The Role of Performance Digital Twins in Achieving Net-Zero Campus Estates - IES

Many universities have set in place ambitious targets to achieve net-zero carbon by as soon as 2030. However, understanding where decarbonisation measures should be implemented and prioritised, particularly when there is often a mix of new and historic buildings to consider across the campus estate, can present many challenges. Not least when there is also a need to optimise the educational environment to meet the needs of both students and staff, while keeping costs at a minimum.

This session will explore, through a selection of real case study examples, how performance digital twin technology is being utilised by a number of UK institutions to support the decarbonisation of campus buildings. Sharing lessons learned to outline a holistic, data-driven approach which can encompass both short-term optimisation measures and longer-term decarbonisation investments to plan, implement and manage current and future operational performance at both a campus and individual building level.

1. The Role of Performance Digital Twins in Achieving Net-Zero Campus Estates Erik Archer, Associate Director, IES [email protected]

2. The Decarbonisation Challenge Buildings are complex, dynamic systems Energy, carbon & cost must balance Designed for energy but operated for comfort Need to ensure occupant health & wellbeing Where/how to invest to decarbonise Need confidence in financial risk and ROI Mix of old and new buildings on campus estates Aging BMS systems and data challenges

3. Making Good Decisions Digital technology is key Data vs actionable information Minimise costs of decarbonisation Optimise building & system operation Long term Net-Zero investment plans Reduce carbon impact of facilities while balancing other priorities, e.g. Optimise educational environment for staff & students Support occupant health & wellbeing Keep operational costs at a minimum

4. Making Good Decisions Source: UKGBC. Building the case for net zero: retrofitting office buildings – Jan 2024

5. Net-Zero Opportunities Mitigate Energy & Climate Risks Attract eco-conscious students Deliver Operational Efficiency Reach Net-Zero Goals Achieve Regulatory Compliance Modernise and Digitise your Campus Buildings Investment Grade Intelligence Enable Financial Planning Lead on Net-Zero Technology & Research​ (Living Lab)

6. What is a Performance Digital Twin? A digital representation of a building's physical and functional characteristics to simulate its energy performance Streamline operations Enhance energy efficiency Actionable intelligence Real-time digital replica of a physical structure

7. Performance Digital Twin

8. Digital Twin Applications

9. Best Practice Approach to Decarbonising Buildings Assess Data acquisition & analysis Robust energy modelling Plan Efficiency first Retrofit scenario assessments Decarbonisation pathway Implement Optimise Operation Invest in Net-Zero Monitor & Optimise Ensure value of investments delivered

10. Step 1: Building Energy Modelling Base Energy Modelling ​ Fast and scalable Creates robust high level baseline Understand current energy and carbon performance Advanced Energy Modelling ​ High detail energy model Accurate breakdown of energy use Virtual testbed for simulating retrofit scenarios Lifelong digital asset

11. Step 2: Net Zero Scenario Testing Weather and climate scenarios Operational changes Occupancy changes Fabric Upgrades ​ Technology replacements ​ Conditioning Upgrades Adding Renewables ​​

12. Step 3: Decarbonisation Pathways Bring together detailed improvement scenarios Create decarbonisation roadmaps or transition pathways Align with targets ​ Interactive online dashboards Compare impacts and payback periods Balance energy, carbon and cost alongside comfort, health & wellbeing​​

13. Ongoing Energy Management Unlock the full potential of your building data Close the performance gap​ Identify performance drift​ Understand energy impact of comfort settings ​ Save energy from layout changes​ Stop HVAC performance degradation​ Identify savings linked to fixing broken or faulty equipment​ Track savings from improvement projects Utilise - not waste - design energy models​

14. Whole Life Building Performance Evaluation Ongoing Energy Management Digital Twin

15. Digital Twins in Action: University of Glasgow

16. A Brief History of the Work Academics using IES software to create building energy models across the campus since 2015 2019 – Innovate UK eDigit2Life project was funded, created first Digital Twins across the campus and created working relationships with stakeholders across the University 2023 – Transferred research to real-world application, using Digital Twins to create a Living Lab for the campus with 3 core goals: Ensure new buildings perform as expected Analyse and optimise existing buildings to help identify areas for improvement Look at the wider campus to provide information to define the Universities strategy towards net zero, including decarbonisation of the district heating network

17. Stage 1 – Identify Waste Energy (New Buildings) New buildings are not performing as anticipated and using significantly more energy than budgeted This is known as the Performance Gap C osting the University more than forecasted in their financial plans IES Digital Twins can verify that the building performs as expected This will close the performance gap and ensure budgets are met Lessons to take to Keystone and other new buildings ARC MBx Example: Lab consuming high energy that needs to be investigated JMS MBCx Observations/ Defects

18. Stage 1 – Identify Waste Energy (Existing Buildings) There are significant savings to be made in existing buildings through BMS optimization Potential savings of 33% on heat and 7% on electricity Approximate cost saving of £6.3k (for the month of August only) Yearly savings in the region of £50k to £100k (single building) Number Area of Operation Heating (MWh) Electricity (MWh) Value Diff Value Diff Baseline 85.7 332.4 1 7am-10pm operation 84.4 -1% 305.5 -8% 2 Heating valve 58.0 -32% 330.0 -1% 3 Setpoints variations 63.9 -25% 332.7 0% 4 Photo archive setpoint 85.2 -1% 332.3 0% 5 Co2 Sensors 65.7 -23% 275.9 -17% 6 Humidity control 93.6 9% 352.2 6% 7 Hex Supply temperature 85.3 0% 332.4 0% ALL 57.7 -33% 309.7 -7%

19. Stage 2 – Scenario Planning Various scenarios tested at the building & campus level Occupancy analysis carried out at the building level (Library) to determine periods of low occupancy. Explored impact of simple shut down after 8pm (set back temperature of 15 o C and turning off the lights from floor 5-12) as well as more detailed strategy, to cover holiday periods. A high-level study to look at 2 scenarios was undertaken at the campus level : Scenario 1 - LED and Dimming Control: All Campus Buildings Scenario 2 – Roof replacement of 3 buildings and windows replacement of 11 buildings, which were poor condition

20. Stage 2 – Scenario Planning Example Results Potential savings identified at campus level : Scenario 1 (LED lighting + dimming controls) = Estimated 16% of total energy consumption (4667MWh) and over £1million savings per year Scenario 2 (envelope upgrades for buildings rated D or lower) = Estimated energy consumption reduction of 1306MWh Further detailed analysis required to estimate ROI for both options to aid informed decision for CAPEX

21. District Heating Analysis A high-level analysis of the district heating network was also carried out Analysis showed it would be possible to drop the supply hot water temperature and switch to a low temperature system Early calculations showed that switching to a heat pump system has potential to significantly increase system efficiency Further detailed analysis required to further investigate the viability of this solution

22. Digital Twins in Action: University of Liverpool

23. Phase 1: Assessing Impact of HVAC Refurbishment University started engagement with IES after seeing the work IES were doing with University of Glasgow around Digital Twins First pilot for Digital Twin: Foundation Building Built 2003 Undergoing HVAC refurbishment Initial version of DT created (calibrated with Monthly pre-COVID data) Use DT to evaluate HVAC refurbishment 2022

24. Foundation Building: First Digital Twin Energy Model representing energy flow and loads across rooms and spaces Calibrated against monthly measured data for 2019 (pre- Covid ) Allows prediction of the baseline energy use and testing interventions

25. Linear Wing HVAC Refurbishment Evaluation Existing singular air handling unit to be replaced by 2 new units Demand control ventilation implemented LED lighting installed 14% estimated energy savings

26. Live Data Connection Data from BMS, energy meters and sensors flowing live and connected to the DT Temperature, CO2, humidity – status, range & map view (more can be added when available) Energy data from meters

27. Live Data Environment - Efficient Operation Overview of energy use and KPIs in real time: total & breakdown of electricity consumption KPIs displayed and updated in real time: EUI, CO 2 Emissions, Cost etc

28. Upgraded Digital Twin – Operational Insights Model calibrated to match measured data on an hourly basis DT simulated on the cloud daily- results displayed with live metered data Impact of operational scenarios evaluated on the DT (i.e. change of setpoints) Metered vs simulated Baseline vs proposed

29. Evaluating Actual Savings Project Tracking: monitoring actual savings from the HVAC refurbishment since implementation using the Digital Twin 23% verified energy savings (Apr-Dec 2023) £25k operational cost saved (Apr-Dec 2023)

30. Connect occupancy data Display alongside actual energy use in real time Show KPIs such as cost per occupant, energy per occupant etc Next Steps – Occupancy Data

31. Decarbonisation Planning – Interventions Assessment Different interventions were virtually tested on the Digital Twin to evaluate potential annual reduction in energy use

32. Visualising Impact – Interactive Dashboards Energy Conservation Measure impact on EUI & financial metrics Editable investment cost and energy price Decarbonisation roadmap

33. Digital Twins in Action: Heriot-Watt University

34. Phase A: Data Collection and Current Performance Assessment Constructed in 1992 Conventional standalone gas boiler heating (VT space heating) Space temp and plant sensor data available via BMS Monthly Electricity and gas metered data available Floor plans and envelope details available Heating schedules available Limited information available on HVAC system components’ specifications Lack of exact data on equipment consumption, as it was highly user-driven Robert Bryson Halls

35. Phase B: Forecast Simulation and Operational Performance Optimization The University’s vision included a focus on reducing the carbon emissions, so the analysis considered a balance between all the factors, with a focus on reducing Carbon that would eventually decide the recommended ECM. An old HVAC and envelope system meant a high amount of energy was consumed in the dormitory. Energy Conservation Measures (ECM) were analysed in the digital twin to reduce this consumption. The digital twin provides an estimation/baseline performance of the real building, which was not possible before due to lack of sensor data and prior building performance analysis. Robert Bryson Halls

36. Results – ECM Analysis   Robert Bryson Halls Edwin Chadwick

37. Phase C: Campus & Portfolio Level Dashboards

38. Final Thoughts Better design for both buildings and campuses, making better decisions from the outset Better control for both buildings and campuses, optimising energy use, while maintaining health and well-being Better information on which to make investment decisions Better planning and communication of net zero roadmap interventions Better tracking and verification of expected savings post implementation

39. Thank You Any Questions? www.iesve.com