Energy metrics assessment of a photovoltaic thermal air collector (PVTAC): a comparison between flat and wavy collector

Jha, Prabhakar; Mondol, Jayanta Deb; Das, Biplab; Gupta, R.

doi:10.1080/15567036.2020.1809563

Cited by 19 publications

(10 citation statements)

References 41 publications

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“…They conducted outdoor tests using wavy and plain absorbers with variable photovoltaic coverage under climatic conditions in Northeast India. Another study by Jha et al [24] compared the performance of two different configurations of a PVT air collector for three energy arrays, including energy recovery time, electricity production factor, and conversion efficiency of the Lifecycle.…”

Section: Related Workmentioning

confidence: 99%

Influencing Factors Evaluation of Machine Learning-Based Energy Consumption Prediction

2021

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Modern computing resources, including machine learning-based techniques, are used to maintain stability between the demand and supply of electricity. Machine learning is widely used for the prediction of energy consumption. The researchers present several artificial intelligence and machine learning-based methods to improve the prediction accuracy of energy consumption. However, the discrepancy between actual energy consumption and predicted energy consumption is still challenging. Various factors, including changes in weather, holidays, and weekends, affect prediction accuracy. This article analyses the overall prediction using error curve learning and a hybrid model. Actual energy consumption data of Jeju island, South Korea, has been used for experimental purposes. We have used a hybrid ML model consisting of Catboost, Xgboost, and Multi-layer perceptron for the prediction. Then we analyze the factors that affect the week-ahead (WA) and 48 h prediction results. Mean error on weekdays is recorded as 2.78%, for weekends 2.79%, and for special days it is recorded as 4.28%. We took into consideration significant predicting errors and looked into the reasons behind those errors. Furthermore, we analyzed whether factors, such as a sudden change in temperature and typhoons, had an effect on energy consumption. Finally, the authors have considered the other factors, such as public holidays and weekends, to analyze the significant errors in the prediction. This study can be helpful for policymakers to make policies according to the error-causing factors.

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Section: Related Workmentioning

confidence: 99%

Influencing Factors Evaluation of Machine Learning-Based Energy Consumption Prediction

2021

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“…The embodied energy is the input energy required in production of raw materials to develop any system. It takes into account the total total consumption during the raw material to the final product and is calculated by the total energy density of each component times total mass of material used [42]. The distribution of embodied energy to fabricate the current developed system is mentioned in Table 7.…”

Section: Energy Payback Period Of the Developed Systemmentioning

confidence: 99%

“…The calculated embodied energy is used to calculate the energy payback time (EPBT). EPBT is the ratio of embodied energy (energy input) to the energy gained from the system (output energy) and it gives a measurement of the time required to pay back the expenses incurred in fabricating current system [42]. EPBT is found to be 7.4 years and 7.8 years incase of system without fin and system with fin, respectively.…”

Section: Energy Payback Period Of the Developed Systemmentioning

confidence: 99%

Performance of finned heat pipe assisted parabolic trough solar collector system under the climatic condition of North East India

Bhagwat

Roy

Das

et al. 2021

Sustainable Energy Technologies and Assessments

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“…The electrical performance of PVTAC is also measured. The solar cell or PV module electrical efficiency (ηsc) is calculated as [35]:…”

Section: Energy Modelingmentioning

confidence: 99%

“…The overall energy collected by the PVTAC (Qov) is the collection of thermal energy and conversion of electrical energy into thermal energy, which is calculated as [35]:…”

Section: Energy Modelingmentioning

confidence: 99%

An environmental and economic evaluation of solar photovoltaic thermal dryer

Gupta

Das

Biswas

et al. 2021

Int. J. Environ. Sci. Technol.

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The up-gradation of the conventional indirect mode forced convection solar dryer to Photovoltaic thermal (PVT) based solar dryer is advantageous in terms of energysaving ability, efficiency, self-sufficient design, and ability to work without any additional electrical energy requirement. However, there is a requirement for a comprehensive analysis of the energy, exergy, and environ-economic parameters for developing an efficient and sustainable PVT solar dryer. In this study, a PVT based indirect mode solar dryer has been fabricated and investigated in the environmental conditions of North-East India (Silchar latitude of 24.83°). Experiments were performed to compare the drying characteristics of tomatoes (solanum lycopersicum) under open sun and solar drying conditions. A new mathematical drying model was proposed to predict the drying characteristics of tomato under both the modes of drying. The average PVT dryer efficiency was found to be 34.98%, higher than some of the published works of indirect mode solar dryer conducted under similar experimental conditions. The calculated values of drying effectiveness, collector efficiency factor, coefficient of performance, and heat utilization factor were 1.12-1.58, 0.011-0.029, 0.71, and 0.29, respectively. Furthermore, CO 2 emission, CO 2 mitigation, carbon credit earned parameters were evaluated for 10, 20, and 30 years of system life.

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Energy metrics assessment of a photovoltaic thermal air collector (PVTAC): a comparison between flat and wavy collector

Cited by 19 publications

References 41 publications

Influencing Factors Evaluation of Machine Learning-Based Energy Consumption Prediction

Influencing Factors Evaluation of Machine Learning-Based Energy Consumption Prediction

Performance of finned heat pipe assisted parabolic trough solar collector system under the climatic condition of North East India

An environmental and economic evaluation of solar photovoltaic thermal dryer

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