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Private and social benefits of a pumped hydro energy storage with increasing amount of wind power

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  • Karhinen, S.
  • Huuki, H.

Abstract

In this paper, we calculate the long-term profitability of a pumped hydro energy storage (PHES) plant that is planned to be built in an old mine. We model the optimal PHES operation for several scenarios with different wind power penetration levels. Our modelling approach first involves estimating wholesale electricity prices for the day-ahead, intraday and balancing market as a function of wind power penetration. The estimated price profiles are implemented in a dynamic programming model, where the PHES plant maximises its balancing market revenue given the optimal commitment in the day-ahead market. We show that increasing the wind penetration changes the optimal PHES operation and increases the PHES profits. Additionally, we quantify how the costs of wind power balancing are affected by the PHES investment. Policy implications are drawn based on the estimated private and social benefits from the investment.

Suggested Citation

  • Karhinen, S. & Huuki, H., 2019. "Private and social benefits of a pumped hydro energy storage with increasing amount of wind power," Energy Economics, Elsevier, vol. 81(C), pages 942-959.
    • Handle: RePEc:eee:eneeco:v:81:y:2019:i:c:p:942-959
    DOI: 10.1016/j.eneco.2019.05.024
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    Citations

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    Cited by:

    1. G.S. Chebotareva & A.A. Dvinayninov, 2021. "An Economic Alternative to Replacing Centralized Gas Supply with Autonomous Biogas Facilities in Russian Cities," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 20(3), pages 582-612.
    2. Yanyue Wang & Guohua Fang & Zhenni Wang, 2022. "The Benefit Realization Mechanism of Pumped Storage Power Plants Based on Multi-Dimensional Regulation and Leader-Follower Decision-Making," Energies, MDPI, vol. 15(16), pages 1-15, August.
    3. Jayanta Bhusan Basu & Subhojit Dawn & Pradip Kumar Saha & Mitul Ranjan Chakraborty & Taha Selim Ustun, 2022. "Economic Enhancement of Wind–Thermal–Hydro System Considering Imbalance Cost in Deregulated Power Market," Sustainability, MDPI, vol. 14(23), pages 1-25, November.
    4. Anne Immonen & Maria Kopsakangas-Savolainen, 2022. "Capturing Consumers’ Awareness and the Intention to Support Carbon Neutrality through Energy Efficient Consumption," Energies, MDPI, vol. 15(11), pages 1-27, May.
    5. Chyong, Chi Kong & Newbery, David, 2022. "A unit commitment and economic dispatch model of the GB electricity market – Formulation and application to hydro pumped storage," Energy Policy, Elsevier, vol. 170(C).
    6. Côté, Elizabeth & Salm, Sarah, 2022. "Risk-adjusted preferences of utility companies and institutional investors for battery storage and green hydrogen investment," Energy Policy, Elsevier, vol. 163(C).
    7. Harun Or Rashid Howlader & Oludamilare Bode Adewuyi & Ying-Yi Hong & Paras Mandal & Ashraf Mohamed Hemeida & Tomonobu Senjyu, 2019. "Energy Storage System Analysis Review for Optimal Unit Commitment," Energies, MDPI, vol. 13(1), pages 1-21, December.
    8. Tian, Bingying & He, Yongxiu & Zhou, Jinghan & Wang, Bingwen & Wang, Yi & Shi, Wenran, 2023. "Cost-sharing mechanisms for pumped storage plants at different market stages in China," Renewable Energy, Elsevier, vol. 217(C).
    9. Karhinen, Santtu & Huuki, Hannu, 2020. "How are the long distances between renewable energy sources and load centres reflected in locational marginal prices?," Energy, Elsevier, vol. 210(C).
    10. Xiaokun Man & Hongyan Song & Huanhuan Li, 2023. "Estimating Hydropower Generation Flexibilities of a Hybrid Hydro–Wind Power System: From the Perspective of Multi-Time Scales," Energies, MDPI, vol. 16(13), pages 1-17, July.
    11. Han, Zhixin & Fang, Debin & Yang, Peiwen & Lei, Leyao, 2023. "Cooperative mechanisms for multi-energy complementarity in the electricity spot market," Energy Economics, Elsevier, vol. 127(PB).
    12. Zhang, Mingming & Nie, Jinchen & Su, Bin & Liu, Liyun, 2024. "An option game model applicable to multi-agent cooperation investment in energy storage projects," Energy Economics, Elsevier, vol. 131(C).

    More about this item

    Keywords

    Wind power; Energy storage; Dynamic programming; Balancing costs; Pumped hydro;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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