Exergy analysis of a naturally ventilated Building Integrated Photovoltaic/Thermal (BIPV/T) system

Agathokleous, Rafaela A.; Kalogirou, Soteris A.; Karellas, Sotiriοs

doi:10.1016/j.renene.2017.06.085

Cited by 55 publications

(20 citation statements)

References 24 publications

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“…The contributions of methodology and features of this study are compared to other studies in the literature in Table , which highlights the investigated parameters, types of learning algorithms and evaluation criteria.…”

Section: Resultsmentioning

confidence: 99%

“…The results revealed that glazed BIPVT collectors performed better, where the highest annual average exergy efficiency was around 10.81%, while the unglazed BIPVT exergy efficiency was around 10.75%. Agathokleous et al performed the exergy assessment of a naturally ventilated BIPVT collector and found that the exergy efficiency of the system is in the range of 13% to 16%. Shahsavar and Khanmohammadi compared the annual useful exergy gain of two configurations: (a) the BIPVT‐TW system and (b) the BIPVT and TW systems.…”

Section: Introductionmentioning

confidence: 99%

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Machine learning predictive models for optimal design of building‐integrated photovoltaic‐thermal collectors

et al. 2020

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This research article aims to examine the feasibility of several machine learning techniques to forecast the exergetic performance of a building-integrated photovoltaic-thermal (BIPVT) collector. In this regard, it uses multiple linear regression, multilayer perceptron, radial basis function regressor, sequential minimal optimization improved support vector machine, lazy.IBK, random forest (RF), and random tree approaches. Moreover, it implements the performance evaluation criteria (PEC) to evaluate the system's performance from the perspective of exergy. The use of these approaches serves the identification process to realize the relationship between the input-output parameters of the BIPVT system. The novelty of this work is that it utilizes and compares multiple learning algorithms to predict the PEC of BIPVT through design parameters. Hence, the research considers the parameter (PEC) as the essential output of the BIPVT collector, while the input parameters are the length, width, and depth of the duct, located under the PV modules, as well as the air mass flow rate. The results of the research for the statistical indexes of mean absolute error, root mean square error, relative absolute error (%), and root relative squared error (%) show values of (0.2967, 0.3885, 1.8754, and 1.5237) and (0.4957, 0.8153, 2.9586, and 2.8289), respectively, for the training and testing datasets. While R 2 ranges (0.9997-0.9999) for those datasets. Therefore, to estimate the exergy performance of the BIPVT collector, the RF model is superior to other proposed models. K E Y W O R D SBIPVT, exergetic performance, machine learning, performance evaluation criteria, predictive model

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Machine learning predictive models for optimal design of building‐integrated photovoltaic‐thermal collectors

et al. 2020

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“…Building Integrated Photovoltaic (BIPV) systems have been increasingly used (Agathokleous et al, 2018;Curtius, 2018) as a means to generate electricity on-site, and their diffusion will increase in the near future, taking into account the EU regulation on nearly net zero energy buildings (nZEB), called Energy Performance Building Directive (EPBD) (EC, 2010). This concept considers a building that has a very high energy performance, that is to say, that energy must be covered basically from renewable sources produced on-site or nearby, usually requiring on-site electricity generation and sale to the electrical grid (Tripathy et al, 2017).…”

Section: 1bipv Systems and The Reelcoop Projectmentioning

confidence: 99%

Sustainability indicators of a naturally ventilated photovoltaic façade system

Garraín

Herrera

Rodríguez-Serrano

et al. 2020

Journal of Cleaner Production

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Building Integrated Photovoltaic (BIPV) systems have been increasingly used as a means to generate electricity on-site, and their diffusion will increase in the near future. The objective of this article is to carry out a sustainability assessment of a BIPV system installed in Turkey regarding the three pillars: environmental, economic and social potential impact, in order to develop different indicators. For the socioeconomic analysis, a Multiregional Input-Output (MRIO) method was used to estimate production of goods and services, value added creation and employment opportunities. For the environmental evaluation, an Environmental Footprint (EF) analysis was performed. The levelized electricity costs and the greenhouse gas emissions abatement costs were also calculated.Results showed that the socioeconomic effects are relevant, although only a 23% of these effects remain in Turkey. The environmental profile is also good in terms of climate change impacts, showing substantial reductions in greenhouse gas emissions compared to fossil fuel alternatives for electricity generation. Regarding the life cycle stages of the technology, the highest environmental impacts are produced in the PV manufacturing processes. The electricity produced is still more costly than fossil-based technologies and in the highest range of PV technologies, but greenhouse gases abatement costs are not so high when compared to other references.

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“…BIPVT is a building-integrated photovoltaic-thermal system, which is used for the simultaneous conversion of the energy of radiant solar energy into electricity and thermal energy [42,43]. The system contains a PV panel for the conversion of solar energy into electricity due to the photovoltaic effect and into thermal energy through the absorption process [44]. The BIPV system applied as thermal insulation to the building envelope in hot and humid climates showed the significance of insulation on the energy use in residential and commercial buildings [31].…”

Section: Overview Of the Pv Systemsmentioning

confidence: 99%

Semitransparent Building-Integrated Photovoltaic: Review on Energy Performance, Challenges, and Future Potential

Joseph

Pogrebnaya

Kichonge

2019

International Journal of Photoenergy

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Buildings consume large amounts of energy, and their transformation from energy users to producers has attracted increasing interest in the quest to help optimize the energy share, increasing energy efficiency and environmental protection. The use of energy-efficient materials is among the proposed approaches to increase the building’s energy balance, thus increasing the performance of building facades. Semitransparent building-integrated photovoltaic (BIPV), being one of the technologies with the potential to increase a building’s energy efficiency, is considered as a feasible method for renewable power generation to help buildings meet their own load, thus serving dual purposes. Semitransparent BIPV integration into buildings not only displaces conventional building facade materials but also simultaneously generates energy while retaining traditional functional roles. The awareness in improving building energy efficiency has increased as well as the awareness in promoting the use of clean or renewable energy technologies. In this study, semitransparent BIPV technology is reviewed in terms of energy generation, challenges, and ways to address limitations which can be used as a reference for the BIPV stakeholders.

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Exergy analysis of a naturally ventilated Building Integrated Photovoltaic/Thermal (BIPV/T) system

Cited by 55 publications

References 24 publications

Machine learning predictive models for optimal design of building‐integrated photovoltaic‐thermal collectors

Machine learning predictive models for optimal design of building‐integrated photovoltaic‐thermal collectors

Sustainability indicators of a naturally ventilated photovoltaic façade system

Semitransparent Building-Integrated Photovoltaic: Review on Energy Performance, Challenges, and Future Potential

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