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Two-stage stochastic optimization frameworks to aid in decision-making under uncertainty for variable resource generators participating in a sequential energy market

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  • Al-Lawati, Razan A.H.
  • Crespo-Vazquez, Jose L.
  • Faiz, Tasnim Ibn
  • Fang, Xin
  • Noor-E-Alam, Md.

Abstract

Decisions for a variable renewable resource generator’s commitment in the energy market are typically made in advance when little information is obtainable about wind availability and market prices. Much research has been published recommending various frameworks for addressing this issue. However, these frameworks are limited as they do not consider all markets a producer can participate in. Moreover, current stochastic programming models do not allow for uncertainty data to be updated as more accurate information becomes available. This work proposes two decision-making frameworks for a wind energy generator participating in day-ahead, intraday, reserve, and balancing markets. The first framework is a two-stage stochastic convex optimization approach, where both scenario-independent and scenario-dependent decisions are made concurrently. The second framework is a series of four two-stage stochastic optimization models wherein the results from each model feed into each subsequent model allowing for scenarios to be updated as more information becomes available to the decision-maker. In the simulation experiments, the multi-phase framework performs better than the single-phase in every run, and results in an average profit increase of 7%. The proposed optimization frameworks aid in better decision-making while addressing uncertainty related to variable resource generators and maximize the return on investment.

Suggested Citation

  • Al-Lawati, Razan A.H. & Crespo-Vazquez, Jose L. & Faiz, Tasnim Ibn & Fang, Xin & Noor-E-Alam, Md., 2021. "Two-stage stochastic optimization frameworks to aid in decision-making under uncertainty for variable resource generators participating in a sequential energy market," Applied Energy, Elsevier, vol. 292(C).
    • Handle: RePEc:eee:appene:v:292:y:2021:i:c:s0306261921003706
    DOI: 10.1016/j.apenergy.2021.116882
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    as
    1. Motamedi Sedeh, Omid & Ostadi, Bakhtiar, 2020. "Optimization of bidding strategy in the day-ahead market by consideration of seasonality trend of the market spot price," Energy Policy, Elsevier, vol. 145(C).
    2. Katarzyna Maciejowska & Weronika Nitka & Tomasz Weron, 2019. "Day-Ahead vs. Intraday—Forecasting the Price Spread to Maximize Economic Benefits," Energies, MDPI, vol. 12(4), pages 1-15, February.
    3. Gomes, I.L.R. & Pousinho, H.M.I. & Melício, R. & Mendes, V.M.F., 2017. "Stochastic coordination of joint wind and photovoltaic systems with energy storage in day-ahead market," Energy, Elsevier, vol. 124(C), pages 310-320.
    4. Borne, Olivier & Korte, Klaas & Perez, Yannick & Petit, Marc & Purkus, Alexandra, 2018. "Barriers to entry in frequency-regulation services markets: Review of the status quo and options for improvements," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 605-614.
    5. Olivier Borne & Klaas Korte & Yannick Perez & Marc Petit & Alexandra Purkus, 2018. "Barriers to entry in frequency-regulation services markets: Review of the status quo and options for improvements," Post-Print hal-01660475, HAL.
    6. Yuwei Wang & Huiru Zhao & Peng Li, 2019. "Optimal Offering and Operating Strategies for Wind-Storage System Participating in Spot Electricity Markets with Progressive Stochastic-Robust Hybrid Optimization Model Series," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-19, July.
    7. Liu, Ye & Wu, Xiaogang & Du, Jiuyu & Song, Ziyou & Wu, Guoliang, 2020. "Optimal sizing of a wind-energy storage system considering battery life," Renewable Energy, Elsevier, vol. 147(P1), pages 2470-2483.
    8. Koch, Christopher & Hirth, Lion, 2019. "Short-term electricity trading for system balancing: An empirical analysis of the role of intraday trading in balancing Germany's electricity system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    9. Al-Swaiti, Mustafa S. & Al-Awami, Ali T. & Khalid, Mohammad Waqas, 2017. "Co-optimized trading of wind-thermal-pumped storage system in energy and regulation markets," Energy, Elsevier, vol. 138(C), pages 991-1005.
    10. Boomsma, Trine Krogh & Juul, Nina & Fleten, Stein-Erik, 2014. "Bidding in sequential electricity markets: The Nordic case," European Journal of Operational Research, Elsevier, vol. 238(3), pages 797-809.
    11. Fernandes, Camila & Frías, Pablo & Reneses, Javier, 2016. "Participation of intermittent renewable generators in balancing mechanisms: A closer look into the Spanish market design," Renewable Energy, Elsevier, vol. 89(C), pages 305-316.
    12. Jun Dong & Anyuan Fu & Yao Liu & Shilin Nie & Peiwen Yang & Linpeng Nie, 2019. "Two-Stage Optimization Model for Two-Side Daily Reserve Capacity of a Power System Considering Demand Response and Wind Power Consumption," Sustainability, MDPI, vol. 11(24), pages 1-22, December.
    13. Crespo-Vazquez, Jose L. & Carrillo, C. & Diaz-Dorado, E. & Martinez-Lorenzo, Jose A. & Noor-E-Alam, Md, 2018. "Evaluation of a data driven stochastic approach to optimize the participation of a wind and storage power plant in day-ahead and reserve markets," Energy, Elsevier, vol. 156(C), pages 278-291.
    14. Klaus Skytte & Lucien Bobo, 2019. "Increasing the value of wind: From passive to active actors in multiple power markets," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(3), May.
    15. Crespo-Vazquez, Jose L. & Carrillo, C. & Diaz-Dorado, E. & Martinez-Lorenzo, Jose A. & Noor-E-Alam, Md., 2018. "A machine learning based stochastic optimization framework for a wind and storage power plant participating in energy pool market," Applied Energy, Elsevier, vol. 232(C), pages 341-357.
    16. Xu, Bin & Zhu, Feilin & Zhong, Ping-an & Chen, Juan & Liu, Weifeng & Ma, Yufei & Guo, Le & Deng, Xiaoliang, 2019. "Identifying long-term effects of using hydropower to complement wind power uncertainty through stochastic programming," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
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    2. Hohl, Cody & Lo Prete, Chiara & Radhakrishnan, Ashish & Webster, Mort, 2023. "Intraday markets, wind integration and uplift payments in a regional U.S. power system," Energy Policy, Elsevier, vol. 175(C).
    3. Xiong, Houbo & Zhou, Yue & Guo, Chuangxin & Ding, Yi & Luo, Fengji, 2023. "Multi-stage risk-based assessment for wind energy accommodation capability: A robust and non-anticipative method," Applied Energy, Elsevier, vol. 350(C).
    4. Fusco, Andrea & Gioffrè, Domenico & Francesco Castelli, Alessandro & Bovo, Cristian & Martelli, Emanuele, 2023. "A multi-stage stochastic programming model for the unit commitment of conventional and virtual power plants bidding in the day-ahead and ancillary services markets," Applied Energy, Elsevier, vol. 336(C).
    5. Rujie Zhu & Kaushik Das & Poul Ejnar Sørensen & Anca Daniela Hansen, 2023. "Optimal Participation of Co-Located Wind–Battery Plants in Sequential Electricity Markets," Energies, MDPI, vol. 16(15), pages 1-17, July.
    6. Cao, Jiaxin & Yang, Bo & Zhu, Shanying & Chung, Chi Yung & Guan, Xinping, 2022. "Multi-level coordinated energy management for energy hub in hybrid markets with distributionally robust scheduling," Applied Energy, Elsevier, vol. 311(C).

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