Use different curves to assess the sensitivity of outcomes on the dataset about merit HOT 4 CLOSED

The curves described above for wind (coastal, inland and offshore), solar and demand have been used to calculate full load hours and production for all merit order participants.
The differences between production (PJ) of 2009/2010 and 200/2011 curves have been expressed as a fraction (e.g., fractional_difference = ABS(2009 - 2010) / 2009).

See /Dropbox/Merit order/Part Two (EnergieNederland)/Data/Testing/DifferentCurves/overview.xlsx for details. A snapshot of this Excel sheet is shown below:

As can be seen from the analysis, the energy_power_combined_cycle_gas_power_fuelmix is the primary producer (22% of the total) and shows up to 6% difference in production when comparing 2009 to 2011. This difference results from the fact that this producer is often the price-setting producer and thus sensitive to stochasticity in the demand and volatile curves.

Larger (fractional!) deviations occur for plants with fewer full load hours and thus less production. Their impact is therefore also less important.

My preliminary conclusion is that the results of the MO module seem to be robust against exchanging load profiles.

from merit.

@AlexanderWirtz @JAlsem @dennisschoenmakers please have a look at the analysis and let me know if you would like to know more...

from merit.

Looks okay to me. We could also add more yearly load profiles for technologies to Merit, and then let the user choose which year to use, e.g.

Merit::Order.new(2009)

But I don't think that's worth the effort for now.

from merit.

Closing.

from merit.