How Digital Engineering Can Improve Building Operation

Darragh Gleeson, Senior Project Consultant, IES

The construction industry is not renowned for being open to change. However, Digital Engineering concepts such as building simulation and improved digital information management are assisting in the design and construction of better performing buildings.

Can these Digital Engineering concepts be effectively applied at a building’s operational stage too?

Background

Simulation of building performance using 3D modelling and thermal simulation software is a mature discipline. Simulation software has been employed for decades in the design of buildings. The increased digitisation of building documentation using Building Information Modelling (BIM) has led to the recognition of Digital Engineering as a distinct sub-discipline in the design of modern buildings.

Simulation modelling of buildings allows designers to virtually test their designs prior to construction, examining the impact of design decisions on building running cost, occupant comfort and level of daylight. The introduction of the National Calculation Method (NCM), which uses building modelling as a way of demonstrating compliance with Part L2a of the building regulations, ensures that modelling is a key part of the design of modern buildings. Given the NCM is also used to create Energy Performance Certificates (EPCs) most commercial buildings in the UK will have a 3D model of some description created.

However, there is a persisting misconception in the UK industry that Part L/Energy Performance Certificate (EPC) compliance models should somehow suffice for design analysis, and in some cases are mistakenly used as a form of operational energy prediction.

The compliance model is simply a benchmark exercise and omits key design/energy elements within the building in its calculation. For example, unregulated loads such as plug loads, server rooms and external lighting.

Reliance on compliance models in lieu of design analysis contributes not only to unrealistic energy expectations, but also to unexploited energy saving opportunities, overheating and other internal comfort issues. It wastes capital expenditure, operational expenditure and leads to dissatisfied end users.

With only a little extra effort, designers could create simulation models that accurately capture their design intent. This same simulation model then becomes a digital asset, which may be used to verify that the building that is constructed is operating as intended.

Data, Data, Everywhere…

In recent years, there has been a huge increase in the quantity, quality and accessibility of building data. The Internet of Things (IoT) has unlocked the potential to collect real-time data about the individual components that make up our buildings. Smart Meters can deliver half-hourly utility meter readings and Building Management Systems (BMS) monitor and control a wide range of building services.

However, in practice, such systems are often not set up in a way that provides useful information to building operators and energy managers and there is often a lack of “effective” commissioning undertaken prior to building handover. Routinely clients inherit buildings with design flaws, inefficient control strategies and insufficient capability to collect or report energy performance in a way that is meaningful to operators.

Further, sub-metering frequently fails to deliver on its potential. Sub-metering strategy is regularly a case of “put a meter on each distribution board” with little thought given to how operators can make use of this information. Meter selection must be driven by a metering strategy that provides insights into what building equipment is consuming energy and when. Good commissioning would help catch frequent failings in sub-meter installations, including ill-thought-out metering strategy, faulty meters, badly sized meters, and meters that require manual reading.

A well-developed simulation model which produces an accurate estimation of building consumption is a valuable tool during commissioning. Differences between metered building performance and simulated behaviour can be investigated to determine whether differences are driven by building faults or incorrect assumptions in the model. Control strategies, tested virtually in the model prior to construction, can be verified as working in practice through comparison of measured and simulated building data. Additionally, a well thought out sub-metering strategy that provides granular data on end-uses facilitates this comparison between model and reality, reducing uncertainty in the diagnosis of building issues.

Calibrated Modelling
A simulation model which provides a close match to measured energy consumption of a building can be said to be a “calibrated model”. Traditionally, creating calibrated models was seen to be challenging due to the vast quantities of input data required to be entered into modelling software and the high level of uncertainty surrounding this data. However, digitisation of construction documentation through BIM and the continued use of simulation modelling throughout the commissioning process removes some of the traditional barriers to calibration.

In addition to being useful during commissioning, the models can also be used for a wide range of applications including:

  • Monitoring & Targeting (M&T) of energy sub-categories in a building, particularly those that vary significantly with weather.
  • Identification of Energy Conservation Measures (ECMs) and estimation of expected payback through virtual testing of the ECM in the simulation model. These ECMs could be anything from a small control tweak, to extensive building retrofit options such as external cladding.
  • The simulation model can also be used for Measurement & Verification (M&V) of any applied ECMs as the pre-intervention model can effectively be used as the Baseline model for calculation of savings.

Existing Buildings
Whilst the continued take up of Digital Engineering techniques makes it easier to utilise simulation modelling in new buildings, the benefits of modelling can equally be applied to existing buildings. The proliferation of recordable building data, outlined above, represent an often untapped resource in many existing buildings.

Where existing construction documentation may be scarce, building data such as BMS trend logs and temporary IOT sensors can be used to gain insight into how a building operates. Coupled with modern data analysis tools, building data can be interrogated to determine the appropriate inputs into a simulation model. A process of iteration, comparing simulation outputs to measured sensor and meter data, leads to a calibrated simulation model of the existing building. Once created, the calibrated model becomes a digital asset which may be used by energy managers for the applications outlined above i.e. ongoing M&T, ECM identification, and M&V.

The Future

Ultimately where this technology leads us is to a situation where calibrated simulation models can be fed with real-time sensor data, tariff information and weather predictions, and used to simulate thousands of control strategy variations. These can be fed back into the Building Management System in the form of highly optimised control strategies.

Conclusion

Digital Engineering techniques such as building simulation are increasingly being employed in the operation of buildings and not just during the design stage. Coupled with better management and increased utilisation of building data, such as sub-meter and BMS data, it can be a valuable digital asset for building operators and energy managers.

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