ENTSOG TYNDP 2017 - Main Report

Within the scenario storylines, there is a clear distinction between coal and gas merit orders, with gas before coal on a regulatory basis in the Blue Transition and Green scenarios. Due to the fuel and CO ² prices used in the ENTSO-E TYNDP 2016, this merit order may not have been reflected within the modelling. As a result ENTSOG has applied a methodology, the thermal gap approach, to help TSO’s use the data from ENTSO-E to determine the gas demand required for power generation (see Annex C4 for more details about this methodology). The implementation of this methodology requires a significant number of assump- tions, including electricity generation from alternative sources, the electricity exchange with neighbouring countries, assumptions regarding the usage of CHP (those facilities earn their money in both the heat and the electricity market) and limitations in the utilisation of coal and gas. These assumptions are based on the actual electricity mix, along with feedback from stakeholders and inputs from TSOs, reflecting the specific factors for each country.

GW

1,600 1,400 1,200 1,000

800 600 400 200

0

2015

2030 Vision 1

2030 Vision 3

2030 Vision 4

Nuclear

Solar

Wind

Hydro

Hydro – pump

Biofuel

Others – RES

Coal

Gas

Oil

Others – Non RES

Figure 2.22: Power generation installed capacities for Vision 1 (Slow Progression),

Vision 3 (Blue Transition) and Vision 4 (Green Evolution and EU Green Revolution). (Source: ENTSO-E)

Peak day and 2-week high demand cases  1)

There are different assumptions on the climatic dependence of the generation data between the defined probabilities of the high demand situations and those ones in the available information. ENTSO-E market modelling uses a specific climatic year, while the ENTSOG 2-week and peak day demand cases are representing 1-in-20 or national design case situations. Therefore adequate data was requested by gas TSOs during the data collection process. The peak gas consumption is expected on a day of high electricity demand for which the availability of variable sources is low. The gas consumption on a day when the availability of variable sources is high allows the estimation of the flexibility required from the gas system in order to compensate for variability.

 1) For more details on the definition of high demand cases and how they are considered in the assessment, please refer to Annex F: Methodology

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