Volume 13, Issue 8 (August 2026), Pages: 83-107

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 Original Research Paper

Techno-economic and CO₂ impacts of AI-enabled transparent BIPV façades in Saudi smart-city sites: Multi-site simulation

 Author(s): 

Abdalrahman Alhndawi ^1, *, Muhamad Ali Bin Muhammad Yuzir ¹, Haneen Nsair ²

 Affiliation(s):

¹Department of Environmental Engineering, Faculty of Civil Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru, Johor, Malaysia
²Department of Architecture and Urban Planning, College of Engineering, Qatar University, Doha, Qatar

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 * Corresponding Author. 

   Corresponding author's ORCID profile:  https://orcid.org/0009-0003-4562-7763

 Digital Object Identifier (DOI)

 
https://doi.org/10.21833/ijaas.2026.08.009

 Abstract

This study evaluates the techno-economic performance and CO₂ benefits of transparent building-integrated photovoltaics (BIPV) façades with AI-enabled operation across four Saudi smart-city sites (NEOM, Riyadh, Red Sea, and AlUla). The objective is to quantify how an AI decision-support layer affects electricity generation, levelized cost of electricity (LCOE), discounted payback, return on investment (ROI), and CO₂ outcomes. A multi-site, per-m² façade simulation is conducted at hourly resolution and aggregated into monthly and annual indicators. Three cases are compared: conventional PV (S1), transparent PV without AI (S2), and AI-enabled transparent PV (S3); a maintenance-constrained case (S3b) is also assessed. AI is represented as condition-based loss recovery through reduced soiling-related losses and improved cleaning responsiveness, without altering PV device physics. Results show that S3 improves transparent-façade yield relative to S2 by ≈8.75–9.22%, reducing LCOE by ≈7.4–7.9%, shortening payback by ≈1.2–1.3 years, and increasing ROI by ≈0.8–0.9 percentage points. Avoided operational CO₂ increases proportionally with delivered electricity. Economic realism and probabilistic uncertainty analyses indicate that feasibility depends on tariff and financing conditions, AI/controls cost, and maintenance practicality. Overall, conventional PV should be prioritized for bulk generation, while AI-enabled transparent façades are suitable as a complementary resource where architectural and planning constraints justify façade integration.

 © 2026 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

AI-enabled operation, Building-integrated photovoltaic, Net CO₂, Saudi smart cities, Transparent photovoltaics

 Article history

Received 17 February 2026, Received in revised form 26 July 2026, Accepted 14 August 2026

 Acknowledgment

The authors gratefully acknowledge the support of the Faculty of Civil Engineering, Department of Environmental Engineering, Universiti Teknologi Malaysia (UTM), in facilitating this research. The authors also acknowledge Qatar University for institutional support. Any opinions, findings, and conclusions expressed in this paper were those of the authors and did not necessarily reflect the views of the supporting institutions. 

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 Citation:

Alhndawi A, Yuzir MABM, and Nsair H (2026). Techno-economic and CO₂ impacts of AI-enabled transparent BIPV façades in Saudi smart-city sites: Multi-site simulation. International Journal of Advanced and Applied Sciences, 13(8): 83-107

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