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Optimal forward trading and battery control under renewable electricity generation

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  • Hinz, Juri
  • Yee, Jeremy

Abstract

The increased market penetration of renewable energy sources and the rapid development of electric battery storage technologies yield a potential for reducing electricity price volatility while maintaining stability of the power grid. This work presents an algorithmic approach to control battery levels and forward positions to optimally manage power output fluctuations caused by intermittent renewable energy generation. This paper will also explore the effect of battery technology on the firm’s optimal trading behaviour in the electricity spot market.

Suggested Citation

  • Hinz, Juri & Yee, Jeremy, 2018. "Optimal forward trading and battery control under renewable electricity generation," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 244-254.
    • Handle: RePEc:eee:jbfina:v:95:y:2018:i:c:p:244-254
    DOI: 10.1016/j.jbankfin.2017.06.006
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    References listed on IDEAS

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    Cited by:

    1. Anna Maria Gambaro & Nicola Secomandi, 2021. "A Discussion of Non‐Gaussian Price Processes for Energy and Commodity Operations," Production and Operations Management, Production and Operations Management Society, vol. 30(1), pages 47-67, January.
    2. Juri Hinz, 2020. "Resilience Analysis for Double Spending via Sequential Decision Optimization," Research Paper Series 408, Quantitative Finance Research Centre, University of Technology, Sydney.
    3. Paolo Falbo & Juri Hinz & Piyachat Leelasilapasart & Cristian Pelizzari, 2021. "A Computational Approach to Sequential Decision Optimization in Energy Storage and Trading," Research Paper Series 422, Quantitative Finance Research Centre, University of Technology, Sydney.

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