Case Study: Operational Energy Reduction through Data Analysis & Virtual Benchmarking

Darragh GleesonBy Darragh Gleeson, Senior Project Consultant – IES

In this session, IES will explore the use of digital building performance models during building operation to optimise performance and reduce “in use” energy consumption. To satisfy regulatory requirements (e.g. Part L/Section 6) a digital model is created during the design stage for practically all new commercial buildings, but often these regulatory compliance models under predict energy consumption by a large margin, known as “the Performance Gap”.

With additional effort, these compliance models can be enhanced by combining utility and BMS data with the 3D virtual model and undertaking a calibration exercise. This enhanced digital asset provides a much more realistic representation of building performance and energy consumption and can therefore play a valuable role in improving operation of the building and identifying opportunities for energy savings. New Parametric and Optimisation techniques are also playing a key role in reducing the time it takes to undertake model calibration.

During 2016, Barts Health NHS Trust – the largest NHS Trust in the UK – undertook an innovative project with IES to perform enhanced Energy Modelling and Building Management System (BMS) Data Analysis services for the Alex Wing, Dental Teaching Hospital within The Royal London Hospital.

The project aimed to take advantage of the existing BMS and extensive sub-metering infrastructure and utilised the latest advances in building performance modelling to deliver innovation in how the Trust approaches assessment of proposed Energy Conservation Measures (ECMs).

Through a combination of building data and advanced computer modelling, IES succeeded in creating a virtual benchmark of the building which comfortably meets the calibration thresholds for ASHRAE Guideline 14. The calibrated model was used to identify operational issues and assess potential Energy Improvement Strategies, with possible energy demand reductions of 22.5% for Gas and 30% for Electricity demonstrated.

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