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

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

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Presentation on the Spatio-Temporal Energy Efficiency Visualisation (STEEV) tool (http://steevsrv.edina.ac.uk/) given by Stuart Macdonald, EDINA, at the JISC GECO/STEEV Green Energy Tech Event ...

Presentation on the Spatio-Temporal Energy Efficiency Visualisation (STEEV) tool (http://steevsrv.edina.ac.uk/) given by Stuart Macdonald, EDINA, at the JISC GECO/STEEV Green Energy Tech Event (#e3vis) on Thursday 13th October 2011.

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  • EDINA is one of the two JISC-funded National Data Centres in the UK based at the University of Edinburgh in Scotland JISC is funded by all of the UK higher education funding councils and provides leadership in the use of ICT in support of learning, teaching, research and administration in UK tertiary education. JISC funding, commercial and public partnerships Middleware, proof of concept, service component or enhancement
  • An 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 uses built form and age to group properties into 100 different types. Each type has an associated 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 into properties.
  • Hi – can you hear me OK? I’m going to talk to you this morning about the engaging researchers in the research data curation process
  • Request and fetch maps with a temporal element PostGIS is an open source software program that adds support for geographic objects to the PostgreSQL object-relational database
  • Geoinformation group’s Building Class dataset – UK coverage for urban centres over 10,000 – contains structural type, age, build fabric, size etc

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

  • 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!!