W8UP10 An investigation of feedback and feedforward energy efficiency mechanisms from a UK school crowdsourced building stock model

W8UP10 An investigation of feedback and feedforward energy efficiency mechanisms from a UK school crowdsourced building stock model
26th July 2018 Duncan Grassie

Duncan Grassie, UCL Energy Institute


Background

To assist with tracking progress towards the UKs 2050 emissions commitments, the development of automated methods combined with national datasets in fabric and geometry have facilitated the construction of 16,000 UK school EnergyPlus building simulation models. While these models combine the top-down benchmarking of schools relative to peers with bottom-up sources for under or overperformance based on building physics, a key issue identified in previous work (see preceding MRes project) was that occupant datasets of schedules and setpoints of the building services (heating, lighting, IT, catering, etc.) are also necessary to differentiate between poorly built and poorly operated school buildings.

Previous efforts to determine operational performance of buildings has involved engaging design engineers but school building users themselves are custodians of the actual operation of the building. Monitoring and post occupancy evaluation can be carried out with budget and personnel constraints limiting the scale, but large scale modelling projects will require engagement of this key group  by overcoming knowledge or motivational gaps.

Research objectives

A crowdsourcing platform will be developed as part of this research project to test whether it is possible to recruit school building users and managers to provide occupant datasets which improve model accuracy in return for providing insights on the performance of their building. Key research questions to be answered are:

For the school building stock in England and Wales, can a platform be developed to evaluate school energy performance and associated CO2 emission that:

  • – Feeds forward to track progress towards national CO2 reduction targets
  • – Feeds back to individual schools to support performance improvement
  • and can the necessary data be obtained for each purpose?

A series of workshops will determine a preliminary design of feedback and feedforward mechanisms for each set of stakeholders. In years 2 and 3, this Crowdsourcing platform will be introduced to school building users and tested to investigate if model efficacy improves as the participants enter more information.

Project Team

Student(s)
Duncan Grassie

Supervisor(s)
Dr. Ivan Korolija

Prof. Dejan Mumovic

Prof. Paul Ruyssevelt

Outputs


Building Simulation and Optimization 2018 conference paper

Lolo Student Led conference

20180613 Lolo Conference – Grassie