Optimal Generation and Storage Scheduling in the Presence of Renewable Forecast Uncertainties

Nicolas Gast 1, 2 Dan-Cristian Tomozei 2 Jean-Yves Le Boudec 2
1 MESCAL - Middleware efficiently scalable
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : —Renewable energy sources, such as wind, are char-acterized by non-dispatchability, high volatility, and non-perfect forecasts. These undesirable features can lead to energy loss and/or can necessitate a large reserve in the form of fast-ramping fuel-based generators. Energy storage can be used to mitigate these ef-fects. In this paper, we are interested in the tradeoff between the use of the reserves and the energy loss. Energy loss includes energy that is either wasted, due to the inefficiency of the storage cycle and the inevitable forecasting errors, or lost when the storage capacity is insufficient. We base our analysis on an initial model proposed by Bejan, Gibbens, and Kelly. We first provide theoretical bounds on the trade-off between energy loss and the use of reserves. For a large storage capacity, we show that this bound is tight, and we de-velop an algorithm that computes the optimal schedule. Second, we develop a scheduling strategy that is efficient for small or moderate storage. We evaluate these policies on real data from the U.K. grid and show that they outperform existing heuristics. In addition, we provide guidelines for computing the optimal storage character-istics and the reserve size for a given penetration of wind in the energy mix.
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Article dans une revue
IEEE Transactions on Smart Grid, Institute of Electrical and Electronics Engineers, 2014, pp.12. 〈10.1109/TSG.2013.2285395〉
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Nicolas Gast, Dan-Cristian Tomozei, Jean-Yves Le Boudec. Optimal Generation and Storage Scheduling in the Presence of Renewable Forecast Uncertainties. IEEE Transactions on Smart Grid, Institute of Electrical and Electronics Engineers, 2014, pp.12. 〈10.1109/TSG.2013.2285395〉. 〈hal-01086022〉

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