ESAIM: Proceedings and Surveys (Jan 2019)

Regression Monte Carlo for microgrid management

  • Alasseur Clemence,
  • Balata Alessandro,
  • Ben Aziza Sahar,
  • Maheshwari Aditya,
  • Tankov Peter,
  • Warin Xavier

DOI
https://doi.org/10.1051/proc/201965046
Journal volume & issue
Vol. 65
pp. 46 – 67

Abstract

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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 [14] 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.