NEW PROBABILISTIC TECHNIQUES FOR THE ANALYSIS OF ENERGY NETWORKS UNDER UNCERTAINTY

Tommaso Nesti, PhD student at CWI’s Stochastics group, has developed new mathematical techniques to help model, control and operate modern-day power grids in the presence of uncertainty.

Publication date: 03-04-2020

Tommaso Nesti, PhD student at CWI’s Stochastics group, has developed new mathematical techniques to help model, control and operate modern-day power grids in the presence of uncertainty, for example caused by the unpredictable supply and demand of renewable energy. The electricity transmission network is regarded as one of the greatest engineering achievements of the 20th century, and is expected to power day-to-day human activities in a reliable and seamless fashion. The advent of intermittent power generation from renewable sources is making this expectation challenging to live up to. The increased supply-side variability may lead to unexpected violations of stability constraints, which can cause the failure of grid components and potentially result in widespread blackouts.

Now, Tommaso Nesti has drawn on techniques from applied probability, such as large deviations theory and statistical learning, to develop uncertainty-aware stability conditions that make sure that disruptive events, such as transmission line failures, are rare. This will allow grid operators to identify which parts of the networks are most vulnerable to fluctuations in renewable supply, and help energy market participants to better predict fluctuations of energy prices, for example. Moreover, this research sheds new light on the nature of widespread blackouts, providing the first mathematical analysis linking a microscopic model of a power grid with a macroscopic phenomenon of blackouts, namely the scale-free nature of blackout size distributions.

Tommaso says: “The ongoing, desirable transition towards more renewable clean generation comes with many technical challenges, due to the intermittent nature of energy sources like wind and solar. In my thesis, I try to make the case that applied probability techniques, which have proved extremely valuable in the fields of telecommunication, engineering, and finance in the past, can and will play a major role in guiding this renewable energy transition.”

Tommaso defended his PhD thesis “Stochastic Analysis of Energy Networks” at the Eindhoven University of Technology (in an online fashion) on March 30th, 2020, and was awarded the 2020 Applied Probability Trust Prize for his thesis, an honor awarded to young researchers for outstanding scientific accomplishments.  Tommaso’s promoters are Bert Zwart (CWI and TU/e) and Alessandro Zocca (VU).