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The Alternative Green Energy Thread
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This may help as it is a live map including interconnectors.
electricityMap | Live CO₂ emissions of electricity consumption
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Estimating the marginal carbon intensity of electricity with machine learning
As a consumer, when you decide to charge your electric vehicle at a given time, you are causing the marginal plant to produce more, and therefore, are responsible for the carbon emissions associated to it. Those emissions are called marginal carbon emissions. It is the quantity that should guide our choice as flexible consumers. For example, it is better to charge your electric vehicle when a hydro dam provides the additional electricity, compared to when a gas turbines does (as the latter has much higher emissions).
Traditionally, marginal carbon emissions were calculated using assumptions on what kind of generation would be marginal at a given time. However, we’d like to present an alternative: Instead of assuming what kind of generation is marginal, this article is about how we use machine learning to estimate the marginal origin of electricity, and thereafter deduct the associated carbon emissions.
Here’s how, on average, each area generates its marginal electricity:
and here are the associated emissions of generating an extra unit of electricity:
Interestingly while we have lower average emissions than Germany our marginal electricity production produces much higher emissions at over 500gCO2\kWh. It could be argued therefore that it creates more emissions to plug in and charge an EV here than in Germany despite our grid normally being twice as clean.Northern Lincolnshire. 7.8 kWp system, (4.2 kw west facing panels , 3.6 kw east facing), Solis inverters, Solar IBoost water heater, Mitsubishi SRK35ZS-S and SRK20ZS-S Wall Mounted Inverter Heat Pumps, ex Nissan Leaf owner)0 -
gefnew said:This may help as it is a live map including interconnectors.
electricityMap | Live CO₂ emissions of electricity consumptionNorthern Lincolnshire. 7.8 kWp system, (4.2 kw west facing panels , 3.6 kw east facing), Solis inverters, Solar IBoost water heater, Mitsubishi SRK35ZS-S and SRK20ZS-S Wall Mounted Inverter Heat Pumps, ex Nissan Leaf owner)1 -
JKenH said:
Estimating the marginal carbon intensity of electricity with machine learning
As a consumer, when you decide to charge your electric vehicle at a given time, you are causing the marginal plant to produce more, and therefore, are responsible for the carbon emissions associated to it. Those emissions are called marginal carbon emissions. It is the quantity that should guide our choice as flexible consumers. For example, it is better to charge your electric vehicle when a hydro dam provides the additional electricity, compared to when a gas turbines does (as the latter has much higher emissions).
Traditionally, marginal carbon emissions were calculated using assumptions on what kind of generation would be marginal at a given time. However, we’d like to present an alternative: Instead of assuming what kind of generation is marginal, this article is about how we use machine learning to estimate the marginal origin of electricity, and thereafter deduct the associated carbon emissions.
Here’s how, on average, each area generates its marginal electricity:
and here are the associated emissions of generating an extra unit of electricity:
Interestingly while we have lower average emissions than Germany our marginal electricity production produces much higher emissions at over 500gCO2\kWh. It could be argued therefore that it creates more emissions to plug in and charge an EV here than in Germany despite our grid normally being twice as clean.
8kW (4kW WNW, 4kW SSE) 6kW inverter. 6.5kWh battery.0 -
If you are charging your EV then switch on the kettle for a cup of tea does the EV stop using marginal electricity and instead the kettle does so?
I'm afraid I can't see the merit in this argument.I think....1 -
ABrass said:JKenH said:
Estimating the marginal carbon intensity of electricity with machine learning
As a consumer, when you decide to charge your electric vehicle at a given time, you are causing the marginal plant to produce more, and therefore, are responsible for the carbon emissions associated to it. Those emissions are called marginal carbon emissions. It is the quantity that should guide our choice as flexible consumers. For example, it is better to charge your electric vehicle when a hydro dam provides the additional electricity, compared to when a gas turbines does (as the latter has much higher emissions).
Traditionally, marginal carbon emissions were calculated using assumptions on what kind of generation would be marginal at a given time. However, we’d like to present an alternative: Instead of assuming what kind of generation is marginal, this article is about how we use machine learning to estimate the marginal origin of electricity, and thereafter deduct the associated carbon emissions.
Here’s how, on average, each area generates its marginal electricity:
and here are the associated emissions of generating an extra unit of electricity:
Interestingly while we have lower average emissions than Germany our marginal electricity production produces much higher emissions at over 500gCO2\kWh. It could be argued therefore that it creates more emissions to plug in and charge an EV here than in Germany despite our grid normally being twice as clean.We will get more renewable electricity as time goes by but until we have several times more we will still have to meet any additional load from gas.Northern Lincolnshire. 7.8 kWp system, (4.2 kw west facing panels , 3.6 kw east facing), Solis inverters, Solar IBoost water heater, Mitsubishi SRK35ZS-S and SRK20ZS-S Wall Mounted Inverter Heat Pumps, ex Nissan Leaf owner)0 -
JKenH said:ABrass said:JKenH said:
Estimating the marginal carbon intensity of electricity with machine learning
As a consumer, when you decide to charge your electric vehicle at a given time, you are causing the marginal plant to produce more, and therefore, are responsible for the carbon emissions associated to it. Those emissions are called marginal carbon emissions. It is the quantity that should guide our choice as flexible consumers. For example, it is better to charge your electric vehicle when a hydro dam provides the additional electricity, compared to when a gas turbines does (as the latter has much higher emissions).
Traditionally, marginal carbon emissions were calculated using assumptions on what kind of generation would be marginal at a given time. However, we’d like to present an alternative: Instead of assuming what kind of generation is marginal, this article is about how we use machine learning to estimate the marginal origin of electricity, and thereafter deduct the associated carbon emissions.
Here’s how, on average, each area generates its marginal electricity:
and here are the associated emissions of generating an extra unit of electricity:
Interestingly while we have lower average emissions than Germany our marginal electricity production produces much higher emissions at over 500gCO2\kWh. It could be argued therefore that it creates more emissions to plug in and charge an EV here than in Germany despite our grid normally being twice as clean.We will get more renewable electricity as time goes by but until we have several times more we will still have to meet any additional load from gas.
The marginal effect analysis doesn't make sense in a system that's inherently dynamic and that has a constantly changing makeup.
Just for interest, are we adding more Solar power generation to the grid than we are electric vehicle demand?
The closest sensible measure would be to look at the change in power over a year and see if the total has gone up or down, and the fraction that came from Gas or renewables.8kW (4kW WNW, 4kW SSE) 6kW inverter. 6.5kWh battery.1 -
AsABrass said:JKenH said:ABrass said:JKenH said:
Estimating the marginal carbon intensity of electricity with machine learning
As a consumer, when you decide to charge your electric vehicle at a given time, you are causing the marginal plant to produce more, and therefore, are responsible for the carbon emissions associated to it. Those emissions are called marginal carbon emissions. It is the quantity that should guide our choice as flexible consumers. For example, it is better to charge your electric vehicle when a hydro dam provides the additional electricity, compared to when a gas turbines does (as the latter has much higher emissions).
Traditionally, marginal carbon emissions were calculated using assumptions on what kind of generation would be marginal at a given time. However, we’d like to present an alternative: Instead of assuming what kind of generation is marginal, this article is about how we use machine learning to estimate the marginal origin of electricity, and thereafter deduct the associated carbon emissions.
Here’s how, on average, each area generates its marginal electricity:
and here are the associated emissions of generating an extra unit of electricity:
Interestingly while we have lower average emissions than Germany our marginal electricity production produces much higher emissions at over 500gCO2\kWh. It could be argued therefore that it creates more emissions to plug in and charge an EV here than in Germany despite our grid normally being twice as clean.We will get more renewable electricity as time goes by but until we have several times more we will still have to meet any additional load from gas.
The marginal effect analysis doesn't make sense in a system that's inherently dynamic and that has a constantly changing makeup.
Just for interest, are we adding more Solar power generation to the grid than we are electric vehicle demand?
The closest sensible measure would be to look at the change in power over a year and see if the total has gone up or down, and the fraction that came from Gas or renewables.Northern Lincolnshire. 7.8 kWp system, (4.2 kw west facing panels , 3.6 kw east facing), Solis inverters, Solar IBoost water heater, Mitsubishi SRK35ZS-S and SRK20ZS-S Wall Mounted Inverter Heat Pumps, ex Nissan Leaf owner)0 -
michaels said:If you are charging your EV then switch on the kettle for a cup of tea does the EV stop using marginal electricity and instead the kettle does so?
I'm afraid I can't see the merit in this argument.Northern Lincolnshire. 7.8 kWp system, (4.2 kw west facing panels , 3.6 kw east facing), Solis inverters, Solar IBoost water heater, Mitsubishi SRK35ZS-S and SRK20ZS-S Wall Mounted Inverter Heat Pumps, ex Nissan Leaf owner)0 -
ABrass said:Just for interest, are we adding more Solar power generation to the grid than we are electric vehicle demand?A BEV travelling 10000 miles/yr at 0.25kWh/mile will need 2500kWh.The pending round of CfD auctions will be for approx. 10GW of renewable generation, mostly wind. Wind is delivering something like a 47% capacity factor over the year (link but a bit out of date), so that 10GW will deliver 40TWh per year, enough to fuel 16 million BEVs.Based on that I think we're adding renewable capacity faster than we're buying BEVs.N. Hampshire, he/him. Octopus Intelligent Go elec & Tracker gas / Vodafone BB / iD mobile. Ripple Kirk Hill member.
2.72kWp PV facing SSW installed Jan 2012. 11 x 247w panels, 3.6kw inverter. 34 MWh generated, long-term average 2.6 Os.Not exactly back from my break, but dipping in and out of the forum.Ofgem cap table, Ofgem cap explainer. Economy 7 cap explainer. Gas vs E7 vs peak elec heating costs, Best kettle!1
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