A Spatial Microsimulation Model for the Estimation of Heat Demand in Hamburg

Muñoz H., M. Esteban (2016) A Spatial Microsimulation Model for the Estimation of Heat Demand in Hamburg. REAL CORP 2016 – SMART ME UP! How to become and how to stay a Smart City, and does this improve quality of life? Proceedings of 21st International Conference on Urban Planning, Regional Development and Information Society. pp. 39-46.

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Abstract

Most spatial bottom up domestic heat models are based on an existing building stock data set, this can be the official digital cadastre (ALKIS in Germany), community based data sources (e.g: open-street) or collected data stored on a GIS system. On this paper we present an innovative method for the creation of spatial bottom up domestic heat models that do not need an existing building stock data-set as input. The advantage of this type of models are its transferability, speed and flexibility. The presented model uses national standardized statistical data, making it possible to apply it for any region in the country without having to modify the model. Because the input data for the model is more compact the speed of the model increases significantly, the type of analysis possible with a high speed model allow us to perform a microsimulation of the building stock for the entire country, see (Muñoz H., Seller, & Peters, 2015). The presented model structure allows us to quickly develop dynamic simulation scenarios. We present a spatial microsimulation model developed for the simulation of domestic heat demand. The presented model use the GREGWT R package to create a synthetic building stock benchmarked to aggregated small area statistics from the 2011 German census. We create this synthetic building stock from the 2010 microsensus. The heat estimation if performed on the microcensus with help of the heat R package. The simulation results present a monthly heat demand at a microlevel for the entire city of Hamburg. The generated data for the estimation of heat demand can be use as input data for other Agent Based Models. By enriching the microcensus with time use data, we are able to generate the basis data for the construction of activity based urban models. We see the development of this type of urban models as an essential development of urban planning, specially for a smart urban development. The generation of microdata is a fundamental part of the smart city development.

Item Type: Article
Uncontrolled Keywords: Spatial Microsimulation, Synthetic City, GREGWT, Urban Heat Demand, Hamburg
Subjects: G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography
H Social Sciences > HD Industries. Land use. Labor
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Depositing User: REAL CORP Administrator
Date Deposited: 22 Jul 2016 09:01
Last Modified: 22 Jul 2016 09:01
URI: http://repository.corp.at/id/eprint/176

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