The paper presents a method based on Markov decision processes to optimally schedule energy storage devices in power distribution networks with renewable generation. The time series of renewable generation is modeled as a Markov chain which allows for the implementation of a stochastic dynamic programming algorithm. The output of this algorithm is an optimal scheduling policy for the storage device achieving the minimization of an objective function including cost of energy and network losses. Besides this, other properties, such as energy storage placement and size, can be assessed and compared in optimized systems with different layouts.

Optimal storage scheduling using Markov decision processes

A Pievatolo;
2016

Abstract

The paper presents a method based on Markov decision processes to optimally schedule energy storage devices in power distribution networks with renewable generation. The time series of renewable generation is modeled as a Markov chain which allows for the implementation of a stochastic dynamic programming algorithm. The output of this algorithm is an optimal scheduling policy for the storage device achieving the minimization of an objective function including cost of energy and network losses. Besides this, other properties, such as energy storage placement and size, can be assessed and compared in optimized systems with different layouts.
2016
Istituto di Matematica Applicata e Tecnologie Informatiche - IMATI -
Energy storage; Markov processes; renewable generation; stochastic dynamic programming
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/336074
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