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A fully backward representation of semilinear PDEs applied to the control of thermostatic loads in power systems

Abstract : We propose a fully backward representation of semilinear PDEs with application to stochastic control. Based on this, we develop a fully backward Monte-Carlo scheme allowing to generate the regression grid, backwardly in time, as the value function is computed. This offers two key advantages in terms of computational efficiency and memory. First, the grid is generated adaptively in the areas of interest and second, there is no need to store the entire grid. The performances of this technique are compared in simulations to the traditional Monte-Carlo forward-backward approach on a control problem of thermostatic loads.
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Preprints, Working Papers, ...
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https://hal.archives-ouvertes.fr/hal-03210302
Contributor : Francesco Russo Connect in order to contact the contributor
Submitted on : Monday, September 27, 2021 - 10:40:45 AM
Last modification on : Friday, December 3, 2021 - 11:34:11 AM

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  • HAL Id : hal-03210302, version 2
  • ARXIV : 2104.13641

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Lucas Izydorczyk, Nadia Oudjane, Francesco Russo. A fully backward representation of semilinear PDEs applied to the control of thermostatic loads in power systems. 2021. ⟨hal-03210302v2⟩

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