PhD Project: Quantifying Demand Flexibility in the Irish Commercial Building Stock

Technological University Dublin; Ireland; On-site; EUR 19,000 - 27,000; Full time

Job summary

Technological University Dublin invites applications for a First Stage Researcher (R1) PhD position in energy systems and building stock. The candidate will work with IBSO and OPN Buildings datasets to construct demand/load profiles from real buildings.

The work compares these profiles with the Irish electricity system's renewable share and curtailment patterns to identify where demand can be steered to align with supply, advancing a harmonised energy future.

Qualifications

• Background in building services or energy engineering.
• Interest in working with real operational data from a live national portfolio.

Responsibilities

• Assemble a representative dataset of buildings drawn from OPN Buildings' live portfolio.
• Analyze measured electrical loads and aggregate into demand profiles.
• Compare demand profiles with supply-side patterns to identify divergence and adaptation potential.

Job description

First Stage Researcher (R1) (Up to the point of PhD)

Not funded by a EU programme

About

Outline

Ireland's commercial and public-sector building stock is a large, controllable and largely unquantified source of electricity demand. The Irish Building Stock Observatory (IBSO) is currently carrying out work to characterise the non-residential stock and to develop a set of non-domestic Reference Dwellings, in parallel with the residential Reference Dwelling set (Li et al., 2025) that underpins the companion PhD in this programme. This thesis does not repeat that characterisation. Instead, it works from a portfolio dataset of real buildings. The student will assemble a representative dataset of buildings drawn from OPN Buildings' live portfolio, which spans universities, airports, manufacturing sites, hospitals, museums and local-authority buildings, checked for representativeness against the sector typologies IBSO's work identifies. For each building in the dataset, the thesis will examine measured electrical loads from OPN's continuous sub-metered and building-management-system data, and aggregate these into demand load profiles, first for individual buildings and then for the portfolio as a whole. These demand profiles will be compared against supply-side profiles, principally the time-varying renewable share and curtailment pattern of the Irish electricity system, to identify where and when demand and supply diverge. The thesis will then qualify the potential of the dataset's building loads to adapt: to switch on at times of excess renewable supply and switch off at times of scarcity, moving demand toward an idealised energy system in which supply and demand are harmonised. Because this adaptation depends on both building-level control capability and system-level communication, the thesis addresses two further questions. First, how much of the identified adaptive potential is deliverable given each building's Smart Readiness Indicator (SRI) score and Building Automation and Control System (BACS) class. Second, how a platform such as OPN's could function as a communication layer, or middleware, between the TSO and the demand side: aggregating building-level load and flexibility data upward for system visibility, and translating TSO dispatch or price signals downward into instructions individual buildings' control systems can act on.

What is funded

Funding Agency: Research Ireland

Student Stipend per annum

Materials & Travel Budget per annum

Fees covered by the funding per annum

Application Closing Date:23rd October 2026

This PhD suits a candidate with a background in building services or energy engineering, energy systems, with an interest in working directly with real operational data from a live national portfolio.

The responsibility for the funding offers published on this website, including the funding description, lies entirely with the publishing institutions. The application is handled uniquely by the employer, who is also fully responsible for the recruitment and selection processes.