Presentation title
Parallel Statistical Model Checking for Safety Verification in Smart GridsAuthors
Toni Mancini, Igor Melatti and Enrico TronciInstitution(s)
Sapienza University of RomePresentation type
Presentation of a research group from one or more scientific institutionsAbstract
In modern smart electric grids, stakeholders have to counteract the problem of peaks in power demand caused by the users connected to a single substation (feeder). If such peaks are over a given threshold, the substation safety is violated and this might cause service and/or infrastructure disruption.
An increasingly popular approach for electricity distribution operators is to offer time-dependent tariffs (also known as price policies) to users, with the ultimate goal of inducing a change in their behaviour into power profiles compatible with the grid safety constraints. In particular, when subject to time-dependent tariffs, it is expected that users will manage (at least to some extent) their loads, by, e.g., shifting some of their power needs to lower-tariff time periods (load shifting). Unfortunately, although incentivised by lower tariffs, there is no guarantee that users will actually adhere to the power profiles envisioned for them by the electricity operator. As a consequence, the electric grid might be still at risk.
We present a software system allowing Distribution System Operators to compute a portfolio of KPIs over the probability distribution of the Aggregated Power Demand subject to probabilistic deviations of end-users from their predicted behaviours under the given price policies. This allows stakeholders to check, e.g., if the probability of violating the substation safety is kept sufficiently low. The feasibility of the approach and the scalability of the system have been tested by using a realistic scenario taken from an existing medium voltage Danish distribution network.