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We were seeing too high capacity_factors for Offwind with weather year 2013 (still testing for 2019). That's probably due to too high wind speeds from atlite. They should be corrected by a scaling factor.
We already implemented a scaling for wake effects in wind parks. As a consequence the maximum power output of windfarms is reduced to 88.5% of their nominal capacity. This way we will probably see less grid expansion.
Adding another sacling of the capacity to account for overestimated wind speeds would lead to even less maximum output and even less grid expansion.
Therefore we should scale the windspeeds directly in atlite.
In the latest 3H run (Elec scenario) we get the following trajectory for the CF:
offwind-dc
0.34726276283057
0.507773415011066
0.518321418111682
0.518621713244829
0.511528488497239
0.511420904408977
That's still on the high side. I wonder why we see the jump between 2020 and 2025.
Relatedly, there is still #161. It has been mostly adressed by #171 but the scaling for the wake effects remains active and leads to an underestimation of the required grid capacity.
So:
High Priority: Find out why capacity factors are high in 2025-2045
We were seeing too high capacity_factors for Offwind with weather year 2013 (still testing for 2019). That's probably due to too high wind speeds from atlite. They should be corrected by a scaling factor.
We already implemented a scaling for wake effects in wind parks. As a consequence the maximum power output of windfarms is reduced to 88.5% of their nominal capacity. This way we will probably see less grid expansion.
Adding another sacling of the capacity to account for overestimated wind speeds would lead to even less maximum output and even less grid expansion.
Therefore we should scale the windspeeds directly in atlite.
This has been discussed in PyPSA/pypsa-eur#153 as well
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