Simulation-Based Total Energy Demand Estimation of Buildings using Semantic 3D City Models

Abstract

The present climate and environmental policy efforts require comprehensive planning regarding the modification of the energy supply and infrastructures in cities. The strategic planning of the different measures requires a holistic approach and the combination of extensive and complex information. Within this paper, current developments in the context of the project Energy Atlas Berlin are presented. The Energy Atlas Berlin is based on the semantic information model of CityGML and provides an integrative data backbone for the common spatio-semantic representation of the city structure including energy related information of different themes. The virtual 3D city model of Berlin (mainly LOD2 building models) is used as data basis and has been enriched by information of different stakeholders and disciplines. In order to ensure the energy supply, the knowledge about the energy demands of buildings during the planning and optimization of measures is of great strategic importance. Therefore, this paper focuses on the city-wide estimation of the energy demands of buildings including heating, electricity and warm water energy in the city of Berlin using available official geobase and statistical data integrated within the Energy Atlas Berlin. It is explained in detail how the spatial and semantic properties of the 3D building models are being used to estimate these energy demands on an individual building level for the entire city.

Applications of 3D City Models: State of the Art Review

“…Recent years have seen the advent of this application, where researchers, predominantly in Germany, have used 3D city models to combine the data of the volume of buildings, number of floors, type of the building, and other characteristics to predict the energy demand for heating and/or cooling [73,[123][124][125][126][127][128][129][130][131][132][133][134]. For instance, estimating the energy demand is important to assess the benefit of energy-efficient retrofitting.…”

“…For instance, the computation of the volume of a building is a spatial operation that is, among other operations, used in at least two use cases: estimating the energy demand (larger buildings require more energy to be heated) [73], and estimating the number of inhabitants of a building (larger buildings generally host more people) [74]. The latter use case is valuable in at least two application domains: for emergency response (estimating the number of people that have to be evacuated), and in environmental modelling (estimating the number of people affected by noise).…”

An improved LOD specification for 3D building models

“…Usability-wise, they can be used in a wider range of applications than LOD1, such as the estimation of the solar potential of rooftops (Fath et al, 2015;Biljecki et al, 2015a)), or as an improvement in accuracy over LOD1 (e.g. in energy demand estimation (Kaden and Kolbe, 2014)). (2013), respectively).…”

“…An example of such use case is the computation of the net internal area of a building, useful for energy estimations, real estate valuation, and population counts (Kaden and Kolbe, 2014;Nouvel et al, 2015;Boeters et al, 2015;Lwin and Murayama, 2009). Hence it does not strictly hold that LOD(i + 1) > LOD i, i.e.…”

Modeling Turkey National 2D Geo-Data Model as a CityGML Application Domain Extension in UML

“…In recent years considerable progresses have been realized in modelling 3D geo-data as CityGML ADE for different domains such as noise mapping (Czerwinski et al 2007;Wilson 2011;OGC 2012), utility networks (Becker et al 2011;Becker et al 2013); immovable property taxation (Çaǧdaş 2012); time dependent variables ; inclusive routing (Prandi et al 2013;Kaya and Gazioğlu, 2015); energy potential assessment (Wate and Saran 2015;Bahu and Nouvel 2015;Krüger and Kolbe 2012;Kaden and Kolbe 2014;Nouvel et al 2015), ubiquitous network robots services (OGC 2012), planning and management (Büyüksalih et al, 2017) etc. Most of the above mentioned studies were carried out based on only CityGML specifications that are existing national geodata models were not taken into account.…”