Urban energy use modeling methods and tools: A review and an outlook. (15th August 2019)

• Record Type: Journal Article
• Authors: Abbasabadi, Narjes; Ashayeri, Mehdi
• Is Part Of: Building and environment. Volume 161(2019)
• Publication Date: 2019-08-15
• Subjects: Urban energy use modeling -- Operational energy -- Transport energy -- Embodied energy -- Data-driven -- Simulation; Buildings -- Environmental engineering -- Periodicals; Building -- Research -- Periodicals; Constructions -- Technique de l'environnement -- Périodiques; Electronic journals; 696
• DOI: 10.1016/j.buildenv.2019.106270
• Languages: English
• ISSNs: 0360-1323

Abstract

Abstract: Urban energy use modeling is important for understanding and managing energy performance in cities. However, the existing methods and tools have limitations in representing a realistic urban energy model and supporting energy performance evaluation at urban or neighborhood scales. In addition, there is a lack of an integrated approach for modeling and analyzing different components of urban energy use. The existing methods and tools for assessment of urban energy use often reduce the urban energy use definition to operational energy of buildings, ignoring other essential components such as transportation energy, and embodied energy of buildings and infrastructure. In addition, reliable and accurate urban energy prediction remains a challenge as methodological uncertainties that are embedded in the common methods are often not considered. This, in turn, affects the suitability of these approaches for decision-making purposes. The key limitation of data-driven methods stem from the use of aggregate data for energy use estimations and generalizing the status quo. In simulation-based methods, oversimplification of the urban context and failure to account for occupancy and human-related factors, and urban microclimate and inter-building effects are the major limitations. The present article provides a review of the current modeling methods, tools, and techniques in urban energy use modeling. It examines the strengths and limitations of each and presents an outlook for a future urban energy use modeling (UEUM) approach that could capture different components of urban energy use through a bottom-up hybrid data-driven and simulation-based techniques to build upon the strengths of the two methods while reducing the modeling uncertainties.