The reason the "Bonus Round" does not match the actual KPIs is because:
1) There is a trade off between Wind Capacity, Solar Capacity and Storage Capacity. Each combination results in a different Capex vs FCOE value.
2) For my "Bonus Round" I choose the optimum values for Capex vs. FCOR.
3) Obviously, the "Actual" Data is not going to match this optimum value as Capacities are growing at different rates.
Grid operators should be managing the BLEND of Wind, Solar & Storage to optimize economics. But of course, they can not do this as each generator project is based on economics for THAT project.
I agree that the optimum LOW-Carbon is probably around 80% and definitely not higher than 90%. That of course depends on if your objective is to reduce consumer costs or to reduce CO2e emissions!
Another approach is to calculate the amount of storage required to cope with the worst case scenario for the supply of wind - the fundamental input to the wind power system.
The worst case scenario is a series of nights in close succession with little or no wind. In Australia the longest run of low wind nights is three but there are months with up to 10.
Then there is the problem iofcharging the batteries, or the pumped hydro system. Currently the batteries are charged while prices are negative and they feed into the grid during the evening peak. However to ride through windless nights the charge can only accumulate day on day when there is enough wind and solar in the system to deliver a surplus almost every day.
My colleague John McBratney has explained that the charging problem, in a grid without a considerable amount of dispatchable power, is insurmountable.
Rafe... Everything I do is based firmly on real-time data from the grid in question. That means that I capture wind lulls as well as rainy days, etc. for solar. I use a complex grid model to determine the amount of storage and wind/solar capacity needed.
Hi Bill,
Interesting read.
I think your 'bonus round' should inform your earlier KPIs.
Aiming for 100% 'renewable' power hits the 'diminishing returns' buffers.
So I think the solution will require a compromise between the absolutists and the pragmatists.
Maybe somewhere around 80% would be my guess, but greatly depending on the total installed cost of energy storage and how that develops.
The reason the "Bonus Round" does not match the actual KPIs is because:
1) There is a trade off between Wind Capacity, Solar Capacity and Storage Capacity. Each combination results in a different Capex vs FCOE value.
2) For my "Bonus Round" I choose the optimum values for Capex vs. FCOR.
3) Obviously, the "Actual" Data is not going to match this optimum value as Capacities are growing at different rates.
Grid operators should be managing the BLEND of Wind, Solar & Storage to optimize economics. But of course, they can not do this as each generator project is based on economics for THAT project.
I agree that the optimum LOW-Carbon is probably around 80% and definitely not higher than 90%. That of course depends on if your objective is to reduce consumer costs or to reduce CO2e emissions!
Another approach is to calculate the amount of storage required to cope with the worst case scenario for the supply of wind - the fundamental input to the wind power system.
The worst case scenario is a series of nights in close succession with little or no wind. In Australia the longest run of low wind nights is three but there are months with up to 10.
Then there is the problem iofcharging the batteries, or the pumped hydro system. Currently the batteries are charged while prices are negative and they feed into the grid during the evening peak. However to ride through windless nights the charge can only accumulate day on day when there is enough wind and solar in the system to deliver a surplus almost every day.
My colleague John McBratney has explained that the charging problem, in a grid without a considerable amount of dispatchable power, is insurmountable.
https://rafechampion.substack.com/p/grid-scale-electricity-storage-why
Rafe... Everything I do is based firmly on real-time data from the grid in question. That means that I capture wind lulls as well as rainy days, etc. for solar. I use a complex grid model to determine the amount of storage and wind/solar capacity needed.