banner

Blog

Oct 15, 2024

Performance optimization for solar photovoltaic thermal system with spiral rectangular absorber using Taguchi method | Scientific Reports

Scientific Reports volume 14, Article number: 23849 (2024) Cite this article

81 Accesses

1 Altmetric

Metrics details

Solar collector systems efficiently transform sunlight into energy that may be used to meet various needs. This research aimed to use the Taguchi method to determine the ideal operating parameters for a solar thermal collector with a rectangular spiral absorber. Controllable parameters including mass flow rate, solar radiation, and absorber design were manipulated during the energy recovery process, and features like PV temperature and outlet water temperature were used to assess the system’s effectiveness. The findings indicate that certain criteria significantly affect response indicators. The observed percentage contribution of absorber design, solar radiation, and the mass flow rate was 69.19%, 27.99%, and 2.83% in PV surface temperature. In comparison, the individual percentage contributions were 73.63%, 13.51%, and 10.57% for absorber design, solar radiation and mass flow rate for water output temperatures. The present model’s R2 values for PV and outlet water temperatures are 97.24% and 99.67%, respectively. The Predictive regression model was found in fine harmony and the maximum percentage error is limited to 0.68%. The maximum analytical electrical efficiency was observed with a spiral rectangular absorber of 14.57% at the lowest mass flow rate of 0.04 kg/s at the lowest radiation level of 600 W/m2. In comparison, maximum analytical thermal efficiency was observed with a spiral rectangular thermal absorber of 63.56% at the highest flow rate of 0.06 kg/s and the highest solar radiation level of 1000 W/m2. The analytical and experiment findings were in better agreement in this study, with the highest relative error of 7.52%. According to the study’s findings, the rectangular absorber-based PVT system is at its best at a higher mass flow rate to lower PV temperature and boost thermal energy recovery via water. The present research work can be extended for exergy, environmental, and economic feasibility analysis.

During 2020, the amount of solar power generated was 724.09 terawatt-hours, which is roughly a 10.30% share of total renewable energy generation1. Solar thermal collectors capture solar radiation and transform it into heat, while solar photovoltaic collectors convert solar radiation into electrical power. Because solar PV technology generates electricity directly without the need for moving parts, it has grown in popularity. According to the study2, the PV system performed better electrically when it had an additional cooling arrangement, and the coolant was able to recover thermal energy3,4,5. This type of hybrid, or photovoltaic-thermal, power generation from a single collector is known as a PVT system. The primary factor that determines a solar collector’s reach, longevity, and acceptance in society at large is its efficiency. The literature notes the attempts6 to adjust operational and design factors in order to maximize the performance of solar collectors. To assess and improve the performance of the solar system, a variety of optimization approaches7 were offered. The Taguchi technology is one of the optimization techniques preferred by the researcher community to control and optimize parameters as per desired performance. The parametric optimization of paraffin vax-based phase change material was performed for thermal storage using the Taguchi methodology8. The L9 orthogonal array was selected for a level, three-factor experimental design. The optimization study determined the optimum condition for melting time and time-dependent enhancement ratio for thermal storage. In a recent study9, Taguchi methodology was applied to identify influencing parameters that affect the energy performance of PVT systems particularly for the different climatic zones of Morocco. The study showed that optimized values of process parameters not only improved energy (electrical-thermal) performance but also mitigated higher CO2 as compared to a non-optimized PVT systems. The following table shows the latest survey on the effectiveness of the Taguchi methodology in the solar system to decide and optimize operating and design parameters. The Taguchi-based optimization study was performed for the PVT system by varying coolant and its concentration at varying flow rates and radiation levels10. In the study, SiO2-W, Al2O3- W, and CuO-W at 0.1, 0.2, and 0.3 as volume concentrations were investigated for electrical and thermal efficiency at 0.55, 1.1, and 1.65 lpm flow rate and 300, 600 and 900 W/m2 radiations. It was observed that electrical efficiency mainly depends on irradiance followed by flow rate, volume concentration, and nanofluid while thermal efficiency is affected by the irradiance followed by flow rate, nanofluid, and volume concentration. The compound parabolic collector solar PVT system was optimized using Taguchi methodology11. In the study, thickness, air gap thickness, glass cover thickness, nanoparticles, mass fraction, and PV efficiency were the operating parameters parameters while heat transfer and performance efficiency were the output responses. From the study, it was observed that highest overall performance of the PVT system was 71.1%, at 2 mm glass cover thickness, 10 mm air gap thickness, 21% PV cell efficiency, and 6% nanoparticle mass fraction. The different types of solar collectors such as solar Air heaters with tin cans, solar Air heaters with reflecting mirrors- tin cans, and solar Air heaters with triangular fins were investigated using Taguchi methods for parametric optimization12. The responses were recorded in terms of outlet temperature of the air, thermal efficiency, pressure drop, exergy, and exergy loss. It was observed that each solar heater performs better in particular hours such as an Air Heater with reflecting mirrors- tin cans during the noon period. A tabulated details of control parameters can be found in Table 1.

It was observed in the literature that many researchers have preferred the Taguchi optimization methodology for performance optimization due to its time-cost effectiveness and ease of result explanation. During the development stage of the system, Taguchi optimization plays an instrumental role in evaluating the optimum performance parameters. It was also observed in the literature that coolant type, low-rate radiation level absorber type; thickness, and flow pattern are key design parameters that affect PVT performance. In PVT design flat plate, circular type thermal absorbers are common thermal absorber type but very few have tried rectangular type of thermal absorber. Additionally, a comparative optimization study among simple PV, circular absorber-based PVT, and rectangular absorber-based PVT was not found in the literature. The present study aims to compare and optimize major effective parameters that improve PVT efficiency and also validate in experimental settings.

The goal of the current study is to use the Taguchi technique to maximize the performance of solar flat panel photovoltaic thermal systems. To determine the importance and ideal arrangement of particular design and operational parameters impacting PV and output water temperatures, the Taguchi technique is used. The water flow rate, incident solar radiation level, and thermal absorber design are among the chosen criteria. The radiation levels used for the performance were in the range of 600–1000 W/m2, with three flow rates of 0.04–0.06 kg/sec. The PV module’s backside is where the non-absorber, spiral circular, and spiral rectangular thermal absorbers are mounted. Comparative analysis and analysis of variance using the Taguchi methodology are used to determine the role of various factors on the surface temperature and water outlet temperature of PV and PVT systems. The performance equation and statistical significance of the parameters were created based on Taguchi optimization.

The Taguchi design is a fractional factorial design that estimates maximum numbers of main effects from minimum runs of the experiment using an orthogonal array. Based on the literature survey, the current study selected the absorber design, solar radiation, and mass flow rate of circulating fluid factors as significant factors that impact performance. In absorber design, no absorber (also called conventional PV) is designed named A1, spiral circular thermal absorber (A2), and spiral rectangular thermal absorber (A3) is made up of the same material and dimensions are preferred, and design is shown in Fig. 1. All the results obtained from the CFX 19.2 simulation are used to optimize. The photograph of the experiment can be found in Fig. 2 The methodology adopted for optimization is, as shown in the flowchart below Fig. 3.

Pictorial views of proposed Thermal absorber configurations for analysis.

Experimental test rig.

The parameter such as ambient temperature, PV surface temperature, water inlet and outlet temperature, outlet water temperature, PV voltage, PV current and radiation intensity was measured with various instruments. The ambient air temperature was measured with a mercury-based thermometer. The PV surface temperature, inlet-outlet water temperature were measured with a K-type thermocouple. The thermocouples were placed; temperatures were stored and displayed with a temperature acquisition system. The 100 W poly-crystalline PV panels were used for research purposes with reference efficiency of 14.9%. The voltage and current of PV are measured by voltmeter and ammeter respectively. Each set of experiments is recorded after a 30-minute interval, including solar irradiation, water temperature, PV, PVT V-I characteristics, ambient temperature, and surface temperature. The descriptions of Thermal absorber collector systems are enlisted in Table 2. In the experimental work, range of measuring instruments and their uncertainty has vital role hence uncertainty analysis needs to perform. The Table 3 represents instrument used for measuring performance parameter and their individual error.

Flowchart showcasing methodology adopted for Taguchi analysis.

Table 4 represents the DoE of the experimentation. The design of the experiment is proposed with three factors (n) with three-level (L) variable, number of experiments need to be conducted for three parameters is given by26,

No of Experiment = Degree of Freedom (DOF) + 1 = n (n-1) + 1.

Therefore, L9 Orthogonal Array (OA) is selected for Taguchi Analysis27. The number of experiments is conducted according to L9 OA is reported in table no.

The S/N ratio measures the performance of control factors that affect process variability. The S/N ratios minimize the effect of noise factors and are classified according to preferred characteristics28.

Where Yi is observed data, Ym is observed data average, Svis variation in Yi, and n is a number of experimental observations.

As discussed in the introduction part, the electrical performance of PV module depends on its instantaneous surface temperature and given by29,

Where ɳref is reference efficiency of PV panel as per manufacturer’s catalogue (14.9%), γ is constant temperature coefficient and has a value of 0.0045/°C, Tcell is the instantaneous temperature of PV panel while Tref is the reference PV surface temperature (25 °C).

Whereas thermal efficiency can be obtained from equation,

Where CP is specific heat of water at constant pressure and has the value of 0.4187 kJ/kg-K, and Ar is area of PV panel.

The error analysis is performed using general form of Kline and McClintock method

Where, R= {m, Tout, Tin, Ac, Ig, Voc, Isc} are the average value of parameters.

Hence, by applying Eq. (6) to evaluate uncertainty in the thermal efficiency (WɳT)

Similarly equation for uncertainty in electrical efficiency is developed and uncertainty is calculated30,31,32.

The results obtained from numerical simulation were summarized in a table and utilized to execute Taguchi analysis using Minitab 21.1 software. The methodology was adopted to optimize PV surface temperature and outlet water temperature according to S/N ratios and means calculated by Minitab software.

The response values obtained for PV Temperature by Taguchi designs are summarized in Table 4. The voltage carrying capacity decline at elevated PV temperature resulted in power loss; hence lower the better characteristics were selected. From the main effect plot, it is observed that the third level of factor A (Absorber design), the first level of factor Si (Solar radiation), and the second level of factor Mf (mass flow rate) are higher. Hence, for minimum PV temperature optimum configuration, it can be concluded that the optimum configuration is a spiral rectangular thermal absorber with 0.05 mass flow rates at 600 W/m2. From the response table, the value of delta and rank shows that factor A has the highest significance on PV temperature, followed by factor Si and Mf. The importance of lower PV temperature lies in a higher electrical energy conversion by PV panel. At the higher PV surface temperature, voltage output reduces and result in lower electrical power generation33,34. Hence, operating PV at a lower temperature is recommended to ensure better power generation and improve PV panel life.

The results obtained from Minitab 21.1version software by applying Taguchi design for outlet water temperature are shown in Table 5, Fig. 4. The larger, the better option is selected, and optimum levels of factors are identified using the S/N ratio. Taguchi prediction shows that the third level of factor A, the third level of factor Si and the first level of factor mf are higher. Therefore maximum water temperature at the outlet will be achieved from a spiral rectangular thermal absorber at 0.04 kg/sec with 1000 w/m2 radiation. The response table shows that absorber design is the most influencing factor in water temperature trailed by radiation value and mass flow rate. The water circulated from the thermal absorber reduces the temperature of the PV surface and recuperate heat energy to enhance overall energy output35. As A1 is no absorber level, it does not influence thermal efficiency. The rectangular absorber design recovers heat effectively due to better surface area contact with the backside of the PV surface than the spiral circular absorber design. This recovered heat through water can be effectively used for domestic or process heat industrial applications.

(a) Plot for means; (b) plot for signal to noise ratio (S/N).

The ANOVA was executed to predict the implication of the process parameter that affects desired performance36. The result obtained from ANOVA analysis for PV temperature and outlet water temperature were tabulated in Tables 6 and 7, respectively. From Table 6, it was observed that PV surface temperature is significantly influenced mainly by absorber design followed by solar radiation and water flow rate, respectively. The observed percentage contribution of absorber design, solar radiation and the water flow rate was 69.19%, 27.99% and 2.83%, as shown in Table 6. Similarly, the outlet water temperature was influenced mainly by absorber design followed by solar radiation and mass flow rate. The respective percentage contributions were 73.63%, 13.51% and 10.57% for absorber design, solar radiation and mass flow rate. An ANOVA analysis concludes that absorber design is the most significant parameter that affects PV and outlet water temperature.

In the current work, regression analysis was performed in Minitab 21.1 software to develop a predictive regression model that gives the relation between predictors and response variables. The mathematical equations obtained from linear regression analysis for PV and outlet water temperatures are follows. Table 8. Analysis of Variance (ANOVA) outlet Water temperature.

For PV temperature,

For water outlet temperature,

The efficiency of the developed model is evaluated from the coefficient of determination, i.e. R2 value. The range of R2 values varies from zero to one. The R2 value shows disperse of observed data values around the regression plot, and higher values represent lower variation from the regression model37. The present model’s R2 values for PV and outlet water temperatures are 97.24% and 99.67%, respectively. The developed regression model shows higher R2 values and good fitment of the model. The residual plot investigates the significance of the coefficient in the predictive regression model. The straight-line residual plot indicates residual errors are normally distributed, and coefficients in regression equations are significant. The residual plot obtained for PV Panel temperature and outlet water temperature is revealed in Fig. 5. From Fig. 6, it was observed that residuals were in proximity to the straight line for Tpanel and Twater, which implies coefficients in the developed model are promising and significant.

(a) Plot for means. (b) Plot for signal to noise ratio (S/N).

Residual plot for (a) PV temperature, (b) outlet water temperature.

The developed mathematical model was validated by conducting a confirmation test, and results were tabulated in Table 9. The test result was taken randomly and compared with predicted results. From the confirmation test, it was seen that the results of analytical analysis were found in good harmony with the predicted result. The percentage error was limited to 0.68% in the case of PV Panel temperature while 0.035% for outlet water temperature. In literature, a similar agreement between analytical and predicted results was found. Table 10. Confirmation results for the developed model.

The effect mass flow rates and solar radiation on electrical efficiency of conventional PV and PVT collector systems is discussed in Figs. 7 and 8. It was observed that the electrical efficiency of the conventional PV system was lower than the PVT system. This low efficiency were because non-cooling of the PV system at elevated radiation and surface temperature. The electrical efficiency of PV system varied in the range of 12.3-13.17%. The electrical efficiency of the spiral circular thermal absorber PVT system varied in range from 12.80 to 14.32%. On the other hand, the electrical efficiency of spiral rectangular thermal absorber PVT system varied in range from 13.40-14.57%.This higher electrical efficiency is due to the effective cooling of PV surfaces obtained from water cooling Incorporating spiral rectangular thermal absorber.

Variation in the electrical efficiency from spiral circular absorber PVT system.

Variation in the electrical efficiency from spiral rectangular absorber PVT system.

The maximum electrical efficiency of 14.57% was observed at the highest flow rate of 0.06 kg/sec under a minimum radiation level of 600 W/m2 from spiral rectangular thermal absorber PVT system while minimum electrical efficiency of 12.8% was observed at a lowest mass flow rate of 0.04 kg/sec under maximum radiation level of 1000 W/m2 from spiral circular thermal absorber PVT system.

It was clear from the Figs. 9 and 10 that thermal efficiency increases with the rise in water flow. At a higher water flow rate, more heat accumulation results in higher water outlet temperature. The similar trend of result is observed in the literature. The maximum temperature gradient was seen with a spiral rectangular thermal absorber. This gradient is because spiral rectangular thermal absorber maintained surface contact with flipside PV surface, whereas spiral circular thermal absorber maintained line contact. Similarly, rectangular flow resulted in better turbulence due to its geometrical features. The spiral rectangular thermal absorber exhibited higher thermal efficiency due to its better heat extraction features than the spiral circular thermal absorber. Analytically the maximum thermal efficiency of 63.56% was observed at the highest mass flow rate of 0.06 kg/sec under a maximum radiation level of 1000 W/m2 while minimum thermal efficiency of 52.20% was observed at a lowest flow rate of 0.04 kg/sec under minimum radiation level of 600 W/m2.

Variation in the thermal efficiency from spiral circular absorber PVT system.

Variation in the thermal efficiency from spiral rectangular absorber PVT system.

It was also seen that experimental electrical and thermal efficiency were lower in all cases than the analytical results. This variation is because analytical treatments were performed at steady-state conditions. The effect of wind speed and heat loss through conduction, convection, and radiation from PV surface is neglected; that affect the electrical and thermal efficiency in the actual case46,47. Additionally, the uncertainty analysis using Kline and McClintock method was carried out and relative uncertainties found to be 0.98% and 2.45% for thermal for electrical efficiency. Table 11 Comparative analysis of the findings with recent works (last three years).

The current study concluded that Taguchi methodology determines optimum conditions that significantly reduce PV temperature and increase the outlet water temperature to increase electrical and thermal efficiency of PVT system. The Study concluded that rectangular absorber design was the dominant and most influential factor for lowering PV and rising water outlet temperatures, followed by solar radiation and mass flow rates. The trade-off was observed about solar radiation for optimum PV and output water temperatures and should be selected as per the desired end-use. From the ANOVA analysis, PV temperature and the output water temperature was significantly affected by Absorber Design with the contribution of 69.13% and 75.63%, respectively. The present study is a foundation that provides spiral rectangular thermal absorber should be preferred over spiral circular thermal absorber, conventional PV system for better performance. In analytical treatment, the maximum thermal efficiency of 63.56% was observed at the highest mass flow rate of 0.06 kg/sec under a maximum radiation level of 1000 W/m2 from spiral rectangular thermal absorber PVT system. The maximum electrical efficiency of 14.57% was observed at the highest flow rate of 0.06 kg/sec under a minimum radiation level of 600 W/m2 from spiral rectangular thermal absorber PVT system. The experimental electrical and thermal efficiency were lower in all cases than the analytical results due to real time atmospheric condition and heat losses. Experimental uncertainties were 0.98% and 2.45% for thermal for electrical efficiency. The analytical and experiment findings were in better agreement in this study, with the highest relative error of 7.52%.

Close conformity was found between predicted and experimental results from the developed regression model as the maximum error is limited to 0.68%. Hence above-developed model could be accustomed toassess the temperature characteristics of Water-PVT systems without conducting trials.

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Ritchie, H. & Roser, M. Renewable Energy. https://ourworldindata.org/renewable-energy (2020).

Jitendrasatpute, J. R. A. Recent advancement in cooling technologies of solar photovoltaic (PV) system. FME Trans. 46, 575–584 (2018).

Article Google Scholar

Srinidhi, C. et al. Thermodynamic and exhaust emission studies of CI engine powered by neem oil methyl ester blends doped with nickel oxide nano additives. Environ. Prog. Sustain. Energy 1, e14437. https://doi.org/10.1002/ep.14437 (2024).

Article CAS Google Scholar

Srinidhi, C. et al. Relative exergy and energy analysis of DI-CI engine fueled with higher blend of Azadirachta indica biofuel with n-butanol and NiO as fuel additives. Environ. Prog. Sustain. Energy 43(3), e14336 (2024).

Article CAS Google Scholar

Gajbhiye, A. M., Sonawane, P. R., Karle, A. H. & Campli, S. Optimization of welding parameters for En8D and SAE1018 materials by Taguchi. Int. J. Interact. Des. Manuf. 1, 1–10 (2023).

Google Scholar

Mapa, L. et al. Study of the project parameters influence in the performance of solar collectors. Int. J. Heat Technol. 37, 313–321. https://doi.org/10.18280/ijht.370137 (2019).

Article Google Scholar

Sharma, N. & Varun, S. Stochastic techniques used for optimization in solar systems: A review. Renew. Sustain. Energy Rev. 16(3), 1399–1411. https://doi.org/10.1016/j.rser.2011.11.019 (2012).

Article Google Scholar

Çinici, O. K. et al. Optimization of melting time of solar thermal energy storage unit containing spring type heat transfer enhancer by Taguchi based grey relational analysis. J. Energy Storage 47, 103671 (2022).

Article Google Scholar

Seddik, Z. B. et al. Hybridization of Taguchi method and genetic algorithm to optimize a PVT in different Moroccan climatic zones. Energy 250, 123802 (2022).

Article Google Scholar

Gelis, K. et al. Multi-objective optimization of a photovoltaic thermal system with different water based nanofluids using Taguchi approach. Appl. Therm. Eng. 219, 119609 (2023).

Article CAS Google Scholar

Yan, G. et al. Proposing and optimization of a parabolic trough solar collector integrated with a photovoltaic module layer. Appl. Therm. Eng. 223, 119999 (2023).

Article Google Scholar

Singh, V. et al. Comparison of different designs of solar air heater with the simple solar heater of having reflecting mirrors. Proc. Inst. Mech. Eng. C J. Mech. Eng. Sci. https://doi.org/10.1177/09544062231158530 (2023).

Article Google Scholar

Prabowo, A. D. Geometry optimization of PV/T-TEG collector under different operating conditions using CFD simulation and Taguchi method. Eng. J. 26, 1–11 (2022).

Article CAS Google Scholar

Omeroglu, G. et al. Taguchi approach for experimental efficiency analysis of ultimate-black coated flat plate solar collector. Heat Transf. Res. 53, 1–14 (2022).

Article Google Scholar

Lin, W., Ma, Z., Cooper, P., Sohel, M. I. & Yang, L. Thermal performance investigation and optimization of buildings with integrated phase change materials and solar photovoltaic thermal collectors. Energy Build. https://doi.org/10.1016/j.enbuild.2016.01.041 (2016).

Article Google Scholar

Kuo, C.-F.J. et al. Using the Taguchi method and grey relational analysis to optimize the flat-plate collector process with multiple quality characteristics in solar energy collector manufacturing. Energy 36, 3554–3562 (2011).

Article Google Scholar

Fan, W. et al. A multi-objective design optimization strategy for hybrid photovoltaic thermal collector (PVT)-solar air heater (SAH) systems with fins. Solar Energy 163, 315–328 (2018).

Article ADS Google Scholar

Özakın, A. N. Experimental thermodynamic analysis of air-based PVT system using fins in different materials: Optimization of control parameters by Taguchi method and ANOVA. Solar Energy 197, 199–211 (2020).

Article ADS Google Scholar

Kuo, C.-F.J. et al. Optimization and practical verification of system configuration parameter design for a photovoltaic thermal system combined with a reflector. J. Intell. Manuf. https://doi.org/10.1007/s10845-015-1043-7 (2015).

Article Google Scholar

Yesildal, F. et al. Optimization of operational parameters for a photovoltaic panel cooled by spray cooling. Eng. Sci. Technol. https://doi.org/10.1016/j.jestch.2021.04.002 (2013).

Article Google Scholar

Kazemian, A., Parcheforosh, A., Salari, A. & Ma, T. Optimization of a novel photovoltaic thermal module in series with a solar collector using Taguchi based grey relational analysis. Solar Energy 215, 492–507 (2021).

Article ADS Google Scholar

Liu, X. Optimization of a new phase change material integrated photovoltaic/thermal panel with the active cooling technique using Taguchi method. Energies 12(6), 1022. https://doi.org/10.3390/en12061022 (2019).

Article CAS Google Scholar

Kolioak, Y., Radhakrishna, M. & Prasad, A. M. K. Optimization of heat energy based on phase change materials used in solar collector using Taguchi method. Mater. Today Proc. 22, 2404–2411. https://doi.org/10.1016/j.matpr.2020.03.365 (2020).

Article CAS Google Scholar

Chen, W.-L. et al. Employing Taguchi method to optimize the performance of a microscale combined heat and power system with stirling engine and thermophotovoltaic array. Energy 270, 126897 (2023).

Article CAS Google Scholar

Omeroglu, G. et al. Taguchi approach for experimental efficiency analysis of ultimate-black coated flat plate solar collector. Heat Transf. Res. 53, 1–14. https://doi.org/10.1615/Heattransres.2022041917 (2022).

Article Google Scholar

Antony, J. & Jiju Antony, F. Teaching the Taguchi method to industrial engineers. Work Study 50(4), 141–149. https://doi.org/10.1108/00438020110391873 (2001).

Article Google Scholar

Elsheikh, A. H., Sharshir, S. W., Kabeel, A. E. & Sathyamurthy, R. Application of Taguchi method to determine the optimal water depth and glass cooling rate in solar stills. Sci. Iran. 28(2), 731–742 (2021).

Google Scholar

Tsui, K.-L. An overview of Taguchi method and newly developed statistical methods for robust design. IIE Trans. 24(5), 44–57 (1992).

Article Google Scholar

Sachit, F. A. et al. Numerical investigation and performance analysis of photovoltaic thermal PV/T absorber designs: A comparative study. J. Adv. Res. Fluid Mech. Therm. Sci. 58, 62–77 (2019).

Google Scholar

Chatur, M. G., Maheshwari, A. & Campli, S. Investigation of waste cooking oil–diesel blend with copper oxide additives as fuel for diesel engine under variations in compression ratio. Int. J. Energy Environ. Eng. 14, 791–802. https://doi.org/10.1007/s40095-022-00549-7 (2023).

Article CAS Google Scholar

Pawar, S., Hole, J., Bankar, M., Channapattana, S. & Srinidhi, C. Studies on Xanthium strumarium L. seed oil: biodiesel synthesis and process optimization. Mater. Today Proc. 66, 2169–2177 (2022).

Article CAS Google Scholar

Chopade, S. C. et al. Lattice geometry controlled synthesis of Cu–doped nickel oxide nanoparticles. Ceram. Int. 44(5), 5621–5628 (2018).

Article CAS Google Scholar

Zaini, N. H. et al. The effect of temperature on a mono-crystalline solar PV panel. In 2015 IEEE Conference on Energy Conversion (CENCON) 249–253 (IEEE, 2015).

Amelia, A. R. et al. Investigation of the effect temperature on photovoltaic (PV) panel output performance. Int. J. Adv. Sci. Eng. Inf. Technol. 6(5), 682–688 (2016).

Article Google Scholar

Kazem, H. A. et al. Evaluation and comparison of different flow configurations PVT systems in Oman: A numerical and experimental investigation. Solar Energy 208, 58–88 (2020).

Article ADS Google Scholar

Mirzaei, N. Solar collector performance analysis using ANOVA method. Trans. Famena 45, 1–9 (2021).

Google Scholar

Kasuya, E. On the Use of r and r Squared in Correlation and Regression Vol. 34 (Wiley, 2019).

Google Scholar

Misha, S. et al. Simulation CFD and experimental investigation of PVT water system under natural Malaysian weather conditions. Energy Rep. 6, 28–44 (2020).

Article Google Scholar

Kazem, H. A. et al. Comparison and evaluation of solar photovoltaic thermal system with hybrid collector: An experimental study. Therm. Sci. Eng. Prog. 22, 100845 (2021).

Colombini, R., Molinaroli, L., Simonetti, R., Colombo, L. P. M. & Manzolini, G. Numerical analysis of different designs of roll-bond absorber on PV/T module and performance assessment. Appl. Therm. Eng. 192, 116873. https://doi.org/10.1016/j.applthermaleng.2021 (2021).

Article Google Scholar

Hassan, A. et al. An experimental and numerical study on the impact of various parameters in improving the heat transfer performance characteristics of a water based photovoltaic thermal system. Renew. Energy 202, 499–512 (2023).

Article Google Scholar

Azad, A. K. & Parvin, S. Photovoltaic thermal (PV/T) performance analysis for different flow regimes: A comparative numerical study. Int. J. Thermofluids 18, 100319. https://doi.org/10.1016/j.ijft.2023.100319 (2023).

Article Google Scholar

Alshibil, A. M. A., Farkas, I. & Víg, P. Thermodynamical analysis and evaluation of louver-fins based hybrid bi-fluid photovoltaic/thermal collector systems. Renew. Energy 206, 1120–1131. https://doi.org/10.1016/j.renene.2023.02.105 (2023).

Article Google Scholar

Le Khac, D. S. Efficient laboratory perovskite solar cell recycling with a one-step chemical treatment and recovery of ITO-coated glass substrates. Solar Energy 267, 112214. https://doi.org/10.1016/j.solener.2023.112214 (2024).

Article CAS Google Scholar

Chuang, T.-H. et al. Highly stable and enhanced performance of p–i–n perovskite solar cells via cuprous oxide hole-transport layers. Nanomaterials 13, 1363. https://doi.org/10.3390/nano13081363 (2023).

Article CAS PubMed PubMed Central Google Scholar

Narasimman, K., Gopalan, V., Bakthavatsalam, A. K., Elumalai, P. V., Iqbal Shajahan, M., & Joe Michael, J. (2023). Modelling and real time performance evaluation of a 5 MW grid-connected solar photovoltaic plant using different artificial neural networks. In Energy Conversion and Management (Vol. 279, p. 116767). Elsevier BV. https://doi.org/10.1016/j.enconman.2023.116767

Tripathi, A.K.; Aruna, M.; Venkatesan, E.P.; Abbas, M.; Afzal, A.; Shaik, S.; Linul, E. Quantitative Analysis of Solar Photovoltaic Panel Performance with Size-Varied Dust Pollutants Deposition Using Different Machine Learning Approaches. Molecules27, 7853. https://doi.org/10.3390/molecules27227853

Download references

The authors extend their appreciation to the Researchers Supporting Project number (RSPD2025R698), King Saud University, Riyadh, Saudi Arabia for funding this research work.

Suman Ramesh Tulsiani Technical Campus Kamshet, Pune, 410405, India

Jitendra Satpute

JSPM Rajarshi Shahu College Of Engineering, Pune, India

Srinidhi Campli & Raju Panchal

Department of Mechanical Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India

Dhinesh Balasubramanian

Department of Mechanical Engineering, Aditya University, Surampalem, India

P. V. Elumalai

Research Fellow, Faculty of Engineering, Shinawatra University, Toei, Thailand

P. V. Elumalai

Department of Mechanical Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai, Tamil Nadu, 602105, India

P. V. Elumalai

Department of Applied Mechanical Engineering, College of Applied Engineering, Muzahimiyah Branch, King Saud University, Riyadh, Saudi Arabia

Yasser Fouad

Centre of Research Impact and Outcome, Chitkara University, Rajpura, 140417, Punjab, India

Manzoore Elahi M. Soudagar

Division of Research and Development, Lovely Professional University, Phagwara, 144411, Punjab, India

Manzoore Elahi M. Soudagar

Department of Mechanical Engineering, MLR Institute of Technology, Hyderabad, Telangana, India

J. Laxmi Prasad

Department of Mechanical Engineering, Wolaita Sodo University, Soddo, Ethiopia

Mesay Dejene Altaye

College of Engineering, Lishui University, Lishui, Zhejiang, 323000, China

Manzoore Elahi M. Soudagar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

J.S, S.C &D.B: Conceptualization, E.P.V, Y.F, M.E.M.S Methodology & Formal analysis, Writing—original draft J.S, S.C.: Conceptualization, Methodology, Formal analysis, Writing—review & editing. R.P, L.P & M.D.A.:, Methodology, Writing—review & editing.

Correspondence to Jitendra Satpute, Dhinesh Balasubramanian or Mesay Dejene Altaye.

The authors declare no competing interests.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

Satpute, J., Campli, S., Balasubramanian, D. et al. Performance optimization for solar photovoltaic thermal system with spiral rectangular absorber using Taguchi method. Sci Rep 14, 23849 (2024). https://doi.org/10.1038/s41598-024-73065-9

Download citation

Received: 24 May 2024

Accepted: 13 September 2024

Published: 11 October 2024

DOI: https://doi.org/10.1038/s41598-024-73065-9

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

SHARE