{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T08:15:24Z","timestamp":1772612124033,"version":"3.50.1"},"reference-count":30,"publisher":"IGI Global","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,7,1]]},"abstract":"<p>Today's needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns (e.g. buildings) corresponding to their specific context. In addition, future energy systems are expected to integrate a considerable share of fluctuating power sources and equally a high share of distributed generation of electricity. Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments thus require a spatial representation in order to reflect the local context and the boundary conditions. This paper describes two recent research approaches developed at EIFER in the fields of (a) geo-localised simulation of heat energy demand in cities based on 3D morphological data and (b) spatially explicit Agent-Based Models (ABM) for the simulation of smart grids. 3D city models were used to assess solar potential and heat energy demand of residential buildings which enable cities to target the building refurbishment potentials. Distributed energy systems require innovative modelling techniques where individual components are represented and can interact. With this approach, several smart grid demonstrators were simulated, where heterogeneous models are spatially represented. Coupling 3D geodata with energy system ABMs holds different advantages for both approaches. On one hand, energy system models can be enhanced with high resolution data from 3D city models and their semantic relations. Furthermore, they allow for spatial analysis and visualisation of the results, with emphasis on spatially and structurally correlations among the different layers (e.g. infrastructure, buildings, administrative zones) to provide an integrated approach. On the other hand, 3D models can benefit from more detailed system description of energy infrastructure, representing dynamic phenomena and high resolution models for energy use at component level. The proposed modelling strategies conceptually and practically integrate urban spatial and energy planning approaches. The combined modelling approach that will be developed based on the described sectorial models holds the potential to represent hybrid energy systems coupling distributed generation of electricity with thermal conversion systems.<\/p>","DOI":"10.4018\/ij3dim.2014070101","type":"journal-article","created":{"date-parts":[[2015,1,30]],"date-time":"2015-01-30T19:57:41Z","timestamp":1422647861000},"page":"1-16","source":"Crossref","is-referenced-by-count":17,"title":["Towards a 3D Spatial Urban Energy Modelling Approach"],"prefix":"10.4018","volume":"3","author":[{"given":"Jean-Marie","family":"Bahu","sequence":"first","affiliation":[{"name":"European Institute for Energy Research (EIFER), Karlsruhe, Germany"}]},{"given":"Andreas","family":"Koch","sequence":"additional","affiliation":[{"name":"European Institute for Energy Research (EIFER), Karlsruhe, Germany"}]},{"given":"Enrique","family":"Kremers","sequence":"additional","affiliation":[{"name":"European Institute for Energy Research (EIFER), Karlsruhe, Germany"}]},{"given":"Syed Monjur","family":"Murshed","sequence":"additional","affiliation":[{"name":"European Institute for Energy Research (EIFER), Karlsruhe, Germany"}]}],"member":"2432","reference":[{"key":"ij3dim.2014070101-0","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-01639-4_32"},{"key":"ij3dim.2014070101-1","first-page":"48","year":"2007","journal-title":"Consommations d'\u00e9nergie et \u00e9mission de gaz \u00e0 effet de serre li\u00e9es au chauffage des r\u00e9sidences principales parisiennes"},{"key":"ij3dim.2014070101-2","unstructured":"Bahu, J.-M. (2013, 19.06.2012). Applied Energy Geo-Simulation for Cities from 3D Urban Data. Paper presented at the Chancen der Energiewende: wissenschaftliche Beitr\u00e4ge des KIT zur 1. Jahrestagung des KIT-Zentrums Energie, Karlsruhe."},{"key":"ij3dim.2014070101-3","doi-asserted-by":"publisher","DOI":"10.4324\/9780203223017"},{"key":"ij3dim.2014070101-4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-29793-9_11"},{"key":"ij3dim.2014070101-5","unstructured":"Carri\u00f3n, D., Lorenz, A., & Kolbe, T. H. (2010). Estimation of the energetic rehabilitation state of buildings for the city of Berlin using a 3D city model represented in CityGML. Paper presented at the ISPRS Conference: International Conference on 3D Geoinformation. XXXVIII-4."},{"key":"ij3dim.2014070101-6","doi-asserted-by":"publisher","DOI":"10.1007\/978-90-481-8927-4_12"},{"key":"ij3dim.2014070101-7","unstructured":"Crooks, A. T., Hudson-Smith, A., & Patel, A. (2010). 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