Concept and Evaluation of Heating Demand Prediction Based on 3D City Models and the CityGML Energy ADE—Case Study Helsinki

Abstract

This work presents a concept for heating demand and resulting CO2 emissions prediction based on a 3D city model in CityGML format in various scenarios under the consideration of a changing climate. In the case study of Helsinki, the Helsinki Energy and Climate Atlas, that provides detailed information for individual buildings conducting the heating demand, is integrated into the 3D city model using the CityGML Energy Application Domain Extension (Energy ADE) to provide energy-relevant information based on a standardized data model stored in a CityGML database, called 3DCityDB. The simulation environment SimStadt is extended to retrieve the information stored within the Energy ADE schema, use it during simulations, and write simulation results back to the 3DCityDB. Due to climate change, a heating demand reduction of 4% per decade is predicted. By 2035, a reduction of 0.7 TWh is calculated in the normal and of 1.5 TWh in the advanced refurbishment scenario. Including the proposed improvements of the district heating network, heating CO2 emissions are predicted to be reduced by up to 82% by 2035 compared to 1990. The City of Helsinki’s assumed heating demand reduction through the modernization of 2.0 TWh/a by 2035 is not achieved with a 3% refurbishment rate. Furthermore, the reduction of CO2 emissions is mainly achieved through lower CO2 emission factors of the district heating network in Helsinki.