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Improving Visual Communication of Energy Forecast Uncertainty

Primary supervisor

Sarah Goodwin

Co-supervisors

  • Rob Hyndman
  • Dianne Cook

Communicating uncertainty in a manner that clearly and accurately conveys the data to enable decision making, is a well known and difficult challenge in the information visualisation community. This project therefore aims to improve the communication of uncertainty of forecast models by working in collaboration with data modellers and those who are interpreting them.

This project specifically focuses on the energy sector, as an important part of energy control centre operations is the ability to strategically plan for potential and developing changes. Forecast models are used for short-term, long-term and operational decision making. These models intrinsically incorporate both spatial and temporal data uncertainty, which needs to be understood for analysts and operators to make informed and sound decisions on a daily basis. In this research, various user-centred design approaches, including observational studies, interviews and user studies, will be used to ensure prototype designs are tailored to control room operations and specifically for decision making during times of critical stress. 

Project hashtags: #energy #zema #energyvis  #uncertainty #forecasting #geovis #multidisciplinary #datavis #DVIALab #phd

Required knowledge

  • Eligible for the PhD program and Zema Scholarship (see link below regarding funding)
  • Programming skills
  • Visualisation or UX design expertise
  • Experience in qualitative and quantitative research methods
  • Interest in visualising uncertainty, forecasting, and it's link to the energy sector

 

 

#sustainability, #energy

Project funding

Other

Learn more about minimum entry requirements.