Merge pull request #250 from RWTH-EBC/issue249_citation

Add citations for pyCity #249

Author: JSchiefelbein

README.md

@@ -267,6 +267,22 @@ Jupyter notebook should open within your browser (such as Firefox). Click on one
 If your Pyhton path does not point at your Python installation, you have to
 open jupyter notebook directly, e.g. by looking for the jupyter.exe in your distribution.
 
+## How to cite pyCity_base
+
++ Schiefelbein, J., Rudnick, J., Scholl, A., Remmen, P., Fuchs, M., Müller, D. (2019),
+Automated urban energy system modeling and thermal building simulation based on OpenStreetMap data sets,
+Building and Environment,
+Volume 149,
+Pages 630-639,
+ISSN 0360-1323
+[pdf](https://doi.org/10.1016/j.buildenv.2018.12.025),
+[bibtex](https://github.com/RWTH-EBC/pyCity/tree/master/doc/S0360132318307686.bib)
+
+If you require a citation in German language:
++ Schiefelbein, J. , Javadi, A. , Fuchs, M. , Müller, D. , Monti, A. and Diekerhof, M. (2017), Modellierung und Optimierung von Mischgebieten. Bauphysik, 39: 23-32. doi:10.1002/bapi.201710001
+[pdf](https://doi.org/10.1002/bapi.201710001),
+[bibtex](https://github.com/RWTH-EBC/pyCity/tree/master/doc/pericles_1437098039.bib)
+
 ## License
 
 pyCity is released by RWTH Aachen University's E.ON Energy Research Center (E.ON ERC),

doc/S0360132318307686.bib

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+@article{SCHIEFELBEIN2019630,
+title = "Automated urban energy system modeling and thermal building simulation based on OpenStreetMap data sets",
+journal = "Building and Environment",
+volume = "149",
+pages = "630 - 639",
+year = "2019",
+issn = "0360-1323",
+doi = "https://doi.org/10.1016/j.buildenv.2018.12.025",
+url = "http://www.sciencedirect.com/science/article/pii/S0360132318307686",
+author = "Jan Schiefelbein and Jana Rudnick and Anna Scholl and Peter Remmen and Marcus Fuchs and Dirk Müller",
+keywords = "City district, Urban energy models, Geographic information systems, Data enrichment, Archetypes, Workflow automation",
+abstract = "City districts have a large potential to reduce greenhouse gas emissions by usage of energy efficiency measures. Urban energy models (UEM) can be useful to analyze the impact of different energy efficiency actions on city districts. While simulation of demand data with high spatial and temporal resolution is often necessary to evaluate retrofit measures, the city's complex structure and lack of data often prevents a reliable application of such methods. This paper presents an urban energy modeling approach based on open-source geographical information system (GIS) datasets to reduce input data uncertainty and simplify city district modeling. We present a method to automatically extract basic city district data from OpenStreetMap (OSM) and enrich these datasets based on national building stock statistics. Building models with representative geometries and physical properties are automatically generated based on building archetype information. These models enable thermal simulation on urban scale. The approach is demonstrated for a use case in Germany, where a reference city district model has been generated with OSM data extraction and enrichment. The reference city district model has been used to perform a space heating net energy demand uncertainty analysis. The demand values simulated with the reference model show a sufficient fit with measured consumption values. The approach provides a fast and structured methodology to model city districts and simulate space heating energy demand on urban scale."
+}

doc/pericles_1437098039.bib

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+@article{doi:10.1002/bapi.201710001,
+author = {Schiefelbein, Jan and Javadi, Amir and Fuchs, Marcus and Müller, Dirk and Monti, Antonello and Diekerhof, Michael},
+title = {Modellierung und Optimierung von Mischgebieten},
+journal = {Bauphysik},
+volume = {39},
+number = {1},
+pages = {23-32},
+keywords = {Stadtquartier, Energieanlagenplanung, Wohngebäude, Nichtwohngebäude, Produktionsstätte, Referenzwohnquartier, Energiesysteme, Modelica, City district, Energy supply, Residential buildings, Non-residential buildings, Production facilities, Stadtbauphysik, Urban building physics},
+doi = {10.1002/bapi.201710001},
+url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/bapi.201710001},
+eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/bapi.201710001},
+abstract = {Abstract Dieser Artikel befasst sich mit der Erstellung eines Planungshilfsmittels für Mischquartiere im Kontext des Projekts „EnEff:Stadt – Bottrop, Welheimer Mark”. Bei der Welheimer Mark handelt es sich um ein Mischgebiet innerhalb der InnovationCity Ruhr in Bottrop. Ziel war die energetische Optimierung des Quartiers zur Reduktion von Treibhausgasemissionen. Hierfür wurden Methoden zur Modellierung von komplexen Quartieren entwickelt und auf die Welheimer Mark angewandt. Simulierte thermische und elektrische Bedarfswerte einer Wohnsiedlung wichen um 6,4 \% von den Verbrauchswerten ab. Während für die elektrische Profilgenerierung von Nichtwohngebäuden kein hinreichendes, vereinfachtes Verfahren identifiziert wurde, wies die Methodik zur Erzeugung thermischer Lastprofile eine gute Übereinstimmung zwischen generierten und gemessenen Profilen auf. Aus einer Optimierung gingen Vorschläge für eine verbesserte Energieanlagenverteilung hervor. Bei moderaten Kostensteigerungen von 6 \% bis 11 \% wäre eine Reduktion von CO2-Emissionen um bis zu 50 \% in bestimmten Bereichen der Welheimer Mark möglich.},,
+year = {2017}
+}
+