Step by step scenario building
The scenario building process is a process that involves market models (such as BID, Plexos, Powersym, Antares, ETC) and calculation algorithms developed by ENTSO-E.
In the example below the methodology is described step by step from 2030 Sustainable transition as the starting scenario.
Figure 14 Scenario building flow for deriving top down scenarios.
Step 1: Apply rules for scenario
ENTSO-E modelling team considers each scenario storylines and proceeds with the first data processing. They deliver for each country and according to rules defined in the storylines (based on data provided by TSOs and on targets depending on the type of scenario):
the yearly load
the number of Electric Vehicles and heat pumps
hourly load profiles corresponding to the determined level of heat pumps and electric vehicles
installed capacity for wind and solar
updated list of power plants
the level of power storage per country.
Step 2: Run Market model and check
Thanks to the expertise of its Members TSOs, ENTSO-E is uniquely able to use the computational power of up to 6 different commercially available market modelling tools. Modelling future systems with a high level of uncertainty is indeed a precise but inexact science. The specific strength of each of the tool gives considerable room to ENTSO-E experts to consolidate the results of the scenarios.
In this step, the market modelling tools are ran and results are checked for errors as well as for Energy not Served (when the generation and grid are unable to meet the demand in a zone). Peaking units are added to the nodes with too little production to prevent these situations from happening. This is a temporary step in the scenario building process to ensure that there is no ENS during the RES-optimisation phase. The peaking units are removed before thermal optimization.
Step 3: RES optimisation
The purpose of the RES-optimisation phase is to distribute the photovoltaic, onshore and offshore wind generation between the different zones through a market based solution. The iterative process ensures that an efficient utilization of renewable energy is achieved at an EU level rather than a national level. The pricing information from market models linked to external optimization algorithms enable renewable capacities to be spread efficiently between market zones. RES optimization also uses boundary conditions for lower and upper RES penetration per market zone.
During RES optimisation a stronger grid is used in order to drive a higher share of RES in areas with good conditions for RES.
Step 4: Thermal Optimisation
Thermal optimisation is another iterative process involving the market model and external market analysis algorithms. The output from the market models are passed through a CAPEX and fixed cost profitability algorithm, which provides indication on what power plants are not economically viable. A second phase in the process evaluates whether new power plants according to the scenario investment costs are viable. Temporary peaking units are included at the beginning of the process to ensure adequacy. The methodology does not consider retrofitting or fuel switch of existing power plants.
Step 5: Check and finish Optimisation
Run model and check for errors and check that the overall RES-target and climate targets for the scenario is reached. After this the scenario is done and the scenario data is output to the required database format.