Presentation Details
| Rooftop Solar Explorer: A Scalable Geospatial Framework for National Rooftop PV Potential Assessment Across India Using Morphological Settlement Zones and Building Footprint Analytics Pipasa Layak, Mahesh Kalshetty, Saptak Ghosh, Shantanu Roy. Center for Study of Science, Technology and Policy (CSTEP), Bengaluru, India |
Abstract
As of early 2026, India ranks third globally in solar power capacity. Yet, the widespread adoption of rooftop photovoltaic (PV) systems is hindered by the lack of high-resolution, building-level solar potential data across its morphologically diverse built environment. The Rooftop Solar Explorer (RTSE), developed by CSTEP, has completed 5-50cm resolution solar assessments, incorporating slope, aspect, shading, and techno-economic analysis for 120 Indian cities. However, this covers approximately 20% of India’s built-up area, leaving millions of buildings across semi-urban towns and rural settlements unaddressed. The present work addresses this gap using a novel and scalable methodology to extend RTSE’s rooftop PV potential assessment to the entire country using three complementary geospatial datasets: (1) the Morphological Settlement Zone (MSZ) framework by the European Commission’s Global Human Settlement (GHS) characteristics, which classifies India’s built environment into 10 settlement typologies across residential and non-residential buildings, (2) Microsoft Bing Maps' Global ML Building Footprints, and (3) CSTEP’s indigenous city-level datasets including rooftop area, generation potential following shading assessments, and Capacity Utilization Factors (CUF). The methodology spatially intersects MSZ classes with building footprints at the taluk level, derives MSZ-specific density ratios as calibration multipliers, and applies weighted-average rooftop suitability ratios validated against CSTEP's ground truth to estimate installable PV capacity nationwide. Location-specific CUFs are incorporated to account for India's diverse irradiance zones. An analogue city-pair matching mechanism extrapolates potential to uncovered geographies using MSZ distribution and latitude-corrected irradiance as matching criteria. The results have been implemented pan-India, including ~6,000 taluks throughout India. The insights provide actionable inputs for India’s flagship PM Surya Ghar Muft Bijli Yojana for driving consumer engagement and rooftop solar installations, thereby contributing to the scheme’s target of solarizing 10 million households by 2027 and meeting the national renewable energy target of 500 GW by 2030.
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No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, including photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the author.
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