Household Energy Dataset

  • Goddard N., Kilgour, J., Pullinger, M. et al (2021). IDEAL Household Energy Dataset. Edinburgh DataShare.
  • Pullinger, M., Kilgour, J., Goddard, N. et al (2021). The IDEAL household energy dataset, electricity, gas, contextual sensor data and survey data for 255 UK homesSci Data 8, 146.

Energy demand and smart meter policy and practice

  • Pullinger, M., Berliner, N., Goddard, N. & Shipworth, D. (2022). Domestic heating behaviour and room temperatures: Empirical evidence from Scottish homes. Energy and Buildings 254, 111509.
  • Lovell, H., Pullinger, M. & Webb, J. (2017). How do meters mediate? Energy meters, boundary objects and household transitions in Australia and the United Kingdom. Energy Research and Social Science 34: 252-259.
  • ​Pullinger, M., Lovell, H., & Webb, J. (2014). Influencing household energy practices: a critical review of UK smart metering standards and commercial feedback devices. Technology Analysis and Strategic Management, 26(10).
  • Goddard N., Moore J., Sutton C., Webb J. & Lovell H. (2012). Machine Learning and multimedia content generation for energy demand reduction. 2012 Sustainable Internet and ICT for Sustainability (SustainIT). Full text.
Other publications and presentations
  • Department for Energy Security and Net Zero, Pullinger, M. & Kilgour, J. (2023). Smart Energy Savings Competition (SENS): Energy Saver app: Trial-Level Evaluation Report.
  • Pullinger, M. & J. Kilgour (2023). Energy demand from Scottish homes: Evidence from smart meter data for policymakers and practitioners. Interim report from the Smart Energy Research Lab. Sustain Lab Research Brief. Full text on OSF:
  • Pullinger, M., Lovell, H. & Webb, J. (2018). Household energy meters: From humble measuring device to instrument of energy system transition? Sustain Lab Research Brief. Full text.
  • Pullinger, M. (2014). Smart meters and the household economy of energy: New frontiers for behaviour change policy and technology. International Society for Ecological Economics conference 2014: Wellbeing and equity within planetary boundaries. Rekjavik, Iceland.​​
  • Lovell, H., & Pullinger, M. (2013). New economies of residential energy demand reduction. RGS-IBG Annual Conference 2013. London, UK.

Feedback design and effects

Conference and workshop presentations
  • Yang, Z., Goddard, N., Webb, L. & Chenn, H. (2021). Electrical Appliance Usage Timeline Data Visualization: Machinima and Dynamic Circle. In e-Energy ’21: Proceedings of the Twelfth ACM International Conference on Future Energy Systems.  DOI: 10.1145/3447555.3466637
  • Pullinger, M., Webb, L., Morgan, E. & Webb, J. (2018). Impacts of digital feedback on the precursors of behaviour change: findings from a large experimental field study. BEHAVE 2018, 5th European Conference on Behaviour and Energy Efficiency, Zurich. 6 September 2018. Extended abstract.
  • Pullinger, M. (2018). Applying digital methods to understanding occupant behaviour and energy demand. TEDDINET closing workshop, London. 15 June 2018

Research methods

Conference presentations
  • Pullinger, M., Goddard, N., & Webb, J. (2016). An experimental research design for evaluating energy feedback. BEHAVE 2016, 4th European Conference on Behaviour and Energy Efficiency . Coimbra, Portugal.​​ Extended abstract

Machine Learning methods