kg was produced by the CSS at energy efficiency of 30.71, 19.02, and 11.44% with the G t of 3, 5, and 6 mm, respectively. The daily average exergy efficiency of 2.46, 1.38, and 0.84% was calculated for the CSS at G t of 3, 5, and 6 mm, respectively.

In this paper, the propagation of particles with different sizes from a coal-based thermal power plant was investigated. It was found that the deterioration of the environment is due to the release of a large amount of SOx, NOx and the volatile particles of Suspended Particulate Matter and Respirable Suspended Particles matter, which cause human and animal diseases. This paper presents the numerical simulation results of air pollution by particles which having different sizes from thermal power plants in real sizes using a 3D model. For the adequacy of the mathematical model, a test problem was solved using different turbulent models. To assess the applicability of the mathematical model, the numerical algorithm and the choice of the optimal turbulent model, experimental data and numerical results of other authors were used. The obtained numerical simulation results are in good agreement with the experimental results and the numerical results of other authors. And to obtain more accurate numerical results for the experimental data for turbulent models ( k − ε $k - \varepsilon $ , k − ω $k - \omega $ ), there were certain corresponding boundary conditions for kinetic energy. Also, profiles of all flow characteristics were compared with and without particles and some effects of the particle on the flow were identified.

Regarding the low energy density of solid biomass, it usually is converted to gaseous bio-fuels to be utilized in power generation systems. In this regard, the biomass gasification and digestion are of two major conversion routes. The main goal of this research is to make a comparison between biomass gasification and digestion to fuel a power and hydrogen cogeneration plant. The proposed plant is composed of a micro-scale gas turbine and an absorption power cycle for exhaust waste heat recovery of the gas turbine. The generated power by the absorption cycle is utilized in an alkaline electrolyzer for hydrogen production. Thermodynamic, economic and electrochemical models are developed to simulate and investigate the systems performances from exergy, economic and environmental standpoints. Also to determine the best operating conditions, tri-objective optimization is conducted based on maximizing the exergy efficiency and minimizing CO2 emission and product cost. The results indicate that the digester-based system yields higher values of power and hydrogen production, and exergy efficiency as well as lower value of CO2 emission compared to gasifier-based system. It implies that selection of the better system between the two considered ones depends on the user/designer special criteria.

Solar energy is the most frequently used renewable energy source which receives the light energy from the sun, and it transform in to electric energy with the help of photovoltaic cell as a module. The flow of electrons or electrical energy is produced by making the sunlight photons to fall on the collector. Which produce the electrical energy, but the power generation is not completely produced because due to various losses. The most commonly occurred power loss is due to heat formed under the solar panel which affects the solar panel performance. Induced electrical energy is inversely proportional to the base panel temperature. Our main scope of the work is to remove the heat, which are accumulated under the solar panel by using different convection mode. In this paper, an experimental analysis is conducted in four different convection mode for heat removal for three days from sunrise 8.00 a.m. to 5.00 p.m. for calculating the maximum current, voltage generation and maximum heat removal. Four experiments namely, without rectangular duct under free convection, with rectangular duct under free convection, with rectangular duct under forced convection and duct with L shaped barrier and forced convection are conducted for three days. The maximum voltage induced in solar panel without duct, with duct under free convection, duct under forced convection and duct under forced convection & L shaped barrier was obtained at 11:00 a.m. as 18.54 V, 19.05 V, 21.04 V and 22.56 V. Results indicate that the maximum voltage induced is significantly increased in all the modifications such as duct under free convection, duct under forced convection and duct under forced convection & L shaped barrier by 2.75%, 13.48% and 21.68% as compared to conventional solar panel without duct condition. The inclusion of duct under free convection, duct under forced convection and duct under forced convection & L shaped barrier in solar panel base limits the maximum temperature as 44℃, 41℃ and 38℃, however the maximum temperature in the solar panel base is 49℃ for solar panel without duct condition. Reduction in solar panel base maximum temperature for duct under free convection, duct under forced convection and duct under forced convection & L shaped barrier are 10.20%, 16.33% and 22.45% as compared to conventional solar panel without duct condition. The results also indicate that the induced voltage and solar panel base panel temperature for four experiments was compared and found the maximum electrical efficiency enhancement of 21.68% with duct and L shaped barrier under forced convection than conventional method and the corresponding base panel temperature reduction is 19.15% is obtained than conventional type. The proposed system significantly increased the photovoltaic panel performance and output voltage due to enhanced evaporation rate and reduction in photovoltaic panel temperature.

Biofuels are considered renewable sources of energy which can replace fossil fuels using naturally extracted fuels from the environment to fulfil growing demands for energy in developing countries. This paper aims to select a suitable province for producing biodiesel from Jatropha plants in new climate conditions of Iran using the additive ratio assessment method (ARAS). Previous feasibility studies lack the environmental factor when considering the cultivation of Jatropha plants in Iran. In this work, the relevant main selecting criteria were identified through using a literature review. Then, the most effective criteria were chosen and categorised as environmental, social and economical factors. The weighting of the criteria was determined by Shannon entropy method and using expert opinions. Next, the ARAS method was used for prioritizing the provinces in Iran. From the results, it is observed that the environmental factor is the key parameter for selecting biodiesel plant location. Furthermore, Golestan province was selected as the best candidate location in Iran for establishing a biodiesel plant using Jatropha plants. Using the semi-arid pastures of Golestan province (about 402,000 Hectares), 1,930,000 tons biodiesel can be produced annually for supplying the fuel to 600,000 diesel cars.

The use of flash-binary geothermal power plants is recognized as an appropriate concept for preparing a sustainable energy production facility. Hence, the target of the current research is to specify the exergetic and economic aspects of an innovative electricity and cooling cogeneration system comprising a dual-flash binary geothermal power plant and an ejector refrigeration unit. The essential point of this study is the smart use of the total capacity of a medium-temperature geothermal source to produce energy-based products and eliminate the weakness of the conventional setups, increasing the exergy and exergoeconomic performances. A parametric study has been implemented to analyze the effect of several main parameters on the vital variables including efficiencies, exergy destruction rate, sum unit exergy cost, investment cost rate, and exergoeconomic factor. Besides, a multi-objective optimization in different cases has been applied to the calculations through a non-dominated sorting genetic algorithm II (NSGA-II) to achieve an optimal design. The results showed that the performance of the system was more sensitive to changing the separators’ operating pressure of the plant. Likewise, the optimum exergy efficiency and optimum unit exergy cost of the system were found to be 12% and 0.0043 $/kWh through the exergy/cost multi-objective optimization case, correspondingly.

Decision Support Systems (DSS) have widely provided on intelligent human–machine interactions like the Internet of Things (IoT). As the dimensions and complexity of the IoT communications between intelligent devices, industrial equipment, sensors, and mobile applications are continuously increasing, supporting Service Level Agreements (SLA) for a large amount of cloud data centers and a huge number of user requests is going to be more challenging. This challenge would be more complicated when the energy consumption of the industrial IoT ecosystems increases exponentially as well. Therefore, DSS models are required for automated decision-making in critical IoT environments like intelligent industrial systems and smart cities. This paper provides a comprehensive review of the DSS strategies for energy-efficient IoT applications in intelligent urban computing. The main objective of this review is (1) presenting a technical taxonomy to categorize existing energy-efficient DSS models for industrial and smart environments in IoT ecosystems; (2) recognizing significant research trends in the field of energy-aware DSS strategies for intelligent urban computing in IoT and (3) presenting a technical and statistical analysis of reviewed studies and evaluation factors. Finally, innovations as forthcoming issues and new challenges of energy-based DSS strategies for intelligent urban computing in IoT are presented.

Transient performance assessment and techno-economic analysis are presented for a novel smart energy system driven by hybrid solar-Hydrogen energies. The proposed system is developed to provide power, heating, and cooling demands for a two-story building as the case study. In detail, the system is composed of photovoltaic thermal panels, fuel cells, thermal energy storage, solar collector, and a small-scale Organic Rankin Cycle. To generate the heating and cooling of a heat pump, an absorption chiller is occupied. The system is analyzed from technical and economic standpoints as well as environmental considerations. To find the best solution point for the system, a tri-objective optimization as a cutting-edge method to optimize all the mentioned indexes is conducted. The system is grid-connected, and the excess power could be sold to the power grid. The results show that the 19.92 kWh power can be sold to the grid, and the heating and cooling load demand are amended. Moreover, at the optimized point, the plant can accomplish the minimum cost and emission of 0.37 Ton/MWh and 8.46 $/GJ, respectively, while the yearly efficiency reaches 37.28%. In conclusion, this study has highlighted the potential of solar-driven micro-CCHP systems based on advanced technologies for residential applications.

Desalination is a perfectly viable solution for alleviating the problem of water scarcity in arid and dry regions with access to seawater or brackish groundwater. Yazd province in central desert part of Iran suffers from drinking water for most of the cities, because of the low precipitation. This study aimed at prioritizing the capitals of counties for desalinating water for the first time for this area. Also selected criteria are being used for the first time which could be used for other regions in the world. Five existing water wells from each of nine counties are nominated and ranked. Technique for Order of Preference by Similarity to Ideal Solution method was used to rank counties in terms of suitability for desalination. Validity of the results is assessed by two different methods, which Marvast found as best location. The maximum capacity of the desalination equipment is 50 m3/h. The project in order to be economically feasible, equipment must operate at least 2 h a day, therefore it would be able to desalinate minimum of 100 cubic meters of water for total of 2 h. By implementing these methods, decision makers can rationally select and rank locations for construction of desalination plants.

Energy is a main factor for sustainable and economic development of many countries in the world. The objective of this paper is to investigate barriers facing solar energy development in Iran through a case study conducted on the Alborz Province. A questionnaire was designed and then submitted to the professionals in the field of solar energy. First, the identified barriers are classified into five categories of technical, legal, economic, sociocultural, and support by help of experts. Then, the fuzzy Best-Worst method is used to determine importance of the identified criteria and sub-criteria for development of the solar energy sector in the region. The findings indicate that the primary barriers to solar energy development are economic factors which are related to the adverse impact of the uncertain economic conditions including the sanctions against Iran. Because of the high risk of new business, domestic people do not have enough ambition and interest in starting new renewable energy projects. The low price of fossil fuels (in the economic category as sub-criteria), has the most significant impact on the stagnation of this sector, which is related to the ease of access to energy in Iran and its effect on the interest in renewable energy use. Supporting the private sectors by receiving financial incentives can help development of the renewable energy sector in the province. By using similar research for other regions, decision makers can accurately identify challenges for development of solar energy.

In this paper, a mathematical model has been developed that describes the characteristics of fluid flow and dispersion of pollutants in a certain quarter of Almaty city, Kazakhstan. The influence of traffic tidal flow was investigated based on the results of passing vehicles measurements as a source of pollution by the CFD method and on the spatial distribution of pollutants for different types of pollution. To validate the numerical algorithm and mathematical model, a test problem was performed. The RNG k-e turbulence model was used as a turbulent model. The obtained data were compared with the measured and calculated values. After validation of the mathematical model, the main problem was characterized: the pollutant emissions process between houses using different types of pollution sources and the presence of different heights of barriers. The calculated data were compared with the obtained calculated values. In the course of various studies, it has been found that, despite different types of pollutants, the presence of barriers along the road reduces the concentration of harmful substances in the pedestrian zone air. And also the optimal height of this barrier along the road was chosen for maximum protection of the pedestrian part from harmful pollutants. And it was found that when using a barrier with a height of 3 m, the concentration value drops more than two times, as opposed to without a barrier, and a further increase in height is not economically profitable and does not give the desired results.

Numerical simulation of hybrid nanomaterial free convection with helps of CVFEM was performed. Dispersing nanomaterial can minimize the exergy loss. The modeling outputs were depicted in terms of 3D plots and contours. Because of reduction of irreversibility with inclusion of nanoparticles, hybrid nanofluid was employed. Increasing Ha results in greater Xd and it is more sensible when convection become stronger. The growth of permeability increases nanomaterial motion and reduces the exergy drop.

Observing the growing energy demand of modern societies, many countries have recognized energy security as a looming problem and renewable energies as a solution to this issue. Renewable hydrogen production is an excellent method for the storage and transfer of energy generated by intermittent renewable sources such as wind and solar so that they can be used at a place and time of our choosing. In this study, the suitability of 15 cities in Fars province, Iran, for renewable hydrogen production was investigated and compared by the use of multiple multi-criteria decision-making methods including ARAS, SAW, CODAS, and TOPSIS. The obtained rankings were aggregated by rank averaging, Borda method, and Copeland method. Finally, the partially ordered set ranking technique was used to reach a general consensus about the ranking. The criteria that affect hydrogen production were found to be solar energy potential, wind energy potential, population, air temperature, natural disasters, altitude, relative humidity, land cost, skilled labor, infrastructure, topographic condition, and distance from main roads. These criteria were weighted using the best–worst method (BWM) based on the data collected by a questionnaire. Solar energy potential was estimated using the Angstrom model. Wind energy potential was estimated by using the Weibull distribution function for each month independently. The results of the multi-criteria decision-making methods showed Izadkhast to be the most suitable location for renewable hydrogen production in the studied area.

Worldwide energy supply is mostly reliant on fossil fuels. Carbon dioxide emissions have caused many negative environmental issues like climate change, air pollution, and energy security. An important alternative to this hazard is substituting the fossil fuel-based carbon energy sources with renewable energy sources. Passive strategies, which are devised to provide thermal comfort in buildings are examples of how to use renewable energies. For this study, a dairy product warehouse in the city of Yazd in Iran was thoroughly investigated. The main goal of this study is to introduce different scenarios, then identifying them based upon optimization of energy consumption. Another main purpose of the present study is to maximize the use of passive energy to meet the cooling needs of a dairy products warehouse in the studied area. Underground temperature is lower than the surface in summer, also it is higher in winter. Therefore, this property of soil is investigated by using nine different scenarios at different heights for constructing underground warehouse for storing dairy products. Clearly, different renewable tools like wind turbine, wind catcher, solar chiller, and different roof designs by Savanah grass, roof pond are also investigated. At first, the cooling load of the warehouse is calculated separately for each season. Then, according to the energy load values obtained, the nominated scenarios are investigated. The results of the comparisons show that the construction of a warehouse at a depth of 3 m from the ground with a green roof covered with Savannah grass helps achieve the best degree of reduction in the cooling power.

This paper presents computational fluid dynamics (CFD) techniques in modeling the pollution distribution from thermal power plant. Carbon dioxide (\(CO_{2}\)) dispersion from a thermal power plant was simulated. The mathematical model and numerical algorithm were tested using a test problem and gave a good match with the experimental data. The influence of gravity force was taken into account. The k-epsilon model of turbulence with the buoyancy force was used. Calculations were performed by ANSYS Fluent. As a result, there was found a distance from the source at which the impurity settles on the ground surface.

The active development of the industry leads to an increase in the number of factories, plants, thermal power plants, nuclear power plants, thereby increasing the amount of emissions into the atmosphere. Harmful chemicals are deposited on the soil surface, remain in the atmosphere, which leads to a variety of environmental problems which are harmful for human health and the environment, flora and fauna. Considering the above problems, it is very important to control the emissions to keep them at an acceptable level for the environment. In order to do that it is necessary to investigate the spread of harmful emissions. The best way to assess it is the creating numerical simulation of gaseous substances’ motion. In the present work the numerical simulation of the spreading of emissions from the thermal power plant chimney is considered. The model takes into account the physical properties of the emitted substances and allows to calculate the distribution of the mass fractions, depending on the wind velocity...