Work

Ontology-driven digital twins for optimized recommissioning of hospital building operations

Year: 2026

Type: article

Abstract: Optimizing setpoints in non-residential buildings is complex due to competing objectives: energy efficiency, occupant comfort, and cost. This paper presents a multi-objective optimization framework integrated with an ontology-based digital twin for building operation optimization. Using the Non-Dominated Sorting Genetic Algorithm II, the framework balances thermal discomfort, CO2 levels, and energy costs, employing semantic models to define building topology and component constraints. Applied to a hospital case study, the approach reduced thermal discomfort by 92% and energy costs by 48% using a comfort-focused strategy with 73 decision variables selected from a Pareto front. Robustness was validated across unseen operational periods, adapting to occupancy and weather variations. Sensitivity analysis identified space temperature setpoints as primary optimization drivers, followed by supplied air temperature. This scalable framework supports building management system recommissioning by mapping results to controllers, suitable for diverse non-residential buildings.

Source: Journal of Building Engineering

DOI: 10.1016/j.jobe.2026.115627

Authors: August M.S. Thomsen, Jakob Bjørnskov, Muhyiddine Jradi

Institution: University of Southern Denmark

Language: English

Topic: Building Energy and Comfort Optimization

Subfield: Building and Construction

Field: Engineering

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Affordable and clean energy, Climate action

Open Access status: hybrid

Estimated APC paid: $3,940