Achieving the decarbonisation objectives by 2030 places the focus on the high penetration of renewable sources, on the entry of new technologies and on a greater and greater integration between the electricity and gas sectors. This report contains descriptions of the mathematical models, new or updated ones developed by RSE, for the simulation of energy markets and integrated energy systems to support analyses of their evolution and operation.

Firstly, the Italian capacity market was analysed. The uncertainty of renewable sources, in fact, poses the problem of being able to satisfy demand for every hour of the year, i.e., of having an adequate electricity system.

For these reasons, in Italy, as in other European countries, a capacity mechanism for the remuneration of electricity generation capacity has been introduced to ensure that market players keep in efficient operation the necessary existing plants and to build new ones, if needed. It is therefore interesting to analyze, from a modeling perspective, the demand and supply curves of the Italian capacity market considered by Terna since 2019, in order to simulate the curves for the delivery year 2025. The intersection of the two curves allows identifying the adequacy state of the electrical system achieved through the estimated offers for 2025.

Subsequently, the developments made to the integrated RSE simulator are illustrated. In fact, the strong integration between the electrical and gas systems requires to focus the attention on models capable of realistically representing the synergy between different energy vectors.

In order to further explore these synergies between energy sectors, two areas of development have been identified: CO2 capture and storage and methanation processes on one side, and district heating and cooling networks on the other side. These elements have been incorporated into the integrated gas-electric simulator previously developed by RSE to provide greater capabilities for future analyses.

Furthermore, another relevant aspect in the modeling field is the ability to correctly simulate the bidding strategies of players participating in the dispatching services market, especially concerning scenario simulations. The goal has been achieved by initially gathering statistical information to be subsequently applied. Furthermore, the complexity of relationships between historical data has led to the choice of using a neural network to better implement this complexity in bid construction.

Finally, to facilitate the development of models, a study has also been initiated for downloading data from public platforms. The first procedure for downloading data from the ENTSO-E platform is presented.

The document is available on the site in Italian