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How Accurate are Operational
Carbon Emissions Projections?
www.iesve.com
How variable carbon intensity modelling can help
improve modelling accuracy, energy grid resilience,
cost, & carbon savings.
Richard Tibenham – IES Consultancy
Business Development Manager
Lewis Goldberg
Graduate Project
Consultant
Richard Tibenham
UK Business
Development Manager
(VE Consultancy)
Agenda
▪ Overview of industry-standard carbon emissions calculation
methods.
▪ Questions;
▪ Are operational carbon emissions calculations accurate when using
aggregated carbon intensity data?
▪ Are aggregated carbon intensities appropriate for the design of ‘Net-
Zero Carbon’ buildings?
▪ Review of UK electrical grid decarbonisation and consideration as
to how this influences the design of buildings.
▪ Modelling approaches using IES software.
▪ Conclusions
www.iesve.com
Carbon Emissions Calculations
Current Industry Standard Methodology for the
Calculation of Carbon Emissions from Buildings:
=
=
Carbon Intensity of
Fuel Source
(kgCO2/kWh)
x
Calculated Operational
Energy Demand by Fuel Type
(kWh/yr)
Total CO2 Emissions
(kgCO2/yr)
Floor Area (m2)
(kgCO2/m2.yr)
www.iesve.com
▪ Building Regulations Part L & Section 6
▪ CIBSE TM54
▪ GLA London Plan
▪ EPC’s
▪ ESOS Carbon Reporting
▪ Many Local Authority planning requirements
Used for:
The performance gap can
be closed using Design for
Performance (DfP)
modelling routes, such as;
- CIBSE TM54
- NABERS
- ASHRAE 90.1
Calculating Operational Energy Demand
Part L compliance assessments & EPC’s
are known to produce a ‘performance gap’.
www.iesve.com
EPC’s = ‘Performance Gaps’
DfP modelling reduces
‘Performance Gaps’
Accurate input data is critical
for accurate DfP modelling
With accurate input data, DfP energy models
can be incredibly accurate.
Part L 2013 – Grid Electricity
BEIS 2022 Long-run Margin – Grid Electricity
Part L 2021 – Grid Electricity
0.519 kgCO2/kWh
0.264 kgCO2/kWh
UK Grid Average 2022
Part L 2021 – Natural Gas
0.210 kgCO2/kWh
All energy demand and carbon intensity data sourced from https://www.nationalgrideso.com/
Part L 2021 carbon intensity profile
Average UK Grid Intensity Annual Average Average UK Grid Intensity Monthly Average
Average UK Grid Half-hourly Intensity
Solar
Nat. Gas
Coal
Wind
Nuclear
www.iesve.com
Why does the
carbon intensity
of the electricity
grid vary?
Electrical energy demand
Carbon Intensity
Key Questions
www.iesve.com
Question 1:
Are operational carbon emissions calculations accurate
when using aggregated carbon intensity data?
Are aggregated carbon intensities appropriate for the
design of ‘Net-Zero Carbon’ buildings?
Question 2:
Question 1
Are operational carbon emissions
calculations accurate when using
aggregated carbon intensity data?
Worked Example
www.iesve.com
▪ Existing city-centre office building.
▪ Based on a real-world building.
▪ Subject to deep-refurbishment under
NABERS rating system.
▪ All-electric HVAC strategy.
▪ No onsite renewable energy generation.
▪ Simulated using Birmingham 2022 Actual
metrological Year (AMY) weather file.
Outline
Specification:
www.iesve.com
Example Building:
Annual energy demand profile
Lighting
Unregulated Electrical Equipment
Space heating
Space cooling
Carbon Intensity Profiles
Op Energy Demand x Carbon Intensity = Op Carbon Emissions Profile
Part L 2022 carbon
intensities under-
estimate carbon
emissions
BEIS carbon
intensities over-
estimate carbon
emissions
heating heating
cooling cooling cooling
Annual CO2 emissions profile when
using Part L carbon intensities
Annual CO2 emissions profile when using 2022
West Midlands half-hourly carbon intensities
Are operational carbon emissions calculations accurate
when using aggregated carbon intensity data?
Question
Operational carbon emissions calculations using aggregated carbon intensity
data do not provide an accurate assessment of carbon emissions under current
grid conditions. Results from such assessments provide approximate guidance
of possible future behaviour only.
Conclusion
www.iesve.com
Question 2
Are aggregated carbon intensities
appropriate for the design of ‘Net-
Zero Carbon’ buildings?
Worked Example
www.iesve.com
To achieve ‘Net Zero’ carbon emissions when using
Part L 2021 carbon intensity assumptions,
2,719m2* of solar PV cells are required.
*Assumed to be orientated due south at an inclination of 35degs with a panel efficiency of 22%.
www.iesve.com
>800kW max. export to grid
240kW max import from grid
Net energy importer Jan-Mar
Net energy exporter Mar-Oct
Net energy importer Oct-Dec
This strategy effectively assumes that the grid
can behave like a battery;
• Assumes that there will be demand on the
grid to absorb surplus energy generation at
any time.
• Assumes that there will be energy supply
when needed.
• Assumes the grid has the capacity to
manage these import & export dynamics.
To limit energy export to <250kW a battery capacity of
10.66MWh is required.
Viable scenario: Distribution Network Operator
(DNO) request that energy export
is limited to <250kW.
www.iesve.com
Energy export capped at ≤250
Solar PV energy offsetting
Building Energy demand
Energy import/export
Battery Charge Status
The addition of the battery
marginally increases annual
carbon emissions when
calculated using Part L 2021
carbon intensity profile.
Incurs net positive carbon
emissions during Jan-May
Incurs net negative carbon
emissions during May-Dec
Theoretically ‘net-zero’ over the
full year
When assessing carbon emission using the West
Midlands Grid carbon intensity profile, the
building is shown to be carbon negative by
~10tonnes per year without a battery
specified.
-9 tonnes CO2
-3 tonnes CO2
When the battery is included, a further 33%
reduction in annual CO2 emissions is
demonstrated
Are aggregated carbon intensities appropriate for the
design of ‘Net-Zero Carbon’ buildings?
Question
Load shifting and energy storage will play a crucial role in the decarbonisation
of the grid, and buildings will likely play a pivotal role in this.
The use of aggregated carbon intensities overlooks the carbon savings
opportunities offered via load-shifting and energy storage measures, and is
therefore considered arguably unsuitable for the design of ‘Net-Zero Carbon’
buildings.
Conclusion
www.iesve.com
The UK’s Decarbonisation
Dilemma and how this may
Influences the Design of
Buildings
www.iesve.com
In the news this week:
“What consumers are being asked to buy is
energy security”.
“According to official estimates published on Tuesday, gas
plants are only expected to be used for around 700 hours in
2030 – the equivalent of about 29 days (8% of the year)”.
“The new plants will be capable of operating efficiently for just
an hour or two at a time to fill in the gaps from other power
sources, the government said”.
24hr Maximum UK fuel
oil and natural gas
demand
Electrical grid 24hr
maximum demand
Additional electrical generation
capacity required if transitioning from
oil & gas boilers to heat pumps
UK fuel oil and natural
gas demand profile
Additional electrical energy capacity
required if transitioning from oil & gas
boilers to heat pumps
2050 Grid Scenario based on CCC guidance:
- Nat gas power generation retained with
CCS.
- 6.5 x wind generation.
- Coal generation removed.
72hr mean average
electrical demand
profile
Generation insufficient to meet demand
Changing priorities between today & 2050:
Modelling Variable Carbon
Intensity & Load Shifting Using
Dynamic Simulation Modelling
NZC Building Design using Variable Carbon Intensity
Modelling :
Step 1:
www.iesve.com
Model an accurate dynamic operational energy demand profile (eg. CIBSE TM54, NABERS, ASHRAE 90.1).
Step 2:
Simulate the model using relevant half-hourly carbon intensity scenarios.
Step 3:
Evaluate carbon emissions performance against NZC design requirements.
Step 4:
Monitor real-world carbon emissions performance using live carbon-intensity data .
2. VE-integrated profiles
3. User-imported profiles
Variable Carbon Intensity Modelling using IES software:
1. VE – Dynamic Simulation outputs
www.iesve.com
The VE provides output data in time steps as low as 1-minute.
The VE includes historic hourly UK carbon emission factors for a
selection of years. These can be set within Energy Source and
Meters
Users can import their own CO2 intensity profiles using APpro, before
assigning within Energy Source and Meters. The following guidance
describes the process.
4. Model with real profiles Actual and forecasted data from Carbon Intensity API
Measured CO2 emissions before and after interventions
5. Monitor & Improve
www.iesve.com
Third-party data can be brought into IES’ data analysis
platform, iSCAN, through APIs. The example shows the
carbon intensity of the UK National Grid data in iSCAN.
This can be brought into the VE as a free-form profile.
This example shows a VE simulated CO2 emissions
profile required to maintain the assets decarbonisation
target compared to a measured CO2 emissions profile
(created in IES iSCAN using metered data.
iSCAN has been used to monitor CO2 performance and
alert the building operator when the measured data
deviates.
Variable Carbon Intensity Modelling using IES software:
Conclusions:
1. Aggregated carbon intensity data not representative of current ‘real-world’ conditions.
2. Designers cannot evaluate the carbon-savings performance of load-shifting strategies using conventional
calculation methods.
3. Load-shifting, time-of-use energy demand, and energy import & export intensity and are likely to
become more dominant factors in building design as we tend towards a NZC grid.
4. Dynamic simulations can be used to evaluate performance to a high degree of accuracy using half-hourly
carbon intensity data.
5. ‘Digital Twin’ software can be used to monitor and optimise real-time, thereby reducing the ‘compliance
gap’ with respect to carbon emissions.
www.iesve.com
Consultancy Support
www.iesve.com
• Geometric modelling
• UK Building Regulations modelling for Part L/Section
6/EPC/MEES compliance & strategic support
• Enhanced Building Energy Models (CIBSE TM54, NABERS,
BREEAM GN32 & ASHRAE 90.1)
• Detailed HVAC modelling adopting IES ApacheHVAC
• Net-Zero and Decarbonisation modelling for strategic
solutions and compliance (e.g. SFT NZPSB Standard)
• Part O strategy support & compliance modelling
• Daylight modelling for Planning Assessments
• CFD for Data Centres/External Comfort/Pollutant Dispersal
Richard.Tibenham@iesve.com
Lewis.Golberg@iesve.com
Thank you.
www.iesve.com

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How Accurate are Carbon Emissions Projections?

  • 1. How Accurate are Operational Carbon Emissions Projections? www.iesve.com How variable carbon intensity modelling can help improve modelling accuracy, energy grid resilience, cost, & carbon savings. Richard Tibenham – IES Consultancy Business Development Manager
  • 2. Lewis Goldberg Graduate Project Consultant Richard Tibenham UK Business Development Manager (VE Consultancy)
  • 3. Agenda ▪ Overview of industry-standard carbon emissions calculation methods. ▪ Questions; ▪ Are operational carbon emissions calculations accurate when using aggregated carbon intensity data? ▪ Are aggregated carbon intensities appropriate for the design of ‘Net- Zero Carbon’ buildings? ▪ Review of UK electrical grid decarbonisation and consideration as to how this influences the design of buildings. ▪ Modelling approaches using IES software. ▪ Conclusions www.iesve.com
  • 5. Current Industry Standard Methodology for the Calculation of Carbon Emissions from Buildings: = = Carbon Intensity of Fuel Source (kgCO2/kWh) x Calculated Operational Energy Demand by Fuel Type (kWh/yr) Total CO2 Emissions (kgCO2/yr) Floor Area (m2) (kgCO2/m2.yr) www.iesve.com ▪ Building Regulations Part L & Section 6 ▪ CIBSE TM54 ▪ GLA London Plan ▪ EPC’s ▪ ESOS Carbon Reporting ▪ Many Local Authority planning requirements Used for:
  • 6. The performance gap can be closed using Design for Performance (DfP) modelling routes, such as; - CIBSE TM54 - NABERS - ASHRAE 90.1 Calculating Operational Energy Demand Part L compliance assessments & EPC’s are known to produce a ‘performance gap’. www.iesve.com EPC’s = ‘Performance Gaps’ DfP modelling reduces ‘Performance Gaps’ Accurate input data is critical for accurate DfP modelling With accurate input data, DfP energy models can be incredibly accurate.
  • 7. Part L 2013 – Grid Electricity BEIS 2022 Long-run Margin – Grid Electricity Part L 2021 – Grid Electricity 0.519 kgCO2/kWh 0.264 kgCO2/kWh UK Grid Average 2022 Part L 2021 – Natural Gas 0.210 kgCO2/kWh All energy demand and carbon intensity data sourced from https://www.nationalgrideso.com/
  • 8. Part L 2021 carbon intensity profile Average UK Grid Intensity Annual Average Average UK Grid Intensity Monthly Average Average UK Grid Half-hourly Intensity
  • 9. Solar Nat. Gas Coal Wind Nuclear www.iesve.com Why does the carbon intensity of the electricity grid vary? Electrical energy demand Carbon Intensity
  • 10. Key Questions www.iesve.com Question 1: Are operational carbon emissions calculations accurate when using aggregated carbon intensity data? Are aggregated carbon intensities appropriate for the design of ‘Net-Zero Carbon’ buildings? Question 2:
  • 11. Question 1 Are operational carbon emissions calculations accurate when using aggregated carbon intensity data? Worked Example www.iesve.com
  • 12. ▪ Existing city-centre office building. ▪ Based on a real-world building. ▪ Subject to deep-refurbishment under NABERS rating system. ▪ All-electric HVAC strategy. ▪ No onsite renewable energy generation. ▪ Simulated using Birmingham 2022 Actual metrological Year (AMY) weather file. Outline Specification: www.iesve.com Example Building:
  • 13. Annual energy demand profile Lighting Unregulated Electrical Equipment Space heating Space cooling
  • 14. Carbon Intensity Profiles Op Energy Demand x Carbon Intensity = Op Carbon Emissions Profile
  • 15. Part L 2022 carbon intensities under- estimate carbon emissions BEIS carbon intensities over- estimate carbon emissions
  • 17. Annual CO2 emissions profile when using Part L carbon intensities Annual CO2 emissions profile when using 2022 West Midlands half-hourly carbon intensities
  • 18. Are operational carbon emissions calculations accurate when using aggregated carbon intensity data? Question Operational carbon emissions calculations using aggregated carbon intensity data do not provide an accurate assessment of carbon emissions under current grid conditions. Results from such assessments provide approximate guidance of possible future behaviour only. Conclusion www.iesve.com
  • 19. Question 2 Are aggregated carbon intensities appropriate for the design of ‘Net- Zero Carbon’ buildings? Worked Example www.iesve.com
  • 20. To achieve ‘Net Zero’ carbon emissions when using Part L 2021 carbon intensity assumptions, 2,719m2* of solar PV cells are required. *Assumed to be orientated due south at an inclination of 35degs with a panel efficiency of 22%. www.iesve.com
  • 21. >800kW max. export to grid 240kW max import from grid Net energy importer Jan-Mar Net energy exporter Mar-Oct Net energy importer Oct-Dec This strategy effectively assumes that the grid can behave like a battery; • Assumes that there will be demand on the grid to absorb surplus energy generation at any time. • Assumes that there will be energy supply when needed. • Assumes the grid has the capacity to manage these import & export dynamics.
  • 22. To limit energy export to <250kW a battery capacity of 10.66MWh is required. Viable scenario: Distribution Network Operator (DNO) request that energy export is limited to <250kW. www.iesve.com
  • 23. Energy export capped at ≤250
  • 24. Solar PV energy offsetting Building Energy demand Energy import/export Battery Charge Status
  • 25. The addition of the battery marginally increases annual carbon emissions when calculated using Part L 2021 carbon intensity profile. Incurs net positive carbon emissions during Jan-May Incurs net negative carbon emissions during May-Dec Theoretically ‘net-zero’ over the full year When assessing carbon emission using the West Midlands Grid carbon intensity profile, the building is shown to be carbon negative by ~10tonnes per year without a battery specified. -9 tonnes CO2 -3 tonnes CO2 When the battery is included, a further 33% reduction in annual CO2 emissions is demonstrated
  • 26. Are aggregated carbon intensities appropriate for the design of ‘Net-Zero Carbon’ buildings? Question Load shifting and energy storage will play a crucial role in the decarbonisation of the grid, and buildings will likely play a pivotal role in this. The use of aggregated carbon intensities overlooks the carbon savings opportunities offered via load-shifting and energy storage measures, and is therefore considered arguably unsuitable for the design of ‘Net-Zero Carbon’ buildings. Conclusion www.iesve.com
  • 27. The UK’s Decarbonisation Dilemma and how this may Influences the Design of Buildings
  • 28. www.iesve.com In the news this week: “What consumers are being asked to buy is energy security”. “According to official estimates published on Tuesday, gas plants are only expected to be used for around 700 hours in 2030 – the equivalent of about 29 days (8% of the year)”. “The new plants will be capable of operating efficiently for just an hour or two at a time to fill in the gaps from other power sources, the government said”.
  • 29. 24hr Maximum UK fuel oil and natural gas demand Electrical grid 24hr maximum demand Additional electrical generation capacity required if transitioning from oil & gas boilers to heat pumps
  • 30. UK fuel oil and natural gas demand profile Additional electrical energy capacity required if transitioning from oil & gas boilers to heat pumps
  • 31. 2050 Grid Scenario based on CCC guidance: - Nat gas power generation retained with CCS. - 6.5 x wind generation. - Coal generation removed. 72hr mean average electrical demand profile Generation insufficient to meet demand
  • 33. Modelling Variable Carbon Intensity & Load Shifting Using Dynamic Simulation Modelling
  • 34. NZC Building Design using Variable Carbon Intensity Modelling : Step 1: www.iesve.com Model an accurate dynamic operational energy demand profile (eg. CIBSE TM54, NABERS, ASHRAE 90.1). Step 2: Simulate the model using relevant half-hourly carbon intensity scenarios. Step 3: Evaluate carbon emissions performance against NZC design requirements. Step 4: Monitor real-world carbon emissions performance using live carbon-intensity data .
  • 35. 2. VE-integrated profiles 3. User-imported profiles Variable Carbon Intensity Modelling using IES software: 1. VE – Dynamic Simulation outputs www.iesve.com The VE provides output data in time steps as low as 1-minute. The VE includes historic hourly UK carbon emission factors for a selection of years. These can be set within Energy Source and Meters Users can import their own CO2 intensity profiles using APpro, before assigning within Energy Source and Meters. The following guidance describes the process.
  • 36. 4. Model with real profiles Actual and forecasted data from Carbon Intensity API Measured CO2 emissions before and after interventions 5. Monitor & Improve www.iesve.com Third-party data can be brought into IES’ data analysis platform, iSCAN, through APIs. The example shows the carbon intensity of the UK National Grid data in iSCAN. This can be brought into the VE as a free-form profile. This example shows a VE simulated CO2 emissions profile required to maintain the assets decarbonisation target compared to a measured CO2 emissions profile (created in IES iSCAN using metered data. iSCAN has been used to monitor CO2 performance and alert the building operator when the measured data deviates. Variable Carbon Intensity Modelling using IES software:
  • 37. Conclusions: 1. Aggregated carbon intensity data not representative of current ‘real-world’ conditions. 2. Designers cannot evaluate the carbon-savings performance of load-shifting strategies using conventional calculation methods. 3. Load-shifting, time-of-use energy demand, and energy import & export intensity and are likely to become more dominant factors in building design as we tend towards a NZC grid. 4. Dynamic simulations can be used to evaluate performance to a high degree of accuracy using half-hourly carbon intensity data. 5. ‘Digital Twin’ software can be used to monitor and optimise real-time, thereby reducing the ‘compliance gap’ with respect to carbon emissions. www.iesve.com
  • 38. Consultancy Support www.iesve.com • Geometric modelling • UK Building Regulations modelling for Part L/Section 6/EPC/MEES compliance & strategic support • Enhanced Building Energy Models (CIBSE TM54, NABERS, BREEAM GN32 & ASHRAE 90.1) • Detailed HVAC modelling adopting IES ApacheHVAC • Net-Zero and Decarbonisation modelling for strategic solutions and compliance (e.g. SFT NZPSB Standard) • Part O strategy support & compliance modelling • Daylight modelling for Planning Assessments • CFD for Data Centres/External Comfort/Pollutant Dispersal