Enhancing urban energy applications through semantic 3D city models and open data
The case of the Netherlands
C.A. León Sánchez (TU Delft - Urban Data Science)
J.E. Stoter – Promotor (TU Delft - Urbanism)
Giorgio Agugiaro – Copromotor (TU Delft - Urban Data Science)
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Abstract
The development of society has led to a dramatic change in urban areas. As of 2025, at least 56% of the world's population lives in cities, and it is projected to reach 70% by 2050. Despite occupying only 3% of the Earth's surface, urban areas account for 60% to 80% of global ''energy consumption''. This intensifies the need for accurate and reliable energy demand models to support carbon reduction and energy transition goals.
Urban Building Energy Modelling (UBEM) provides a structured framework for simulating building energy performance at multiple spatial scales. However, UBEM depends heavily on detailed and high-quality data, which is often fragmented or unavailable as open data. Semantic 3D city models (s3DCMs) are one promising data source. These models offer standardised geometric and semantic representations of urban elements in a three-dimensional environment. This thesis investigates the use of s3DCMs and open data to enhance urban energy applications, focusing on the Netherlands as a case study.
The first part of the thesis addresses the models and data requirements of UBEM, with an emphasis on the Dutch official method for calculating energy performance. It evaluates CityGML as a data model for energy-related applications and analyses the availability and suitability of open datasets in the Netherlands for UBEM use.
The second part focuses on the implementation of the corresponding datasets and simulation solutions to compute the energy performance of buildings. It describes the input data sources, their entities, and the relevant attributes, as well as the enrichment of the s3DCM by linking multiple datasets. A CityGML-based testbed for energy-related applications was published as part of this work, representing the municipality of Rijssen-Holten with Buildings, trees and a digital terrain model (DTM). The enriched s3DCM has been used to perform solar analysis.
Subsequently, the thesis outlines the design and implementation of a building energy simulation (BES) solution for computing the net heat demand of buildings. Due to data limitations at country level, the focus remains on net heat demand rather than full primary energy demand. Required parameters for primary energy calculation were unavailable without introducing additional assumptions.
The simulation results cover two case studies: the municipality of Rijssen-Holten and the national building stock of the Netherlands. Outputs are classified by building type and construction period and compared against available Energy Performance Certificate (EPC) data. Although the comparison must be interpreted with caution, it offers a contextual benchmark for the results.
This thesis highlights the value of open data and the procedures required to enhance existing s3DCM for energy-related use. It also proposes additional research directions, including the integration of solar energy simulation results with the created BES to implement hybrid approaches that better reflect the current characteristics of the Dutch building stock.
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