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Optimal Time to Invest Energy Storage System under Uncertainty Conditions

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  • Yongma Moon

    (College of Business Administration, University of Seoul, Seoul 130743, Korea)

Abstract

This paper proposes a model to determine the optimal investment time for energy storage systems (ESSs) in a price arbitrage trade application under conditions of uncertainty over future profits. The adoption of ESSs can generate profits from price arbitrage trade, which are uncertain because the future marginal prices of electricity will change depending on supply and demand. In addition, since the investment is optional, an investor can delay adopting an ESS until it becomes profitable, and can decide the optimal time. Thus, when we evaluate this investment, we need to incorporate the investor’s option which is not captured by traditional evaluation methods. In order to incorporate these aspects, we applied real option theory to our proposed model, which provides an optimal investment threshold. Our results concerning the optimal time to invest show that if future profits that are expected to be obtained from arbitrage trade become more uncertain, an investor needs to wait longer to invest. Also, improvement in efficiency of ESSs can reduce the uncertainty of arbitrage profit and, consequently, the reduced uncertainty enables earlier ESS investment, even for the same power capacity. Besides, when a higher rate of profits is expected and ESS costs are higher, an investor needs to wait longer. Also, by comparing a widely used net present value model to our real option model, we show that the net present value method underestimates the value for ESS investment and misleads the investor to make an investment earlier.

Suggested Citation

  • Yongma Moon, 2014. "Optimal Time to Invest Energy Storage System under Uncertainty Conditions," Energies, MDPI, vol. 7(4), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:4:p:2701-2719:d:35479
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    Cited by:

    1. Kyungcheol Shin & Jinyeong Lee, 2024. "Investment Decision for Long-Term Battery Energy Storage System Using Least Squares Monte Carlo," Energies, MDPI, vol. 17(9), pages 1-15, April.
    2. Lai, Chun Sing & Locatelli, Giorgio, 2021. "Valuing the option to prototype: A case study with Generation Integrated Energy Storage," Energy, Elsevier, vol. 217(C).
    3. Moon, Yongma & Baran, Mesut, 2018. "Economic analysis of a residential PV system from the timing perspective: A real option model," Renewable Energy, Elsevier, vol. 125(C), pages 783-795.

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