National Carbon Intensity Forecast

This dataset contains national carbon intensity forecast for the GB electricity system. The carbon intensity of electricity is a measure of how much CO2 emissions are produced per kilowatt hour of electricity consumed. <br/><br/>


Publicly Available 
 
1 
 
Authors: Dr Alasdair R. W. Bruce, Lyndon Ruffa, James Kelloway, Fraser MacMillan, Prof Alex Rogersb 
a St. Catherine’s Lodge, Wokingham, NESO, b Department of Computer Science, University of Oxford 
Issue: May 2024 
 
National Energy System Operator (NESO), in partnership with Environmental Defense 
Fund Europe and WWF, has developed a series of Regional Carbon Intensity forecasts for 
the GB electricity system, with weather data provided by the Met Office. 
Introduction 
NESO’s Carbon Intensity API provides an 
indicative trend of carbon intensity for the electrical 
grid of Great Britain up to 48 hours ahead of real-
time [1]. It provides programmatic and timely 
access to forecast carbon intensity. This report 
details the methodology behind the regional 
carbon intensity estimates. For more information 
about the Carbon Intensity API see here. 
What’s included in the forecast 
The Regional Carbon Intensity forecasts include 
CO2 emissions related to electricity generation 
only. The forecasts include CO2 emissions from all 
large metered power stations, interconnector 
imports, transmission and distribution losses, and 
accounts for national electricity demand, and both 
regional embedded wind and solar generation. 
While we recognise upstream emissions and 
indirect land use change impacts and other GHG 
emissions are important, it is only CO2 emissions 
related to electricity generation that are included in 
the forecast. This work does not consider the CO2 
emissions of unmetered and embedded 
generators for which NESO does not have visibility 
of. 
Methodology 
The Carbon Intensity forecast is particularly 
sensitive to short-term forecast errors in demand, 
wind and solar generation, as this impacts the 
amount of dispatchable generation that is required 
to meet demand. 
The forecast also makes use of historic generation 
data to make predictions about future generation, 
which invariably changes per system conditions. It 
is therefore important to note that these forecasts 
are likely to be less accurate than forecasts such 
as electricity demand, since it includes the 
confluence of uncertainties from demand, wind, 
solar, and CO2 emissions by fuel type. 
Estimated carbon intensity data is provided at the 
end of each half hour settlement period. Forecast 
carbon intensity is provided 48 hours ahead of 
real-time for each half hour settlement period and 
uses NESO’s latest forecasts for national demand, 
wind and solar generation. 
The GB carbon intensity 𝐶𝑡 at time 𝑡 is found by 
weighting the carbon intensity 𝑐𝑔 for fuel type 𝑔 by 
the generation 𝑃𝑔,𝑡 of that fuel type. This is then 
divided by national demand 𝐷𝑡 to give the carbon 
intensity for GB: 
 
𝐶𝑡= 
∑
𝑃𝑔,𝑡 × 𝐶𝑔 
𝐺
𝑔=1
𝐷𝑡
 
 
The carbon intensity is then corrected to account 
for transmission losses to give the intensity of 
Carbon Intensity 
Forecast Methodology 

 
 
 
 
Publicly Available 
 
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consumption [3]. Table 1 shows the peer-reviewed 
carbon intensity factors of GB fuel types used in 
this methodology. Carbon intensity factors are 
based on the output-weight average efficiency of 
generation in GB and DUKES CO2 emission 
factors for fuels [4]. 
Interconnector carbon intensity factors 
Daily at 6am, the average generation mix of each 
network the GB grid is connected to through 
interconnectors is collected for the previous 24 
hours through the ENTSO-E Transparency 
Platform API [6].  
The factors from Table 1 are applied to each 
technology type for each import generation mix to 
calculate the import carbon intensity factors. If the 
ENTSO-E API is down, the import carbon factors 
default to those listed in Table 1.  
Fuel Type 
Carbon Intensity 
gCO2/kWh 
Biomassi 
120 
Coal 
937 
Gas (Combined Cycle) 
394 
Gas (Open Cycle) 
651 
Hydro 
0 
Nuclear 
0 
Oil 
935 
Other 
300 
Solar 
0 
Wind 
0 
Pumped Storage 
0 
French Imports 
~ 53 
Dutch Imports 
~ 474 
Belgium Imports 
~ 179 
Irish Imports 
~ 458 
 
The estimated carbon intensity uses metered data 
for each fuel type, which is also available from 
ELEXON via the Balancing Mechanism Reporting 
Service, and includes fuel types such as metered 
wind, nuclear, combined cycle gas turbines, coal 
etc. Estimated data is used for embedded wind 
and solar generation.  
Weather data, such as wind speeds and solar 
radiation, are procured separately by NESO and 
so are not publicly available. A rolling-window 
linear regression for each fuel type is performed 
and used with forecast demand, wind, and solar 
data to estimate forecast carbon intensity. 
An index for carbon intensity has been developed 
to illustrate times when the carbon intensity of GB 
system is high/low. Table 2 (overleaf) shows the 
num

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