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Optimal Operation of Critical Peak Pricing for an Energy Retailer Considering Balancing Costs

Author

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  • Hye Yoon Song

    (Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea)

  • Gyu Sub Lee

    (Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea)

  • Yong Tae Yoon

    (Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea)

Abstract

Recently, there have been frequent fluctuations in the wholesale prices of electricity following the increased penetration of renewable energy sources. Therefore, retailers face price risks caused by differences between wholesale prices and retail rates. As a hedging against price risk, retailers can utilize critical peak pricing (CPP) in a price-based program. This study proposes a novel multi-stage stochastic programming (MSSP) model for a retailer with self-generation photovoltaic facility to optimize both its bidding strategy and the CPP operation, in the face of several uncertainties. Using MSSP, decisions can be determined sequentially with realization of the uncertainties over time. Furthermore, to ensure a global optimum, a mixed integer non-linear programming is transformed into mixed integer linear programming through three linearization steps. In a numerical simulation, the effectiveness of the proposed MSSP model is compared with that of a mean-value deterministic model based on a rolling horizon method. We also investigate the optimal strategy of a retailer by changing various input parameters and perform a sensitivity analysis to assess the impacts of different uncertain parameters on the retailer’s profit. Finally, the effect of the energy storage system on the proposed optimization problem is investigated.

Suggested Citation

  • Hye Yoon Song & Gyu Sub Lee & Yong Tae Yoon, 2019. "Optimal Operation of Critical Peak Pricing for an Energy Retailer Considering Balancing Costs," Energies, MDPI, vol. 12(24), pages 1-20, December.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:24:p:4658-:d:295463
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    References listed on IDEAS

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    1. Huisman, Ronald & Huurman, Christian & Mahieu, Ronald, 2007. "Hourly electricity prices in day-ahead markets," Energy Economics, Elsevier, vol. 29(2), pages 240-248, March.
    2. Herter, Karen & Wayland, Seth, 2010. "Residential response to critical-peak pricing of electricity: California evidence," Energy, Elsevier, vol. 35(4), pages 1561-1567.
    3. Herter, Karen & McAuliffe, Patrick & Rosenfeld, Arthur, 2007. "An exploratory analysis of California residential customer response to critical peak pricing of electricity," Energy, Elsevier, vol. 32(1), pages 25-34.
    4. Paul L Joskow, 2019. "Challenges for wholesale electricity markets with intermittent renewable generation at scale: the US experience," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 35(2), pages 291-331.
    5. Herter, Karen, 2007. "Residential implementation of critical-peak pricing of electricity," Energy Policy, Elsevier, vol. 35(4), pages 2121-2130, April.
    6. Thanh Tam Ho & Sarana Shinkuma & Koji Shimada, 2018. "The Effects of Dynamic Pricing of Electric Power on Consumer Behavior: A Propensity Score Analysis for Empirical Study on Nushima Island, Japan," Energies, MDPI, vol. 11(8), pages 1-22, August.
    7. Steve A. Fenrick, Lullit Getachew, Chris Ivanov, and Jeff Smith, 2014. "Demand Impact of a Critical Peak Pricing Program: Opt-in and Opt-out Options, Green Attitudes and Other Customer Characteristics," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    8. Wang, Xiaonan & Palazoglu, Ahmet & El-Farra, Nael H., 2015. "Operational optimization and demand response of hybrid renewable energy systems," Applied Energy, Elsevier, vol. 143(C), pages 324-335.
    9. Goutam Dutta & Krishnendranath Mitra, 2017. "A literature review on dynamic pricing of electricity," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1131-1145, October.
    10. Katrina Jessoe & David Rapson, 2015. "Commercial and Industrial Demand Response Under Mandatory Time-of-Use Electricity Pricing," Journal of Industrial Economics, Wiley Blackwell, vol. 63(3), pages 397-421, September.
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