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The value of stochastic programming in day-ahead and intra-day generation unit commitment

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  • Schulze, Tim
  • McKinnon, Ken

Abstract

The recent expansion of renewable energy supplies has prompted the development of a variety of efficient stochastic optimization models and solution techniques for hydro-thermal scheduling. However, little has been published about the added value of stochastic models over deterministic ones. In the context of day-ahead and intra-day unit commitment under wind uncertainty, we compare two-stage and multi-stage stochastic models to deterministic ones and quantify their added value. We present a modification of the WILMAR scenario generation technique designed to match the properties of the errors in our wind forecasts, and show that this is needed to make the stochastic approach worthwhile. Our evaluation is done in a rolling horizon fashion over the course of two years, using a 2020 central scheduling model based on the British power system, with transmission constraints and a detailed model of pump storage operation and system-wide reserve and response provision. We show that in day-ahead scheduling the stochastic approach saves 0.3% of generation costs compared to the best deterministic approach, but the savings are less in intra-day scheduling.

Suggested Citation

  • Schulze, Tim & McKinnon, Ken, 2016. "The value of stochastic programming in day-ahead and intra-day generation unit commitment," Energy, Elsevier, vol. 101(C), pages 592-605.
    • Handle: RePEc:eee:energy:v:101:y:2016:i:c:p:592-605
    DOI: 10.1016/j.energy.2016.01.090
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    Cited by:

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    4. Geng, Zhaowei & Conejo, Antonio J. & Chen, Qixin & Xia, Qing & Kang, Chongqing, 2017. "Electricity production scheduling under uncertainty: Max social welfare vs. min emission vs. max renewable production," Applied Energy, Elsevier, vol. 193(C), pages 540-549.
    5. Yin, Yue & Liu, Tianqi & He, Chuan, 2019. "Day-ahead stochastic coordinated scheduling for thermal-hydro-wind-photovoltaic systems," Energy, Elsevier, vol. 187(C).
    6. Yin, Yue & Liu, Tianqi & Wu, Lei & He, Chuan & Liu, Yikui, 2021. "Frequency-constrained multi-source power system scheduling against N-1 contingency and renewable uncertainty," Energy, Elsevier, vol. 216(C).
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    8. Gerrit Erichsen & Tobias Zimmermann & Alfons Kather, 2019. "Effect of Different Interval Lengths in a Rolling Horizon MILP Unit Commitment with Non-Linear Control Model for a Small Energy System," Energies, MDPI, vol. 12(6), pages 1-24, March.
    9. Azad-Farsani, Ehsan, 2017. "Loss minimization in distribution systems based on LMP calculation using honey bee mating optimization and point estimate method," Energy, Elsevier, vol. 140(P1), pages 1-9.
    10. Kotur, Dimitrije & Đurišić, Željko, 2017. "Optimal spatial and temporal demand side management in a power system comprising renewable energy sources," Renewable Energy, Elsevier, vol. 108(C), pages 533-547.
    11. Löschenbrand, Markus & Wei, Wei & Liu, Feng, 2018. "Hydro-thermal power market equilibrium with price-making hydropower producers," Energy, Elsevier, vol. 164(C), pages 377-389.
    12. Turk, Ana & Wu, Qiuwei & Zhang, Menglin & Østergaard, Jacob, 2020. "Day-ahead stochastic scheduling of integrated multi-energy system for flexibility synergy and uncertainty balancing," Energy, Elsevier, vol. 196(C).
    13. Shahbazitabar, Maryam & Abdi, Hamdi, 2018. "A novel priority-based stochastic unit commitment considering renewable energy sources and parking lot cooperation," Energy, Elsevier, vol. 161(C), pages 308-324.
    14. Hermans, Mathias & Bruninx, Kenneth & Delarue, Erik, 2020. "Impact of generator start-up lead times on short-term scheduling with high shares of renewables," Applied Energy, Elsevier, vol. 268(C).
    15. Atakan, Semih & Gangammanavar, Harsha & Sen, Suvrajeet, 2022. "Towards a sustainable power grid: Stochastic hierarchical planning for high renewable integration," European Journal of Operational Research, Elsevier, vol. 302(1), pages 381-391.
    16. Liu Yuan & Jianzhong Zhou & Zijun Mai & Yuanzheng Li, 2017. "Random Fuzzy Optimization Model for Short-Term Hydropower Scheduling Considering Uncertainty of Power Load," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(9), pages 2713-2728, July.
    17. Schulze, Tim & Grothey, Andreas & McKinnon, Ken, 2017. "A stabilised scenario decomposition algorithm applied to stochastic unit commitment problems," European Journal of Operational Research, Elsevier, vol. 261(1), pages 247-259.

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