Application of Stochastic Dual Dynamic Programming to the Real-Time Dispatch of Storage under Renewable Supply Uncertainty

This paper presents a multi-stage stochastic programming formulation of transmission-constrained economic dispatch subject to multi-area renewable production uncertainty, with a focus on optimizing the dispatch of storage in real-time operations. This problem is resolved using stochastic dual dynami...

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Vydáno v:IEEE Power & Energy Society General Meeting s. 1
Hlavní autoři: Papavasiliou, Anthony, Mou, Yuting, Cambier, Leopold, Scieur, Damien
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.08.2018
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ISSN:1944-9933
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Abstract This paper presents a multi-stage stochastic programming formulation of transmission-constrained economic dispatch subject to multi-area renewable production uncertainty, with a focus on optimizing the dispatch of storage in real-time operations. This problem is resolved using stochastic dual dynamic programming. The applicability of the proposed approach is demonstrated on a realistic case study of the German power system calibrated against the solar and wind power integration levels of 2013-2014, with a 24-hour horizon and 15-minute time step. The value of the stochastic solution relative to the cost of a deterministic policy amounts to 1.1%, while the value of perfect foresight relative to the cost of the stochastic programming policy amounts to 0.8%. The relative performance of various alternative real-time dispatch policies is analyzed, and the sensitivity of the results is explored.
AbstractList This paper presents a multi-stage stochastic programming formulation of transmission-constrained economic dispatch subject to multi-area renewable production uncertainty, with a focus on optimizing the dispatch of storage in real-time operations. This problem is resolved using stochastic dual dynamic programming. The applicability of the proposed approach is demonstrated on a realistic case study of the German power system calibrated against the solar and wind power integration levels of 2013-2014, with a 24-hour horizon and 15-minute time step. The value of the stochastic solution relative to the cost of a deterministic policy amounts to 1.1%, while the value of perfect foresight relative to the cost of the stochastic programming policy amounts to 0.8%. The relative performance of various alternative real-time dispatch policies is analyzed, and the sensitivity of the results is explored.
Author Papavasiliou, Anthony
Cambier, Leopold
Mou, Yuting
Scieur, Damien
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  organization: Center for Operations Research and Econometrics, Université catholique de Louvain
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  givenname: Yuting
  surname: Mou
  fullname: Mou, Yuting
  organization: Center for Operations Research and Econometrics, Université catholique de Louvain
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  givenname: Leopold
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  organization: Institute for Computational and Mathematical Engineering, Stanford University
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  givenname: Damien
  surname: Scieur
  fullname: Scieur, Damien
  organization: the Computer Science Department, Ecole normale Sup´erieure d'Ulm
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Snippet This paper presents a multi-stage stochastic programming formulation of transmission-constrained economic dispatch subject to multi-area renewable production...
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SubjectTerms Dynamic programming
Econometrics
Operations research
Programming
Real-time systems
Uncertainty
Title Application of Stochastic Dual Dynamic Programming to the Real-Time Dispatch of Storage under Renewable Supply Uncertainty
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