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Thursday, April 11, 2019
2:00 PM - 3:00 PM
CNLS Conference Room (TA-3, Bldg 1690)

Postdoc Seminar

Mean Field Control and Polynomial Chaos Expansion for compensating and estimating uncertainty in Renewable Energy generation

David Métivier
T-4/CNLS

Renewable Energy, such as provided by wind and sun, is a major novel source of generation. However, it is not reliable as coming inspikes. Having sufficient battery resources can help to mitigate the uncertainty, but even though battery technology has advanced significantly during the last decade, it is still very far from being able to level fluctuations even in a relatively small energy system (a small town, 100 MW scale) caused by the renewable sources. At the same time estimating how this uncertainty affects power grids is necessary to build reliable systems.

In this talk, divided into two distinct parts, we discuss a possibility to compensate the fluctuations by utilizing flexibility on theconsumption (as opposed to production) side of the energy system. We suggest to use a simple Mean Field Control ‘to build’ resilient VirtualBattery aggregating many small loads, like air-conditioners or other Thermostatically Controlled Loads.

The second part will be focused on Uncertainty Quantification in power grids via the Polynomial Chaos Expansion method that I will present. Wewill discuss the possibilities to use the sparsity of the problem to circumvent the curse of dimensionality that limits the method applicability.

Host: Tillmann Weisser