Authors:Amoo O; Fagbenle R, Oyewola M. Pages: 1012 - 1035 Abstract: AbstractThis research is a study assessing the performance of hybrid nanofluids in hybrid photovoltaic (PV)–thermal systems. This study addresses 10 hybrid nanofluids applied to hybrid PV–thermal systems. The transition to carbon-free energy can mitigate the worst effects of climate change, ensuring that global sustainability is addressed. Clean energy is now responsible for one-third of the global capacity, of which 20% is attributed to solar energy. Renewables continue to be economically viable, with declining costs driving growth. This study aims to compare the yearly performances of a model hybrid PV–thermal system using 10 different hybrid nanofluids. Hybrid nanofluids constitute two or more dissimilar materials stably suspended in a base fluid (e.g. water). MATLAB and COMSOL Multiphysics® computational fluid dynamics software are employed together for the benchmarking assessment with good agreement observed. Various fluid inlet temperatures (Tin ∈ [300, 360] K), nanofluid volume concentrations (φ ∈ [0, 4]%) and storage-tank volumes (V ∈ [50, 300] L) were simulated. The meteorological data applied were those for Lagos, Nigeria (6° 27’ 55.5192” N, 3° 24’ 23.2128” E). The assessment based on analytical-numerical solutions reveals that the thermal enhancement by hybrid nanofluids ranges from 6.7% (graphene oxide [GO]—multiwalled carbon nanotube [MWCNT]/water) to 7% (ZnO—Mn–ZnFe2O4/water) for φ = 2% and V = 300 L. The yearly exergy efficiency ranges from 2.8% (ZnO—Mn–ZnFe2O4/water) to 2.9% (GO—MWCNT/water), also for φ = 2% and V = 300 L. These findings have implications for a vast range of industrial processes, expanding the knowledge that is critical to a sustainable future.A combined solar PV-thermal system that stores thermal energy using nanofluids is modelled. Hybrid nanofluids (two or more dissimilar materials stably suspended in a base fluid) are shown to enhance the annual electrical, thermal and exergetic outputs of the system. PubDate: Sat, 05 Mar 2022 00:00:00 GMT DOI: 10.1093/ce/zkac008 Issue No:Vol. 6, No. 2 (2022)
Authors:Janamala V; Radha Rani K. Pages: 1036 - 1052 Abstract: AbstractThis paper proposes to resolve optimal solar photovoltaic (SPV) system locations and sizes in electrical distribution networks using a novel Archimedes optimization algorithm (AOA) inspired by physical principles in order to minimize network dependence and greenhouse gas (GHG) emissions to the greatest extent possible. Loss sensitivity factors are used to predefine the search space for sites, and AOA is used to identify the optimal locations and sizes of SPV systems for reducing grid dependence and GHG emissions from conventional power plants. Experiments with composite agriculture loads on a practical Indian 22-bus agricultural feeder, a 28-bus rural feeder and an IEEE 85-bus feeder demonstrated the critical nature of optimally distributed SPV systems for minimizing grid reliance and reducing GHG emissions from conventional energy sources. Additionally, the voltage profile of the network has been enhanced, resulting in significant reductions in distribution losses. The results of AOA were compared to those of several other nature-inspired heuristic algorithms previously published in the literature, and it was observed that AOA outperformed them in terms of convergence and redundancy when solving complex, non-linear and multivariable optimization problems.Optimal solar photovoltaic system locations and sizes in electrical distribution networks are derived using a novel Archimedes optimization algorithm in order to minimize network dependence and pollutant emissions to the greatest extent possible. PubDate: Sat, 05 Mar 2022 00:00:00 GMT DOI: 10.1093/ce/zkac010 Issue No:Vol. 6, No. 2 (2022)
Authors:Wei L; Xv S, Li B. Pages: 1053 - 1061 Abstract: AbstractA short-term wind power prediction method is proposed in this paper with experimental results obtained from a wind farm located in Northeast China. In order to improve the accuracy of the prediction method using a traditional back-propagation (BP) neural network algorithm, the improved grey wolf optimization (IGWO) algorithm has been adopted to optimize its parameters. The performance of the proposed method has been evaluated by experiments. First, the features of the wind farm are described to show the fundamental information of the experiments. A single turbine with rated power of 1500 kW and power generation coefficient of 2.74 in the wind farm was introduced to show the technical details of the turbines. Original wind power data of the whole farm were preprocessed by using the quartile method to remove the abnormal data points. Then, the retained wind power data were predicted and analysed by using the proposed IGWO–BP algorithm. Analysis of the results proves the practicability and efficiency of the prediction model. Results show that the average accuracy of prediction is ~11% greater than the traditional BP method. In this way, the proposed wind power prediction method can be adopted to improve the accuracy of prediction and to ensure the effective utilization of wind energy.A short-term wind power prediction method is designed and tested with experimental results obtained from a wind farm located in Northeast China. In order to improve the accuracy of the prediction method, the improved grey wolf optimization algorithm has been adopted to optimize its parameters. PubDate: Sat, 05 Mar 2022 00:00:00 GMT DOI: 10.1093/ce/zkac011 Issue No:Vol. 6, No. 2 (2022)
Authors:Kabir Ahmad S; Md Ali U, Md Isa K, et al. Pages: 1062 - 1069 Abstract: AbstractLignocellulosic biomass especially, sugarcane bagasse Saccharum barberi sp., appears to be a more suitable material for partial substitution of transport fuel (diesel) than Saccharum officinarum sp., due to its structural similarity to transport fuel (diesel). Besides that, less research has been implemented on this type of species. Bio-oil can be implemented as biodiesel by processing it further using chemical reactions such as hydrodeoxygenation and cracking with zeolite catalyst. Hence, the purpose of this study is to determine the compatibility of pyrolytic bio-oil produced from Saccharum barberi sp. in comparison with S. officinarum sp. for use as transport fuel (diesel) in automotive applications. This purpose can be accomplished by comparing the oil’s bio-physiochemical properties for both species. The experiment is conducted on a bench-scale on which bio-oil of Saccharum barberi sp. is secured from the catalytic pyrolysis process at a temperature of 500°C and heating rate of 50°C/min with the addition of ZSM-Zeolite catalyst. Thermogravimetric analysis of Saccharum barberi sp. reveals that cellulose is more reactive than lignin, evidenced by the high percentage of weight loss at temperatures ranging from 251°C to 390°C. The high contents of carbon (40.7%) and hydrogen (6.50%), as well as slight traces of sulphur (0.08%) and nitrogen (0.85%), in bio-oil (Saccharum barberi sp.) indicate that it is conceivable to be partially used for replacement in biofuel production. Overall physiochemical properties reveal that Saccharum barberi sp. shows more potential than S. officinarum sp. Gas chromatography–mass spectrometry analysis reveals that bio-oil consists of high amounts of aromatic hydrocarbon (26.2%), phenol (14.8%) and furfural (13.0%) in comparison to S. officinarum sp.Biofuel was produced from sugarcane bagasse (Saccharum barberi sp.) in a bench-scale pyrolysis reactor at 500°C using a zeolite catalyst. Measured properties of the biofuel make it suitable for partial substitution of diesel in transport fuel. PubDate: Sat, 05 Mar 2022 00:00:00 GMT DOI: 10.1093/ce/zkac012 Issue No:Vol. 6, No. 2 (2022)
Authors:Feng B; Yu B. Pages: 1070 - 1077 Abstract: AbstractChina will strive to achieve a ‘dual carbon’ target: ‘carbon peak’ by 2030 and ‘carbon-neutral’ by 2060. In this context, improving the efficiency of renewable energy and reducing the use of thermal power are important ways to achieve the target. Clean, efficient and large-capacity energy-storage technology is the key to improving the utilization rate of renewable energy. First, this paper proposes to use compressed-air energy-storage technology instead of the old energy-storage technology to build an economical and environmentally friendly comprehensive energy park capacity optimization configuration model. Second, this paper uses the newly proposed improved chicken swarm optimization algorithm to solve the model, which is more accurate and faster. Finally, this paper analyzes a comprehensive energy park in north-west China. Through case analysis, it can be seen that the average utilization rate of renewable energy can reach 73.87% through the model proposed in this paper, while the average power-abandonment rate is only 9.32%. PubDate: Tue, 05 Apr 2022 00:00:00 GMT DOI: 10.1093/ce/zkac017 Issue No:Vol. 6, No. 2 (2022)
Authors:Kursun B. Pages: 1078 - 1089 Abstract: AbstractThis work covers a three-stage evaluation: cradle-to-grave life-cycle assessment (LCA) of polycrystalline silicon (pc-Si) and monocrystalline silicon (mc-Si) solar photovoltaics (PVs) as on-grid utility-scale energy options; environmental-impact distribution of pc-Si and mc-Si combinations under local conditions in Turkey; and assessment of the role of solar power in improving the environmental performance of the Turkish electricity mix. In LCA, mc-Si panels are found to have 4.47–9.16% higher environmental impacts than pc-Si panels in absolute terms. However, the higher efficiency and slower degradation rate of mc-Si panels make them have lower impacts on a kWh electricity basis. For the solar PV combination, the global-warming potential (GWP) and human-toxicity potential (HTP) results are found to be significantly lower than that of home-scale pc-Si systems (27.1–34.4 g versus 33.7–59.9 g CO2 equivalent (eq)/kWh 30.6–38.9 g versus 65.9–117 g 1–4 dichlorobenzene (g 1–4 DB) eq/kWh) operating in Turkey due to the higher capacity and efficiency of the utility-scale system. This result reveals the advantage of utilizing solar power as a centralized energy option for the country. All of the eight impacts that we evaluated reduce increasingly with increasing solar percentage in the electricity mix. The general tendency is that each percentage increase in solar electricity in the mix reduces each impact by ~1.0%. With a conservative assumption, if the solar power ratio in the mix increases to 15% by 2030, a GWP reduction of 31.3 million tons can be achieved. This corresponds to 12.7% of the greenhouse-gas mitigation commitment (246 million tons CO2 eq) made by Turkey under the United Nations Framework Convention on Climate Change. With the Turkish electricity sector being dominated by imported coal and natural gas, the obtained results reveal the potential of solar power in improving the environmental performance of the electricity mix in Turkey. PubDate: Sat, 09 Apr 2022 00:00:00 GMT DOI: 10.1093/ce/zkac002 Issue No:Vol. 6, No. 2 (2022)
Authors:Shrestha S; Lohani S. Pages: 1090 - 1099 Abstract: AbstractHousehold biodigesters are self-mixing anaerobic digesters used mostly in rural areas of developing countries as a reliable source of clean cooking energy. For an efficient anaerobic digestion process, the mixing of slurry inside the digester is regarded as one of the most important parameters. In this study, the mixing of slurry in three different designs of household digesters, namely the fixed-dome digester (GGC 2047 model), plug-flow digester and prefabricated plastic digester, are investigated and compared using computational fluid dynamics. A 3D transient simulation is performed using a multiphase volume of fluid (VOF) model in Ansys® Fluent release 16.0. The rheological properties of the feedstock are considered identical for all three digesters. The volume of the plug-flow and prefabricated plastic digesters is designed to be 1 m3 while the volume of the GGC 2047 digester was 6 m3 as the standard size of the household digester. The regions inside the digester where the velocity of slurry is <0.02 m/s are regarded as dead zones and the obtained results were analysed and compared using velocity patterns and dead-zone formation. It is found that the prefabricated plastic digester model has a relatively higher percentage of dead volume (74.6%) and the plug-flow digester has the lowest percentage (54%) of dead volume among digesters that were compared in this study. The study will serve as the basis for designers and researchers to improve the design of household digesters for better mixing performances. PubDate: Wed, 13 Apr 2022 00:00:00 GMT DOI: 10.1093/ce/zkac009 Issue No:Vol. 6, No. 2 (2022)
Authors:Kumar L; Lakshmiprasad C, Ramaraj G, et al. Pages: 1100 - 1117 Abstract: AbstractWater is an essential resource for agriculture and the majority of land is irrigated through borewells or wells. The power requirement for an irrigation pump motor is fed by the on-grid power supply but the availability of electricity in rural areas is still questionable. With rising concerns about global warming and the rise in carbon footprints, it is necessary to choose clean and green energy, thereby attaining self-sustainable life. India receives yearly a mean solar irradiation of 6.5 kWh/m2day. Hence, a solar photovoltaic–water-pumping system (SPV–WPS) is a suitable alternative to grid energy; thereby, the farmers would generate electricity through the solar photovoltaic system and become self-sufficient in their energy needs. In this paper, two different agricultural fields in Tamil Nadu, India that deploy flood irrigation and drip irrigation are taken as a case study. The paper discusses the concerns on the use of grid power and their carbon footprint, design and simulation of 4- and 5.5-kW SPV–WPSs using PVsyst 7.1.1, and the advantages of using SPV–WPSs and life-cycle cost analysis on different use cases. The Government of India has introduced a special scheme to promote the installation of SPV–WPSs by offering attractive incentives through PM-Kisan Urja Suraksha evam Utthaan Mahabhiyan (KUSUM) yojana. The results of the case study show that with the use of SPV–WPSs, either with or without subsidy, the farmer could gain a minimum of 250% on the investment with a project lifetime of 25 years. PubDate: Wed, 13 Apr 2022 00:00:00 GMT DOI: 10.1093/ce/zkac018 Issue No:Vol. 6, No. 2 (2022)
Authors:Semeskandeh S; Hojjat M, Hosseini Abardeh M. Pages: 1118 - 1126 Abstract: AbstractPhotovoltaic (PV) systems can be used to generate electricity due to the potential for solar energy in Iran. Applying floating photovoltaic (FPV) systems is a new approach to utilizing PV systems in water. Most of Iran’s energy consumption is supplied from fossil fuels, especially oil and gas. In recent years, Iran has faced environmental problems and air pollution. Electricity generation using fossil fuels has led to increased environmental pollution. Accordingly, PV systems can be used to generate electricity due to the potential for solar energy in Iran. The interest in predicting the energy production of PV power plants has increased in recent years. In this regard, the techno–economic–environmental study of constructing PV power plants is a basic process to encourage people to use solar energy. A techno–economic–environmental feasibility study has been performed to construct a 5-kW FPV and ground PV (GPV) power plant in a northern city of Iran. Also, the FPV system is compared with the ground PV system using MATLAB® Simulink and RETScreen® software. In this study, the effects of wind and water temperature have been considered. Also, a sensitivity analysis was performed due to the uncertainty in climatic conditions and the amount of PV energy generation. The simulation results show that due to the cooling effect for panels in the FPV system, the production capacity and panels’ efficiency are respectively 19.47% and 27.98% higher than the those of the GPV system. In addition, the FPV system was found to have a 16.96% increase in the annual performance ratio. Overall, using the FPV system reduces the equity payback to 6.3 years (a 22.2% reduction compared to the GPV power plant). PubDate: Wed, 13 Apr 2022 00:00:00 GMT DOI: 10.1093/ce/zkac019 Issue No:Vol. 6, No. 2 (2022)
Authors:Vatankhah Ghadim H; Fallah Ardashir J. Pages: 1127 - 1136 Abstract: AbstractDue to the fuel security and environmental concerns of traditional energy resources like fossil fuels, grid operators are tending to use renewable energies as the primary energy supply. This paper presents the study of designing, simulation and analysis of a 100-kWp on-grid photovoltaic power plant (PV-PP) in north-western Iran. Accurate meteorological data, satellite images and local knowledge from this region have narrowed down the options to three highly irradiated cities of Maragheh, Mahabad and Khalkhal in this region. PVsyst and MATLAB software are used in this paper to obtain the performance results. Environmental effects and carbon-emission savings from the execution of the proposed PV-PP are also available in this paper. The result of this study shows that PV-PP installation in Maragheh will have higher energy output than the two other cities. This study is insightful for the academics and the grid stakeholders in finding optimal spots in north-western Iran to construct a PV-PP. Also, recommendations are available for future studies.A 100-kWp on-grid photovoltaic power plant is designed in north-western Iran. Accurate meteorological data, satellite images, and local knowledge are used in a simulation to select the best location from among three cities. PubDate: Sat, 16 Apr 2022 00:00:00 GMT DOI: 10.1093/ce/zkac013 Issue No:Vol. 6, No. 2 (2022)
Authors:Ghosh S; Roy J, Chakraborty C. Pages: 1137 - 1156 Abstract: AbstractApart from being a clean source of energy, photovoltaic (PV) power plants are also a source of income generation for its investors and lenders. Therefore, mitigation of system losses is crucial for economic operation of PV plants. Combined losses due to soiling, shading and temperature in PV plants go as high as 50%. Much of these losses are unaccounted initially, which can jeopardize the economic viability of PV projects. This paper aims to provide a model to determine losses due to soiling, shading and temperature using quantities like irradiance, cell temperature, DC power and current, which are readily available in PV yield data captured by the remote monitoring system, without involving any additional sensors or equipment. In this study, soiling, shading and thermal losses were calculated using PV yield data obtained from a 30-kWp PV plant located in Kharagpur, India. The results showed soiling and shading losses as high as 25.7% and 9.7%, respectively, in the month of December. Soiling loss was verified by measuring transmittance loss of coupon glasses installed in the vicinity of the plant. Shading loss was verified by shadow simulation using an architectural tool (SketchUp). Array thermal loss obtained using the proposed methodology was found to be in line with the estimated value obtained from PVsyst simulation. Additionally, using time-series data, the energy losses corresponding to soiling, shading and temperature effects were calculated by a numerical-integration technique. The monetary loss due to these energy losses thus obtained provides criteria for deciding when to mitigate the sources of these losses. PubDate: Fri, 29 Apr 2022 00:00:00 GMT DOI: 10.1093/ce/zkac014 Issue No:Vol. 6, No. 2 (2022)
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