Application of stochastic dual dynamic programming to the real-time dispatch of storage under renewable supply uncertainty
(2018) IEEE Transactions on Sustainable Energy — Vol. 9, n° 2, p. 547-558 (2018)
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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.
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Papavasiliou, A., Mou, Y., Cambier, L., & Scieur, D. (2018). Application of stochastic dual dynamic programming to the real-time dispatch of storage under renewable supply uncertainty. IEEE Transactions on Sustainable Energy, 9(2), 547-558. https://doi.org/10.1109/TSTE.2017.2748463 (Original work published 2018)