A Computational Approach to Sequential Decision Optimization in Energy Storage and Trading

Paolo Falbo, Juri Hinz, Piyachat Leelasilapasart and Cristian Pelizzari
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Juri Hinz: University of Technology Sydney
Piyachat Leelasilapasart: University of Technology Sydney

No 422, Research Paper Series from Quantitative Finance Research Centre, University of Technology, Sydney

Abstract: Due to recent technical progress, using battery energy storages are becoming a viable option in the power sector. Their optimal operational management focuses on load shift and shaving of price spikes. However, this requires optimally responding to electricity demand, intermittent generation, and volatile electricity prices. More importantly, such optimization must take into account the so-called deep discharge costs, which have a significant impact on battery lifespan. We present a solution to a class of stochastic optimal control problems associated with these applications. Our numerical techniques are based on efficient algorithms which deliver a guaranteed accuracy.

Keywords: Approximate dynamic programming; energy trading; optimal control; power sector (search for similar items in EconPapers)
Pages: 25 pages
Date: 2021-01-01
New Economics Papers: this item is included in nep-cmp and nep-ene
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