On incorporating forecasts into linear state space model Markov decision processes.

Philos Trans A Math Phys Eng Sci

Department of Management Sciences and Engineering, Stanford University, Stanford CA 94305-2205, USA.

Published: July 2021

Weather forecast information will very likely find increasing application in the control of future energy systems. In this paper, we introduce an augmented state space model formulation with linear dynamics, within which one can incorporate forecast information that is dynamically revealed alongside the evolution of the underlying state variable. We use the martingale model for forecast evolution (MMFE) to enforce the necessary consistency properties that must govern the joint evolution of forecasts with the underlying state. The formulation also generates jointly Markovian dynamics that give rise to Markov decision processes (MDPs) that remain computationally tractable. This paper is the first to enforce MMFE consistency requirements within an MDP formulation that preserves tractability. This article is part of the theme issue 'The mathematics of energy systems'.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8182152PMC
http://dx.doi.org/10.1098/rsta.2019.0430DOI Listing

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