IES' Dr. Naghman Khan presentation on big data in building services from our IES Faculty event, which took place in London on 27th April, 2016. The seminar focused on the application and status of Intelligent Big Data in the fields of building services, architecture and construction.

2. IES Faculty Event
Intelligent Big Data in
Building Services
Presenter: Dr. Naghman Khan
27th April 2016

3. Better Buildings, Smarter Cities

4. IES Research & Development
Building Operation is key focus of IES R&D

5. An Integrated Approach

6. 9:00 – 9:30 Registration & coffee
9:30 – 9:40 Welcome & introduction (Naghman Khan)
9.40 – 10.05 What is Big Data? (Daniel Tuohy)
10.05 – 10.50 Big Data in Building Services (Naghman Khan)
10.50 – 11.20 Coffee break
11.20 – 11.40 The Client’s perspective (Thomas Bouriot, TFT)
11.40 -12.00 Live ERGON demo (Daniel Tuohy)
12:00 – 12:30 Q&A, Discussion & Feedback forms
12:30pm Finish
IES Faculty Agenda

7. What is BIG DATA?

8. BIG DATA in Building Services

9. Gaps in Performance

10. BER Regulated
Load
Carbon Buzz Innovate UK Carbon Trust
57% of BER
280% of BER
Up to 400% of BER
Building Emissions Rate (BER) vs.
actual in-use energy consumption
How Big is the Discrepancy?
Figures vary but it exists

11. 25%
25%
25%
25%
Regulated Load
Unregulated Load
Remaining Performance Gap
Unregulated load accounts for an average
of 25% of overall energy use
BER Regulated
Load
Carbon Buzz Innovate UK Carbon Trust
Why the Discrepancy?
Goes up to 65% in offices

12. Bridging the Discrepancy
Dynamic Simulation Model +
Operational Data
Actual
Building
Gap between predicted and
actual performance can be closed
to 5-10%

13. Untapped Data Asset
Today increasing volume of Data is available at every
stage of the building life cycle

22. IESVE for PerformanceIESVE for Architects IESVE for Engineers

23. Untapped Operational Data

24. How much data
• Monthly kWh 12 points annually
• HH kWh 48 points x 30 days x 12 months = 17,280 points
• HH gas, heat… water……. = 50,000 points
• Sub-meters, typical new office building might have 50
• ……..data points increase exponentially = 2.5 million already
• Portfolio of buildings…. 100 buildings large client, hundreds
of millions of data points
• What about BMS?
• Typical office building with heating/cooling might have
300 relevant BMS points recording data (5 million for 1
building)
• What are we doing with this data?

25. Digital Built Britain – BIML3
• “The Information Economy Strategy identifies that our
most pressing societal challenges manifest themselves
in our cities.
• Rapid urbanisation is a critical issue in emerging
markets, which are demanding cleaner, more
sustainable and healthier urban environments, with
reliable sources of energy and less congestion.
• City leaders around the world are turning to integrated
and intelligent smart systems and associated big-data
concepts to deliver vital public services”

26. Digital Built Britain – BIML3
“The ability to measure “in service” performance and compare it to “as briefed” and “as
delivered” assets - providing the single biggest opportunity to improve both cost and
carbon performance.
The ability to bring together through open data standards from design, construction and
operations and across market sectors - offering the ability to analyse and create the
learning feedback loops that industry needs to be able to deliver sustainable long-term
improvements in asset performance.”

27. BIML3

28. Digital Built Britain – BIML3
“Recent work in connection with the Government Soft Landings (GSL) initiativehas
highlighted that commercial mechanisms are not currently able to facilitate a greater focus
on the absolute achievement of performance requirements.
The involvement of multiple parties employed on a skill and care basis makes it currently
difficult to enforce performance requirements. This is a partial explanation of the widely
observed ‘performance gap’ in buildings and is a key driver behind the introduction of GSL.”

29. Digital Built Britain – BIML3
Snippets from ‘what does the future look like’..
• Data-enabled collaborative working in the design, construction and operation of assets
enabling best use of capability in the supply chain to deliver value to customers
• Use of data recording asset operation and condition to understand asset performance,
define better project briefs and to form the basis of new performance contracting models
• Application of remote monitoring, telemetry and control systems to the real time
operation of assets and networks

30. Untapped Operational Data

31. Using Data

32. Industry Demand
Over 75% of Carbon Trust ESOS audits
identified a need for better metering
and/or BMS
Proportion of Carbon Trust ESOS recommendations
relating to metering and/or BMS.
22%
31%24%
23%
Metering
BMSBoth
Neither
[Source: Carbon Trust]

33. Data Overload
Increasing Volume, Variety & Velocity of Data
• Organise & manage it to reduce risk
• Make sense of it to find opportunities
• Deliver added value and save ££

34. More data captured and managed = clearer picture of your building’s performance
Using Data to build a complete picture
With Analysis, Data is Powerful

35. VE FOR PERFORMANCE

36. VE for Performance
Energy performance predictions rely on:
– Robustness of calculation engine
– Data available
VE for Operation delivers the power of operational data into the
robust VE Energy Performance model

37. An Integrated Approach
IESVE Software

38. Calibrated Models
• Building energy models may be used in all phases of
BLC from design to commissioning and operation.
However, for operational use, there is a need to
address any discrepancies between design
performance and actual performance;
• Building Model Calibration is the process of improving
the accuracy of simulation models to reflect the as-
built status and actual operating conditions

39. Level 3 – BMS Data
(Kit/Plant)
Level 2 – Sub-Metered Data
(Zones)
Level 1 – Metered Data
CalibratedModel Levels of Calibrated Modelling

40.  30% Reduction in Lighting Load
 62% Reduction in Equipment Load
Illustrative example of using data

41.  The combined impact of the actual equipment and lighting loads on the annual boiler
energy compared with the Compliance profiles is shown below
 The compliance model has a 34% reduction in heating energy when compared to the
calibrated model.

42. John Lewis York, UK

43. Outstanding Collaboration
CIBSE Collaborative Working Partnership Award
“John Lewis, York slashed its absolute carbon emissions by a massive 43.8%.”
• 4 Year Collaboration: Lateral Technologies, IES & Next Control Systems
• Next Generation operational monitoring and energy management
• IES-ERGON reads data from BMS and refines it with the design model to highlight
performance gaps

44. • BMS can log any data point but common practice is to log only
default points on a 7 day memory cycle
• The building simulation model used throughout design and
construction routinely becomes obsolete at handover
• The strategic value of the building model is underestimated
• No strategic consideration of logging requirements on handover
Industry Issues
Building Data
Down the Drain

45. Innovative Technology Solution
• IESVE 3D model shared between all
parties
• Operational data from benchmark store
used to inform design
• IESVE ApaceHVAC used to right-size
plant and save Energy + CapEx
• IES ERGON Software deliver enhanced
calibration of the building simulation
model using real-time BMS data to
reflect actual plant performance,
occupancy and weather conditions
• Platform with a difference – supports
commissioning, M&V, Soft Landings and
continual analysis of building operation
• Overlay of Design vs Real data streams –
performance differences reported, investigated
and resolved
• Data profiles can be plugged into future store
designs

46. • BREEAM Outstanding Store
• Carbon emissions down by a massive 43.8%
compared to the benchmark; 14% more
savings than original expectation
• Chiller uses 25% less energy due to accurate
predictions of store’s cooling needs. Also
reduced CapEx.
Headline Results

47. Simulation Methods
York: Simulated Chiller Size
Steady State Dynamic
Simulation
• Steady state method - evaluate heating
and cooling loads for a peak weather
condition at a single point in time
• Dynamic Simulation Method (DSM) -
Evaluate heating and cooling loads over a
design year taking into account internal
load profiles and building thermal
response
• Calibrated Simulation - As dynamic
simulation but now with the ability to
evaluate HVAC performance in line with
advanced BMS control strategies
Calibrated
Simulation
28% reduction
against steady
state
40% reduction
against steady
state

48. Implication
• Technology is available
• Clients will start demanding buildings which
operate closer to design predictions
• Consultants need to stay ahead of the game
• Enables Data Driven Design to feed into
Commissioning, Operation and Retrofit

49. TFT

50. ERGON demo

51. VE for Performance
 ERGON – Real life building profiles
 Training
 Monthly VE Face-to-Face training events & e-training
 NEW ERGON Training – ask us for more details
 Advanced HVAC Training
 Project Based Training
 Consulting Support

52. Dr. Naghman Khan
Naghman.khan@iesve.com
www.iesve.com
www.iesve.com/DiscoverIES

53. Thank You