Occupancy based thermal energy modelling in the urban residential sector

This is a paper and all scripts creating the results of the paper that resulted from the Knowledge Transfer Partnership between the Energy Efficient Cities initiative (EECi) of University of Cambridge and Improbable Ltd.

Getting ready

Installation

The following dependencies are needed to set up an environment in which the analysis can be run and the paper be build:

• conda
• Git
• Java 1.8
• make (optional; without make, e.g. on Windows, you will need to manually run all steps)

When all these dependencies are installed, you can create a conda environment from within you can run the analysis:

conda env create -f conda-environment.yml

Data preparation

All open data is retrieved automatically from the web when running the analysis the first time. All closed or safeguarded data must be provided by the user. These datasets are:

• UK Time Use Survey 2001: safeguarded dataset to be placed in ./data/UKDA-4504-tab/.
• MIDAS: safeguarded dataset to be called ./data/Londhour.csv.

Note: the open census data is retrieved from nomis. There is a download limit for anonymous downloads, which is said to be limited to 25.000. You should not hit this limit when running this analysis.

Run the analysis

make paper

This will run all analysis steps to reproduce results and eventually build the paper. Depending on the machine this might take a few hours.

You can also run certain parts only by using other make rules; to get a list of all rules see the Makefile.

If you do not have make you can manually run the steps through the Python command line interfaces. Refer to the Makefile to see which commands are called to produce results.

Run the tests

make test

Repo structure

• doc: contains all files necessary to build the paper; plots and result files are not in here but generated automatically
• urbanoccupants: a small Python library and their tests, containing reusable code needed several times in this study
• scripts: Python scripts and its tests which run this analysis
• config: configurations for the simulation runs as performed in the study

Datasets

• UK Census 2011: Retrieved from nomis.

Office for National Statistics ; National Records of Scotland ; Northern Ireland Statistics and Research Agency (2016): 2011 Census aggregate data. UK Data Service (Edition: June 2016). DOI: http://dx.doi.org/10.5257/census/aggregate-2011-1

This information is licensed under the terms of the Open Government Licence [http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3].

• London Shape Files: Retrieved from London Datastore.

Contains National Statistics data © Crown copyright and database right 2012

Contains Ordnance Survey data © Crown copyright and database right 2012

Release under the terms of the UK Open Government Licence (OGL v2).

• UK Time Use Survey 2001: Safeguarded data set.

Ipsos-RSL, Office for National Statistics. (2003). United Kingdom Time Use Survey, 2000. [data collection]. 3rd Edition. UK Data Service. SN: 4504, http://doi.org/10.5255/UKDA-SN-4504-1

• MIDAS: Safeguarded data set.

Met Office (2006): MIDAS: UK Hourly Weather Observation Data. NCAS British Atmospheric Data Centre. http://catalogue.ceda.ac.uk/uuid/916ac4bbc46f7685ae9a5e10451bae7c