Browsing by Author "Afzal, A."

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Optimum location and influence of tilt angle on performance of solar PV panels
(2019) Yunus, Khan, T.M.; Soudagar, M.E.M.; Kanchan, M.; Afzal, A.; Banapurmath, N.R.; Akram, N.; Mane, S.D.; Shahapurkar, K.
With the growing demand of economically feasible, clean, and renewable energy, the use of solar photovoltaic (PV) systems is increasing. The PV panel performance to generate electrical energy depends on many factors among which tilt angle is also a crucial one. Among hundreds of research work performed pertinent to solar PV panels performance, this work critically reviews the role of tilt angles and particularly locating the optimum tilt angle using different methods. The past data collected for analysis can be categorized mainly into mathematical model based, experimental based, simulation based, or combination of any of these. Single-axis tracking, dual-axis tracking, simple glass cover, hydrophobic glass cover, soiled glass, clean glass, partial shadow, use of phase-change material, computational fluid dynamic analysis, etc., are the novel methods found in the literature for analysis and locating the optimum tilt angle. For illustration purpose, few figures are provided in which the optimum tilt angle obtained on monthly, seasonally, and annual basis is shown. Research works are growing in the field of computations and simulations using online software and codes. Pure mathematical-based calculations are also reported but the trend is to combine this method with the simulation method. As the PV panel performance is found to be affected by number of parameters, their consideration in any single study is not reported. In future, work is required to carry out the experiment or simulation considering the effect of soiling, glass material, temperature, and surrounding ambience on the location of optimum tilt angle. As a whole, the optimum tilt angles reported for locations exactly on the equator line, i.e., 0 latitude, ranges between ? 2.5 and 2.5 , for locations just above the equator line, i.e., latitude 2.6 30 N ranges between 5 and 28 , for 40 70 N, it is 29 40 , and for 71 90 N, it is 41 45 . For locations at 2.6 30 S, optimum tilt angles range between ? 4 and ? 32 , 30 46 S, it is ? 33 to ? 36 , 47 65 S, it is ? 34 to ? 50 , and for 66 90 S it is ? 51 to ? 62 . 2019, Akad miai Kiad , Budapest, Hungary.
Optimum location and influence of tilt angle on performance of solar PV panels
(Springer Science and Business Media B.V., 2020) Khan, T.M.; Soudagar, M.E.M.; Kanchan, M.; Afzal, A.; Banapurmath Nagaraj, N.R.; Akram, N.; Mane, S.D.; Shahapurkar, K.
With the growing demand of economically feasible, clean, and renewable energy, the use of solar photovoltaic (PV) systems is increasing. The PV panel performance to generate electrical energy depends on many factors among which tilt angle is also a crucial one. Among hundreds of research work performed pertinent to solar PV panels performance, this work critically reviews the role of tilt angles and particularly locating the optimum tilt angle using different methods. The past data collected for analysis can be categorized mainly into mathematical model based, experimental based, simulation based, or combination of any of these. Single-axis tracking, dual-axis tracking, simple glass cover, hydrophobic glass cover, soiled glass, clean glass, partial shadow, use of phase-change material, computational fluid dynamic analysis, etc., are the novel methods found in the literature for analysis and locating the optimum tilt angle. For illustration purpose, few figures are provided in which the optimum tilt angle obtained on monthly, seasonally, and annual basis is shown. Research works are growing in the field of computations and simulations using online software and codes. Pure mathematical-based calculations are also reported but the trend is to combine this method with the simulation method. As the PV panel performance is found to be affected by number of parameters, their consideration in any single study is not reported. In future, work is required to carry out the experiment or simulation considering the effect of soiling, glass material, temperature, and surrounding ambience on the location of optimum tilt angle. As a whole, the optimum tilt angles reported for locations exactly on the equator line, i.e., 0° latitude, ranges between ? 2.5° and 2.5°, for locations just above the equator line, i.e., latitude 2.6°–30° N ranges between 5° and 28°, for 40°–70° N, it is 29°–40°, and for 71°–90° N, it is 41°–45°. For locations at 2.6°–30° S, optimum tilt angles range between ? 4° and ? 32°, 30°–46° S, it is ? 33° to ? 36°, 47°–65° S, it is ? 34° to ? 50°, and for 66°–90° S it is ? 51° to ? 62°. © 2019, Akadémiai Kiadó, Budapest, Hungary.
Quantitative Analysis of Solar Photovoltaic Panel Performance with Size-Varied Dust Pollutants Deposition Using Different Machine Learning Approaches
(MDPI, 2022) Tripathi, A.K.; Mangalpady, M.; Elumalai, E.P.; Abbas, M.; Afzal, A.; Saboor, S.; Linul, E.
In this paper, the impact of dust deposition on solar photovoltaic (PV) panels was examined, using experimental and machine learning (ML) approaches for different sizes of dust pollutants. The experimental investigation was performed using five different sizes of dust pollutants with a deposition density of 33.48 g/m2 on the panel surface. It has been noted that the zero-resistance current of the PV panel is reduced by up to 49.01% due to the presence of small-size particles and 15.68% for large-size (ranging from 600 µ to 850 µ). In addition, a significant reduction of nearly 40% in sunlight penetration into the PV panel surface was observed due to the deposition of a smaller size of dust pollutants compared to the larger size. Subsequently, different ML regression models, namely support vector machine (SVMR), multiple linear (MLR) and Gaussian (GR), were considered and compared to predict the output power of solar PV panels under the varied size of dust deposition. The outcomes of the ML approach showed that the SVMR algorithms provide optimal performance with MAE, MSE and R2 values of 0.1589, 0.0328 and 0.9919, respectively; while GR had the worst performance. The predicted output power values are in good agreement with the experimental values, showing that the proposed ML approaches are suitable for predicting the output power in any harsh and dusty environment. © 2022 by the authors.
The potential of nanoparticle additives in biodiesel: A fundamental outset
(American Institute of Physics Inc. subs@aip.org, 2020) Soudagar, M.E.M.; Ghazali, N.-N.; Akram, N.; Al-Rashid, M.A.; Badruddin, I.A.; Khan, H.; Kallannavar, V.; Shahpurkar, K.; Afzal, A.; Farade, R.; Taqui, S.N.; Ukkund, S.J.
Biodiesel is an unparalleled alternative fuel source envisioned to encompass the significance of diesel fuel and reduce greenhouse gas emissions because to its locked carbon cycle. However, it increases the nitrogen oxide emission, regular engine parts replacement due to clogging, and is not suitable in cold weather conditions. The addition of nanoparticles (metallic, non-metallic, oxygenated, organic and amalgamation) with diesel-biodiesel emulsion fuels results in an enhancement in the engine performance, thermo-physical properties, enrichment in the heat transfer rate, the equilibrium of the fuel mixtures and drop in the exhaust emissions reliant on the prescription of nanoparticle additives. The review intends to demonstrate the most recent nanoparticle additives used in diesel-biodiesel fuels. Â© 2020 Author(s).