Trial / Demo
Following on from part one of this two part Q&A series, Mark Gifford tackles more of your questions around Data & Metering strategies for Digital Twin development, that were submitted following our exclusive Defining Digital Twins session. Held in partnership with the B1M, the session brought together a number of industry experts and sparked significant interest.
Read on for part two, where Mark shares more valuable advice on a range of topics from digital twins and data management, metering and thermal zoning, to BMS and data flow.
Will the growing demand for Digital Twins drive better alignment of Information Management with operational needs and systems (like BIM, CAFM, and BMS), given current gaps between static BIM data and dynamic building data? Is it time to rethink IM strategies for digital twins?
The growing demand for Digital Twins offers a significant opportunity to rethink Information Management (IM) strategies, particularly in addressing the disconnect between static BIM assets and the dynamic data generated by buildings in operation. Traditional BIM workflows focus heavily on the design and construction phases, resulting in data models that often get shelved shortly after handover and can quickly become dated and non-current.
Digital Twins however rely on continuous and dynamic data exchange from the operational building systems and sensors to deliver actionable insights. To bridge this gap, IM strategies must evolve to address the requirements and challenges of integrating legacy design models with dynamic operational systems such as CAFM, BMS, and IoT networks, paving the way for a federated performance-based ecosystem.
Aligning the Before and After requires a paradigm shift towards interoperability and the contextualization of data (or metadata) emerges as a new but significant theme. Digital Twins necessitate a holistic approach where data is not only accessible but also standardized, open, and usable across platforms. By incorporating open data standards and data-driven management procedures, organizations can create a new breed of performance model where operational data dove-tails in to the existing BIM model infrastructure. This ensures that building managers, engineers, and all key stakeholders have access to both historical predictions and real-time data. This offers a whole new range of possibilities for more informed decision making, empowering predictive maintenance, and enhanced building performance throughout the full asset lifecycle.
How does the Metering / submetering scheme for different energy end uses affect the thermal zoning in the energy model or digital twin? Does more submetering make the model complex in order to extract relevant information as per the scheme?
Thermal zoning involves managing heating and cooling, which brings in both heat meters (for water flow) and electrical meters (for power). Since each type of meter is specialised—heat meters in pipes and electrical meters in wires—effective thermal zoning relies on good coordination between mechanical and electrical systems.
In practice, though, mechanical and electrical engineers often work separately, which can lead to disjointed metering setups. If a holistic approach to metering strategy isn’t integrated from the start, issues like overlapping or inconsistent data can arise.
Submetering can add complexity to models, especially in systems with both horizontal and vertical zoning configurations. Picture a building floorplate divided into sub-zones, each with separate units for different corner orientations (NW, NE, SW, SE). When stacked vertically across multiple floors (Levels 1, 2 3, 4 etc) the mix of ducts/pipes for HVAC and meters for heat/power can become hard to sync if the metering isn’t planned well from the beginning. So, yes, more sub-metering can add useful detail but also increases overall system complexity, a well-coordinated metering strategy is essential for effective performance monitoring. So, remember always tailor your model to your desired end-use.
How does monitoring the operation of a building using a Digital Twin compare with using a BMS System for the same purpose?
Using a Digital Twin to monitor a building offers much more flexibility and depth than a traditional Building Management System (BMS). BMS systems are often proprietary with limited data views and analytics capabilities. They allow for basic monitoring but lack the flexibility for advanced, dynamic analytics. For example, with BMS, it’s harder to compare meters, analyse historical data in depth, or view high-frequency data.
Digital Twins, on the other hand, offer links to physics-based simulation, as well as analytical algorithms and routines that facilitate data exploration, comparison across systems, and flexible user-driven analysis, ensuring that the right information is provided to the right project stakeholder. In short, Digital Twins allow for a much deeper and more dynamic approach to monitoring building performance.
Using a typical example of Digital Twin, can you explain how information flow from the physical building to the digital (and vice versa) and how sensors and actuators come into these processes?
In an IES Digital Twin, information flows from the physical building to the digital model primarily through the iSCAN data gateway, gathering data from sensors and actuators connected to the Building Management System (BMS), Building Energy Management Systems (BEMS), or IoT sensors. The BMS handles data from sensors and actuators for HVAC controls, space temperature, CO₂ levels, fans, and pumps, while the BEMS often integrates both HVAC and electrical metering data. IoT sensors can be added as a quick way to gather data on internal air temperature, CO2 levels, humidity and occupancy levels where other options don’t exist.
This data can be extracted in real-time and analysed on its own, or imported into the IES Digital Twin. Although traditional BMS systems can present a number of challenges in terms of achieving the level of data access required (closed protocol vs open protocol) the industry is increasingly modernising and evolving. Expanding data access with IoT protocols like MQTT or OBIX helps bridge these data gaps, making the Digital Twin more dynamic and able to respond to real-time building conditions. Occupancy data can also be used to replace assumptions for different profiles, ensuring an accurate representation of the building in operation.
To utilise the IES DT capabilities, for example, to see real-time building energy and environment data, what type of hardware (meters/sensor, etc.) is required to connect with the IES?
To leverage IES’s Digital Twin for real-time building energy and environmental data, you generally don’t need a full hardware overhaul—most buildings already have most of the underlying essential infrastructure in place. If your building has a BMS or BEMS with HVAC controls, energy meters, and access to half-hourly utility data, you’re well on your way.
IoT sensors can also be added as a quick way to gather data on internal air temperature, CO2 levels, humidity and occupancy levels where other options don’t exist.
Existing BMS Controllers can often be sophisticated enough for this task; it’s often more about commissioning and configuration rather than new equipment. Upgrade and installation to incorporate an embedded web server controller (or JACE) may be required to facilitate enhanced data collection and live data transfer. The real challenge is normally less technical than people think and more commercially based — exploring the themes like data ownership, data governance and the contractual implications of making this data more openly available.
About Mark
Mark specialises in Energy Services, Monitoring Based Commissioning, Data Analytics and Measurement & Verification (M&V), and leads a specialist team of engineering consultants whose primary focus is Building Performance Optimisation projects via integration with smart metering and BMS controls data.
Contact our team for more information or visit our website.
Defining the Digital Twin
Missed our Defining the Digital Twin Webinar in partnership with the B1M? View the on-demand version to hear what industry experts had to say.
Want to discover the capability of IES' suite of Digital Twin technology? Sign up for our upcoming web demo.
This blog is part of a two part series. Click here to read part one.
