REDUCE: Reducing the operational energy performance gap between real buildings and standardised energy rating systems

The School of Mechanical, Electrical & Process Engineering at Munster Technological University (MTU) invites applications for a highly motivated, ambitious and talented individual to undertake a PhD in Energy Engineering. This prestigious program offers the opportunity to contribute to cutting-edge research, develop advanced engineering skills, and make significant impacts in the field. 

The PhD student will be based full time from Monday to Friday at the Cork campus of MTU and work as part of a larger research project including multiple research staff and stakeholders across different institutes. The research environment will expose the PhD student to a wide variety of experiences in professional research.

The overall aim of REDUCE is to quantify and explain the differences between the energy performance of real buildings and the predicted performance as reported by national energy rating systems and suggest how this gap could be reduced in the future. The project is a collaboration between three partner universities and the support of multiple industry collaborators. The study synthesises and utilises data from a large empirical database (with 59 residential buildings and 9 non-residential buildings) to offer insights into the crucial variables where energy rating software must improve its predictive accuracy in order to ensure resilient and robust national energy projections in the future. The project will compare predictions from energy rating software tools to measured datasets for heat pumps, secondary heating, space heating, hot water, ventilation, solar photovoltaics (PV), appliances and lighting. There are opportunities to deploy various machine learning and data modelling techniques within the project.

The PhD researcher will assess a number of different types of buildings including residential, office, schools, universities and industrial buildings. The PhD researcher will work with key stakeholders in the industry to evaluate and initially present the gap that exists in these buildings for different end-uses. A key part of their PhD will be to go beyond the state-of-the-art and provide a pathway to predictive improvement in the performance of building energy rating and modelling approaches. Their work will contribute greatly to policy in this area and will also lead a number of peer-reviewed publications. Finally, the project will suggest and report on ways in which current energy rating systems can be improved to reduce the performance gap and how design can be improved in the future to ensure buildings perform closer to expectations.

The ideal PhD candidate must possess strong numerical and analytical skills, demonstrating a high level of proficiency in handling complex mathematical and statistical problems. Given the nature of the research, which often involves extensive data analysis and computational modeling, it is crucial that the candidate is comfortable working with large datasets. This includes not only the ability to manipulate and interpret data accurately but also to develop and apply sophisticated algorithms and models. A solid foundation in numerical methods and statistical techniques will enable the candidate to contribute effectively to cutting-edge research and derive meaningful insights from large amounts of information.

The starting date for the role is September 2024.