Friday 27 February 2026 12:00pm to 1:30pm
Seminar Room, Civil Engineering Building, University of Cambridge
About
The DRF Lunchtime Clinic is delighted to welcome Professor Ruchi Choudhary, Professor of Architectural Engineering in the Department of Engineering at the University of Cambridge, who will join us to talk about From Static to Adaptive: A Virtual Testing Framework for Continuous Commissioning and Performance Optimization of Ground Source Heat Pump Systems.
About the talk
Traditional commissioning, conducted at system handover, often fails to identify and address operational inefficiencies in energy systems over time. This work proposes a model-based adaptive commissioning framework that combines numerical modelling with continuous performance monitoring to detect and address system inefficiencies. A high-fidelity Modelica-based model is developed to enable virtual testing of operational strategies, allowing assessment of possible improvements in system performance without disrupting building operations. Results show that changing from the original dual-unit operation to a single-unit operation with timely preheating can reduce energy use by 16% while keeping indoor thermal comfort. The heat pump COP can also rise to 4.39. The proposed model-based approach transforms commissioning from a one-time verification into an adaptive process, achieving cost savings through control optimization without hardware modifications.
Bio
Dr. Ruchi Choudhary is Professor of Architectural Engineering in the Engineering Department at University of Cambridge. She specializes in simulation methods for predicting energy demand of the built environment. At Cambridge, she leads the multi-disciplinary Energy Efficient Cities Initiative (EECi). The energy questions in her research are wide ranging and interdisciplinary: understanding the synergistic role of food production in urban environments, impact of urban-scale geothermal systems on subsurface climate, Bayesian statistical modelling of uncertainties in energy system models across scales, and city-scale energy planning involving socio-demographic features of populations.