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Leveraging potential of large scale mixed-use green certified projects for adoption of Building Integrated Photovoltaics (BIPV) in the Global South

2025· article· en· W4413823416 on OpenAlexaff
Khushal Matai, Ashu Dehadani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutions123 Certification (Canada)
Fundersnot available
KeywordsBuilding-integrated photovoltaicsPhotovoltaicsCertificationScale (ratio)Photovoltaic systemEnvironmental scienceArchitectural engineeringEngineeringElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

The shift in urban electricity consumption from industry to high rise commercial buildings has created both a challenge and a significant opportunity for adoption of photovoltaics into building envelopes that can support this demand through decentralized renewable energy generation. Among others, the most promising solutions is Building Integrated Photovoltaics (BIPV). BIPV embed solar technologies directly into the fabric of buildings, particularly facades and glazing, turning passive surfaces into active energy generators. BIPV not only addresses the spatial limitations of traditional rooftop solar in high-density cities, but also enhances architectural value, thermal performance, and long-term energy resilience. Despite global advancements, the adoption of BIPV in the Global South remains limited due to fragmented policy support, lack of awareness, and minimal integration into large-scale urban planning efforts. However, the rise of mixed-use, green-certified developments and modular construction methods provides a unique and scalable opportunity to mainstream BIPV from the design stage onward. This paper explores the current global status of BIPV, highlights the untapped potential of BIPV adoption in the context of large-scale projects in the Global South, and examines the role of green building certification systems in enabling or hindering adoption. It also outlines the multifaceted challenges—technological, regulatory, and social; and identifies the need for a holistic framework for integrating BIPV within future-ready, high-performance buildings across rapidly urbanizing tropical regions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.449
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.261
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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