Spatio-Temporal Energy Efficiency Visualisation (STEEV) tool - Stuart Macdonald, EDINA (http://steevsrv.edina.ac.uk/)

Stuart Macdonald Spatio-Temporal Energy Efficiency Visualisation (STEEV) Project EDINA National Data Centre University of Edinburgh STEEV/GECO Green Energy Tech Workshop Edinburgh Centre for Climate Change 13 October 2011

JISC-funded EDINA National Data Centre - http://edina.ac.uk/
Networked access to a range of online data services for UK tertiary education
Services free at the point of use for use by staff and students in learning, teaching and research through institutional subscription
Focus is on service but also undertake R&D (projects  services)
Delivers c. 20 online services & about 10 major projects
Employs about 80 staff (Edinburgh & St Helens)

Researchers investigating policy options on possible future states of the built environment need a simple mechanism to visualise outcomes of different scenarios of urban energy reduction policy Background: There is a requirement by the UK government to reduce the country’s carbon emission by 80% by 2050. Most building stock which will exist in 2050 has already been built; thus to achieve this target massive alterations of the current buildings are required.

STEEV is a JISC-funded project (Feb. 2011 – Oct. 2011) Information Environment Programme: Geospatial strand Project Partner: Welsh School of Architecture, Cardiff University This project will build a stakeholder engagement tool visualising historic, current and future energy efficiency estimates for small area geographies. Modelled estimates of building energy use for the period 1990-2050 for area in South Wales generated by the Energy and Environmental Prediction model

For further information see: http://www.cardiff.ac.uk/archi/programmes/cost8/case/assessment/eep.html Energy and Environmental Prediction (EEP) Model A digital auditing tool for quantifying energy use and associated emissions for cities to help plan to reduce carbon dioxide and other emissions. The domestic sub-model assigns properties into 100 different types. Each type has a CO2 emission, SAP rating and yearly energy cost associated with it. Every property within the region is surveyed and classified as a 'type'. Predictions can be made of potential CO2 and energy savings that can be made by installing various energy efficiency measures.

Technologies
Open Layers - a JavaScript framework for displaying map data in
web browsers
Digimap OpenStream API provides access to an EDINA WMS
offering OS Open Data products (1:250000 Colour raster,
VectorMapDistrict raster, OS Streetview)
CC BY-NC-SA 2.0 image by Jason Verwey courtesy of Flickr – http://www.flickr.com/photos/94382772@N00/5210633416/ Modelled energy efficiency variables held in PostGIS ( software that supports geographic objects in PostgreSQL) JavaScript client application (HTML/CSS/JQuery)

Scenario 1 – Faint Hearted - business as usual Minor attempts to decarbonise the grid Scenario 2 – Low Carbon Reference - partial decarbonisation Large investment in energy efficiency and small scale renewables - some change in occupant behaviour. Scenario 3 – Super Ambitious - full decarbonisation Through renewables and nuclear, and huge investment in energy efficiency and small scale renewables. Large scale change in occupant behaviour Govt. Policy Scenario descriptions

The Grid The government plans to reduce this emission rate by decarbonising the grid. This slider represents the government policy range from business as usual to super ambitious decarbonisation. Renewables, This slider selects the number of solar panels installed on buildings, Energy Efficiency This slider represents energy use reduction in the home (via insulation, new boilers, double glazing) Occupant Behaviour The way people use their houses has an impact on energy use. This slider changes the indoor temperature of the house set by the occupant Variable descriptions

The government plans to reduce this emission rate by decarbonising the grid. This slider represents the government policy range from business as usual to super ambitious decarbonisation. Output model unit of analysis: SAP Value, Energy Use (KWh per annum), CO2 emissions (Kg per annum) Download raw ASCII data for all scenarios or KML for policy-based scenarios (forthcoming) The government invests in partial decarbonisation of the grid through reduced dependence on fossil fuels. Large investment in energy efficiency and small scale renewable, some change in occupant behaviour. The way people use their houses has an impact on energy use, this slider changes the indoor temperature of the house set by the occupant it varies from 21 degrees C to 17 degrees C representing a business as usual scenario to lower expectation and more clothes worn. Thematic map view of chosen scenario at Output Area level of analysis

Build freeze on 11/11/11 for launch at JISC GeoTools event 28/11/11 Future endeavours… Implement findings and recommendations from external Usability Report and from user feedback (to be received by 21/10/11) With project partner explore generation and visualisation of energy efficiency variables for other urban centres / nationwide Resolve identified bugs, tweaks, cosmetic changes to interface

Credits: CC BY-NC-SA 2.0 image by ecstaticist courtesy of Flickr - http://www.flickr.com/photos/ecstaticist/1337749333/ CC BY-NC-ND 2.0 image by libraryman courtesy of Flickr - http://www.flickr.com/photos/libraryman/111606778/ / CC BY-NC-SA 2.0 image by Jason Verwey courtesy of Flickr - http://www.flickr.com/photos/94382772@N00/5210633416/ CC BY 2.0 image by Malkav courtesy of Flickr – http://farm3.static.flickr.com/2370/2262952280_0b03c07db9_o.jpg CC BY 2.0 image by M. M. Alvarez, T. Shinbrot, F. J. Muzzio, Rutgers University, Center for Structured Organic Composites courtesy of Flickr – http://www.flickr.com/photos/11304375@N07/2326596014/ CC BY-ND 2.0 images by Philippe Put courtesy of Flickr – http://www.flickr.com/photos/34547181@N00/4203882645/sizes/z/in/photostream// CC BY-NC-SA 2.0 image by monkeyc.net courtesy of Flickr – http://www.flickr.com/photos/monkeyc/216415962/ CC image by Darwin Bell courtesy of Flickr – http://www.flickr.com/photos/darwinbell/300495624/ CC image by Ecstaticist courtesy of Flickr – http://www.flickr.com/photos/ecstaticist/321582062/ CC images by Elephantik courtesy of Flickr – http://www.flickr.com/photos/joemaguiredesign/2300745142/ CC image by Darwin Bell courtesy of Flickr – http://www.flickr.com/photos/darwinbell/300495624 / CC image by laszlo-photo courtesy of Flickr – http://www.flickr.com/photos/laszlo-photo/1899390628/
STEEV Demonstrator – URL: http://steevsrv.edina.ac.uk/
STEEV Blog: http:// steev.blogs.edina.ac.uk
Contact: stuart.macdonald@ed.ac.uk
THANK YOU!!

Spatio-Temporal Energy Efficiency Visualisation (STEEV) tool - Stuart Macdonald, EDINA (http://steevsrv.edina.ac.uk/)

by JISC GECO on Oct 14, 2011

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Spatio-Temporal Energy Efficiency Visualisation (STEEV) tool - Stuart Macdonald, EDINA (http://steevsrv.edina.ac.uk/) Presentation Transcript

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