Volume 65, 2019CEMRACS 2017 - Numerical methods for stochastic models: control, uncertainty quantification, mean-field
|Page(s)||46 - 67|
|Published online||02 April 2019|
Regression Monte Carlo for microgrid management
EDF R&D - FIME, Palaiseau, France
2 University of Leeds, Woodhouse Lane, Leeds LS2 9JT, United Kingdom
3 University of Tunis El Manar,ENIT-LAMSIN, BP.37, Le Belvédère 1002 Tunis, Tunisia
4 University of California, Santa Barbara, USA
5 CREST-ENSAE, Palaiseau, France
6 EDF R&D - FIME, Palaiseau, France
We study an islanded microgrid system designed to supply a small village with the power produced by photovoltaic panels, wind turbines and a diesel generator. A battery storage system device is used to shift power from times of high renewable production to times of high demand. We build on the mathematical model introduced in  and optimize the diesel consumption under a “no-blackout” constraint. We introduce a methodology to solve microgrid management problem using different variants of Regression Monte Carlo algorithms and use numerical simulations to infer results about the optimal design of the grid.
© EDP Sciences, SMAI 2019
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