MARGINAL EMISSIONS RATES IN ENERGY SYSTEM CHANGE

Dr A.D. Hawkes

Principal Consultant in Modelling, AEA

Visiting Fellow, Imperial College London

The 2050 target

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UK CO2 Emissions

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Electricity Emissions Intensity

Residential Sector Heating

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Demand Response

District Heating

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CO2 Reduction Performance

Which demand-side technology?

How much CO2 will it save?

Which “baseline” technology will it displace?

Where there is an interaction with the electricity system, how much CO2 will be saved/produced for every kWh saved/used?

What about interactions with other parts of the energy system –primary resource choice, sectoral focus of emissions reduction, etc?

The usual method Choose a baseline system E.g. For heating in the UK; the combustion of natural gas in a condensing boiler

Figure out how much of each “energy carrier” the alternative system saves/produces (relative to the consumption/production of the baseline). E.g. A CHP system may consume an additional 3000kWh of gas/year, and

produce an additional 2500kWh of electricity

Multiply change in consumption for each energy carrier by the respective standard emissions rates; ~0.19kgCO2/kWh for gas, and 0.43kgCO2/kWh for electricity in the UK E.g. Change in CO2 = 0.19*3000 – 0.43*2500 = -1075kg CO2

An alternative method - marginal CO2 rates

The CO2 actually saved due to a change in electricity demand is

related to which power stations actually respond to that change.

The observed response of generators in GB

ELEXON publishes pre-gate closure dispatch data for every “BM unit” in the GB system

We know which generators these are, and their efficiency, so we can calculate the CO2 production rate change associated with a change in output

We can do this for every generator, so we can find the aggregate change in CO2 produced in any ½ hour period, along with the change in aggregate system load

We can create a scatter plot of these

We can create a linear fit (through zero)

The slope of the linear fit is an estimate of the marginal emissions rate for the system

GB Electricity Marginal Emissions2002 to 2009 inclusive

Source: Hawkes, A.D. (2010) Estimating Marginal Emissions Rates in National Electricity Systems. Energy Policy 38(10) 5977-5987.

doi:10.1016/j.enpol.2010.05.053

Change in System Load (GWh/h)

Ch

an

ge

in

Syste

m C

O2

Ra

te (

ktC

O2/h

)

Linear Fit: y = 0.69 x

Stats of the MEF

Change in System Load (GWh/h) GB System Load (GW) Change in System Load (GWh/h)

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ktC

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)

Ma

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al E

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acto

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gC

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f S

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m L

oa

d

y = 0.69 x

Change over time

Decommissioning and commissioning of power stations.

We know which “BM Units” will be decommissioned out to

~2020. National Grid also projects the types of new

generators over the same period.

We can replace the old with the new, and repeat the marginal

emissions calculation.

Resulting in...

Time Period Marginal Emissions Rate

(kgCO2/kWh)

2002-2009 0.69 kgCO2/kWh

2016 0.6 kgCO2/kWh

2020-2025 0.51 kgCO2/kWh

What does this mean? The actual marginal emissions rate from 2002-2009 was 60%

higher than the figure typically used in policy analysis.

But...

What about changes elsewhere in the energy system, and

over a much longer timeframe?

=> Analysis using the UK MARKAL Model

MARKAL (Market Allocation) chooses the least cost pathway for

energy system change over a 50 year time horizon. It is an

optimisation model, with objective function of discounted

system cost, user-defined constraints, and thousands of decision

variables.

MARKAL Analysis Method Constrain the introduction of micro-CHP and heat pumps

into the energy system

Zero to 10,000,000 installations, in 1,000,000 increments

Run MARKAL, record change in total system CO2 emissions over the entire time horizon

Calculate the abatement associated with the introduction of each system (i.e. CO2 reduction per system per year)

Allow all other aspects of the energy system to respond dynamically to the “forced” introduction of the intervention

MARKAL Analysis Results

Conclusion

From 2002-2009, the marginal CO2 intensity of grid

electricity in Great Britain was 0.69 kgCO2/kWh.

But the long term CO2 reduction brought about by a class of

interventions is more reliant on long term system changes

than short term....but MARKAL is a crude tool for such

analyses, and more research would be required to make firm

conclusions.

A stronger link between demand-side modelling and system

modelling is required to assess this situation more accurately.

Key Challenge: which margin?

A hypothetical situation:

1. We adopt a new technology (e.g. an electric car)

2. This technology causes an increase in peak system load (i.e. it

has negative capacity credit).

3. THEREFORE => the electric car is responsible for all the

emissions increase/decrease associated with that power

station. This is the BUILD MARGIN PERSPECTIVE.

4. BUT, when we actually charge the car, it is not the new

power station that responds to this demand.

5. THEREFORE, the operational marginal emissions rate is

appropriate. This is the OPERATING MARGIN

PERSPECTIVE.