Probabilistic methods for energy transition (n. P20224TM7Z)
Type
PRIN 2022 PNRR, D.D. n. 1409 del 14 settembre 2022
CUP
C53D23008390001
Principal Investigator
Luciano Campi (Università degli Studi di Milano)
Other research units
UO1 - Luciano CAMPI - Università degli Studi di MILANO
UO 2 - Tiziano VARGIOLU - Università degli Studi di PADOVA
UO 3 - Tiziano DE ANGELIS - Università degli Studi di TORINO
UO4 - Athena PICARELLI - Università degli Studi di VERONA
Duration
30/11/2023 - 28/02/2026
Description
Building a climate-neutral, green, fair and social Europe is one of the four current priorities for the strategic agenda for the European
Union (EU). This is also present in one of the six priorities of "A European Green Deal", with the aim of making Europe carbon-neutral
by 2050. To reach this very ambitious aim, various actions should take place, like the decommissioning of fossil-based power plants
in favor of renewable energy sources (RES) and the massive introduction of energy storage facilities, to capture electricity produced
by RES and use it when these sources are not available. In order for this process to remain resource-efficient and economically
competitive, one has to determine, for each possible initiative, its expected future costs and benefits, to assess the global
sustainability of this strategy. Mathematically, this typically translates into stochastic control and optimization problems, like e.g.
optimal operation of power plants and/or storages and irreversible installation of RES, which are also useful to assess the
effectiveness of various market mechanisms which are introduced into electricity market in order to facilitate this transition.
Moreover, many relevant problems central to energy transition are typically decentralized. For this reason, the related mathematical
problems are naturally formulated in a multi-agent setting, possibly with a very large number of agents.
Besides the obvious involvement of member states, public regulatory agencies and leading energy producing industries, a key role
of this energy transition will be played by the final consumers, who should be persuaded or pushed to change old habits, based on
the existing fossil-fueled energy system, in favor of new habits: this could entail e.g. the adjustment of energy-consuming behaviors,
the installation of individual RES-based assets (like photovoltaic panels on their roofs, or electricity storages) or the switch to electric
cars. Persuading final consumers and the general public to be more aware of climate change challenges and to have more
energy-efficient behavior can be achieved via Bayesian persuasion, which is a set of modeling and mathematical tools which help to
design optimal ways to release information to induce change in people habits and reduce negative externalities.
We aim to address these challenges using a large range of probabilistic techniques spanning stochastic control, filtering theory,
games for finitely many players and games for a large population of players, such as mean field games, and cutting edge numerical
methods based on neural networks. We plan to do so through three main working packages (WPs):
WP1: Bayesian persuasion for energy transition;
WP2: Optimal management of RES;
WP3: Mean field control problems and games for energy transition.
The objectives of these WPs together with their specific relevance for energy transition will be described in detail in the part B2 of
this project.
