Inferential‐ and measurement‐based methods to estimate rooftop “solar city” potential in megacity Seoul, South Korea

Job Taminiau, John Byrne, Jongkyu Kim, Min‐Hwi Kim and Jeongseok Seo

Wiley Interdisciplinary Reviews: Energy and Environment, 2022, vol. 11, issue 5

Abstract: Data analysis and collection techniques now allow for detailed inventory‐building of urban rooftops for the purposes of identifying solar energy potential within geographically defined boundaries, including those of cities. The complexity and inherent diversity of a city's building stock has propelled the introduction of many so‐called “solar city” assessment methods that, with varying levels of accuracy, scalability, and ease of use, seek to characterize the citywide solar photovoltaic (PV) resource potential. A review of the landscape of available methods supports a fundamental distinction across two classes of methods. First, “solar city” assessment methods can principally rely on inference to identify and characterize rooftop solar potential. Such inferential methods can establish estimates of citywide solar potential without needing direct insight into rooftop conditions or morphology, Second, measurement‐based methods estimate rooftop solar opportunities based on the direct measurement of rooftop conditions, often conducted through remote sensing. Comparative performance testing of several inferential‐ and measurement‐based methods using case study analysis underscores the importance of measurement‐based methods. In particular, measurement‐based methods are likely better positioned to support the needs of policy‐makers and investors interested in transforming a city or metropolitan area into a sustainable city whose buildings serve as the host of a new solar PV‐powered distributed electricity service system. This article is categorized under: Sustainable Energy > Solar Energy Energy and Power Systems > Energy Infrastructure Cities and Transportation > Smart Cities

Date: 2022
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