Towards Sustainable Urban Rooftop Solar Energy Planning Through Spatial Digital Twins Paradigm: A Systematic Literature Review

With the growing need for sustainable urban energy solutions, rooftop solar photovoltaic (PV) systems can play a pivotal role. However, the effective integration of solar energy into urban landscapes faces challenges in spatial planning, resource optimisation, and stakeholder engagement. This literature review addresses the existing gaps by systematically evaluating Geographic Information System (GIS)-based methodologies for PV potential assessment and rooftop solar energy planning. It aims to provide the knowledge necessary for supporting efficient and sustainable solar energy adoption in cities. This chapter involved a systematic review and synthesised the diverse body of knowledge regarding city-scale rooftop solar energy planning. The goal was to identify the technical challenges, highlight the trends, and reveal opportunities for future research initiatives with respect to the evolving needs of sustainable energy planning. Employing a dual-method systematic approach, this review utilised both quantitative and qualitative analysis techniques. Through the quantitative survey, a generic corpus (805 studies) of Scientometrics using CiteSpace was built, ensuring a broad representation of the existing literature. In parallel, a qualitative survey, evaluating literature associated with solar rooftop PV assessment using GIS, modelling techniques, planning implications, and recommendations, led to a critical corpus (76 studies) using the Preferred Reporting Items for Systematic Reviews (PRISMA) method. Spanning the past two decades and drawing from databases of Scopus and Web of Science (WoS), the synthesised corpora formed the foundation for a comprehensive and informed evaluation. Additionally, analytical assessment criteria were developed to provide insights into future research agendas and framework. The literature synthesis unveiled the challenges within urban energy planning, covering issues of data accuracy, model validation, and imperative stakeholder engagement. Emerging trends in GIS models, especially the integration of machine learning and three-dimensional (3D) mapping, emphasise the dynamic nature of the urban environment. Furthermore, applications of GIS in real-world urban contexts provide spatially explicit insights for future implementations. Finally, this literature review proposed a research agenda for advancing GIS-based rooftop solar energy planning, with a particular focus on developing a spatial digital twin environment incorporating three-dimensional (3D) models, real-time data integration, and decision support systems tailored for city-scale applications. Spatial digital twin technologies enable modelling of different energy production scenarios. Such an integrated approach will underpin effective strategies to accommodate the complexities within urban environments, thus providing a roadmap for researchers, urban planners, and policymakers to collaboratively develop sustainable solutions for rooftop solar energy adoption at a city scale.