Progressive building energy models for facility management

Existing buildings entail a third of the energy consumption in the world and contribute a similar share of greenhouse gas emissions. At the same time, they have been shown to have a large potential for improvement in both fronts. Just enhancing operations of what is already in place is estimated to reduce energy and operational emissions by 20% on average.

A significant area of work has focused on whole-building analysis and simulation to rigorously understand performance of existing assets. Here, building audits are combined with holistic physics-based models to improve understanding of what is built and to devise ways to improve operations and retrofit packages. However, such an approach requires specialist knowledge and can easily become onerous given time, interrelationships of physical processes, and resources needed. In addition, it does not link well with metering and building management systems buildings have in place as they only monitor buildings partially.

This project seeks to investigate the role of progressive energy modelling to assist facility managers understand and improve the performance of existing assets. Building systems can be modelled in a wide range of ways, and it is possible to isolate components for dedicated analyses. Then, they can be extended to include further parts relevant to the system. As an example in HVAC systems, heating/cooling generation via heat pumps or boilers could be analysed with a dedicated model, aided by monitoring points typically implemented, like supply/return temperatures or partial loads. Once it is verified that the system works as expected, the model can be extended to represent further parts of the whole system, like losses in distribution systems, emitters, or links with ventilation systems.

Compared to whole-building simulation, this is a bottom-up modelling approach that conceives buildings as a jigsaw of systems that have a closer correspondence with established monitoring practices in facility management. It simplifies complexity, offers faster feedback cycles, retains meaning to explore alternative ways of operating buildings, and could be done in a way that paves the way to whole-building modelling as required.

We are seeking applicants wishing to advance the state of the art in this area, including exploring the role of model complexity, model interoperability, and influence on facility managers' decision-making processes.

Further information

This is a joint PhD project between The University of Edinburgh (Dr Daniel Fosas) and Heriot-Watt University (Professor David Jenkins). The context of the work will be the campuses of these institutions and students will have access to their combined training opportunities.

We welcome applications from all qualified candidates, and we wish to particularly encourage applications from groups underrepresented at this level.

 

To apply to this opportunity, you will need to:

  1. Meet entry requirements (see here). Note this mainly relates to (a) have a degree classification of at least 2:1 or equivalent, (b) have funding, (c) meet English requirements.
  2. Prepare documentation required for conditional admission in the PhD programme (see here). Please note that this requires a formal 2-page research proposal (see guidelines here).

 

We are available to discuss and give feedback to applicants that meet entry requirements.

A comprehensive training programme will be provided comprising both specialist scientific training and generic transferable and professional skills. The PhD candidate will be introduced to comprehensive training options, within The University of Edinburgh and Heriot-Watt University.

The candidate will have the opportunity to become a teaching assistant following formal training, as well as opportunities to contribute to wider training and outreach activities. Further training in both academic and interdisciplinary skills will be available as part of Edinburgh’s Institute for Academic Development.

Closing date: 
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Principal Supervisor

Assistant Supervisor

Eligibility

Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. 

A background related to building performance simulation and building services engineering would be an advantage for the project. The project will require development of building simulation models, off-the-shelve and bespoke ones, and data mining: familiarity or willingness to learn programming languages like Python, Julia, or R will be essential

Please click on this link for further information on English language requirements for EU/Overseas applicants.

Funding

Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere.

Further information and other funding options.

Informal Enquiries