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Risk hedging for gas power generation considering power-to-gas energy storage in three different electricity markets

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  • Lai, Shuying
  • Qiu, Jing
  • Tao, Yuechuan
  • Zhao, Junhua

Abstract

The increasing penetration of intermittent renewable energy has introduced great risks to energy systems and markets. As a result, extensive research on energy storage systems (ESS) has been undertaken to address the risks caused by renewable energy. Among different types of ESSs, the power-to-gas (P2G) storage devices are of great potential. Thus, P2G has been used in this paper as a storage device to provide gas fuel for gas power generators. The aim of this paper is to investigate a portfolio strategy for gas generators to earn profits and hedge risks in three different electricity markets, namely, the spot, the ancillary, and the financial markets. The presented approach is to apply energy storage and financial derivatives to hedge the market risks of gas generators, including short put option and short call option, and the option value deduction process is also involved. Simulations are carried out based on the real historical data from 2016 to 2018 in Australian electricity markets. Three cases are presented, namely, the traditional model, the individual market case, and the proposed portfolio model. Based on the comparison of the three cases, simulation results show that the proposed portfolio model will help gas generators to earn a return of 1.0429 and hedge risks down to 0.0018. It has been found that the returns of the proposed model from 2016 to 2018 are 26.3% higher, whereas the risks are 88.1% lower on average comparing with the traditional model and the individual market case.

Suggested Citation

  • Lai, Shuying & Qiu, Jing & Tao, Yuechuan & Zhao, Junhua, 2021. "Risk hedging for gas power generation considering power-to-gas energy storage in three different electricity markets," Applied Energy, Elsevier, vol. 291(C).
    • Handle: RePEc:eee:appene:v:291:y:2021:i:c:s0306261921003226
    DOI: 10.1016/j.apenergy.2021.116822
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    References listed on IDEAS

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    2. Zeynali, Saeed & Nasiri, Nima & Marzband, Mousa & Ravadanegh, Sajad Najafi, 2021. "A hybrid robust-stochastic framework for strategic scheduling of integrated wind farm and plug-in hybrid electric vehicle fleets," Applied Energy, Elsevier, vol. 300(C).
    3. Živkov, Dejan & Balaban, Suzana & Simić, Milica, 2024. "Hedging gas in a multi-frequency semiparametric CVaR portfolio," Research in International Business and Finance, Elsevier, vol. 67(PA).

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