Building-integrated photovoltaic (BIPV) systems in culturally significant buildings represent one of the key challenges in the transition to renewable energy, as highlighted in Oman Vision 2040. As the world moves towards decarbonization, the use of photovoltaic technologies in protected heritage sites must be approached with utmost care and respect to conservation principles, as stated in the Venice Charter (1964) and other ICOMOS guidelines, such as the criteria of authenticity and reversibility. This study aims to fill a gap and propose a multi-criteria assessment framework for BIPV integration in the culturally significant buildings. Taking the case study of Nizwa Fort in Oman, a sequential mixed-methods approach is used, including: (i) benchmarked energy demand estimation (200–300 kWh/day) with solar irradiance analysis (5.5–6.5 kWh/m²/day) and PV system sizing (50 kWp); (ii) a structured stakeholder survey (n = 42) across general public, architectural conservation specialists, and PV technology experts, with responses analyzed through weighted scoring (0.45/0.35/0.20) and Spearman rank correlation; (iii) scenario-based visual impact assessment of 40 BIPV configurations, derived from four PV technologies (monocrystalline, polycrystalline, PERC, thin-film) applied to ten spatial positions on primary and secondary building elements; and (iv) techno-economic analysis incorporating simple payback period (SPP: 12.8 years), net present value (NPV: OMR 18,400), levelized cost of electricity (LCOE: 0.019) Results show that the best ICOMOS conservation compliance scores and energy yields are achieved by rooftop installations that are concealed and by internal courtyard configurations. 62% of conservation professionals rejected primary façade-mounted installations on heritage elements as conservation-incompatible in all cases. The proposed integrated decision framework offers replicable, structured guidance for practitioners and policymakers for integrating renewable energy in a heritage-compatible way in the hot and arid climate. Monte Carlo uncertainty analysis (10,000 iterations) confirmed that Tier 1 rankings remain stable (>92% probability) under ±20% energy-demand and ±15-percentage-point weighing uncertainties, supporting the robustness of the framework.
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Mahdavinejad et al. (2026) studied this question.
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