Validation

Validation#

The PyPSA-Eur model workflow has been validated by contrasting the outcomes of network optimization against the historical behaviour of the European power system. These comparisons utilize data from the 2019 ENTSO-E Transparency Platform. The setup uses monthly varying fuel prices for gas, lignite, coal and oil as well as CO2 prices, which are created by the script build_monthly_prices.

The comparison with the historical data shows partially accurate, partially improvable results. The following figures show the comparison of the dispatch of the different carriers.

_images/validation_seasonal_operation_area_elec_s_37_ec_lv1.0_Ept.png _images/validation_production_bar_elec_s_37_ec_lv1.0_Ept.png

Issues and possible improvements#

Overestimated dispatch of wind and solar: Renewable potentials of wind and solar are slightly overestimated in the model. This leads to a higher dispatch of these carriers than in the historical data. In particular, the solar dispatch during winter is overestimated.

Coal - Lignite fuel switch: The model has a fuel switch from coal to lignite. This might result from non-captured subsidies for lignite and coal in the model. In order to fix the fuel switch from coal to lignite, a manual cost correction was added to the script build_monthly_prices.

Planned outages of nuclear power plants: Planned outages of nuclear power plants are not captured in the model. This leads to a underestimated dispatch of nuclear power plants in winter and a overestimated dispatch in summer. This point is hard to fix, since the planned outages are not published in the ENTSO-E Transparency Platform.

False classification of run-of-river power plants: Some run-of-river power plants are classified as hydro power plants in the model. This leads to a general overestimation of the hydro power dispatch. In particular, Swedish hydro power plants are overestimated.

Load shedding: Due to constraint NTC’s (crossborder capacities), the model has to shed load in some regions. This leads to a high market prices in the regions which drive the average market price up. Further fine-tuning of the NTC’s is needed to avoid load shedding.