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Generation risk assessment in volatile conditions with wind, hydro, and natural gas units

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  • Sahin, Cem
  • Shahidehpour, Mohammad
  • Erkmen, Ismet

Abstract

This paper studies a generating company (GENCO)’s midterm (a few months to a year) scheduling payoffs and risks in volatile operating conditions. The proposed algorithm considers the integration of intermittent wind units into a GENCO’s generation assets and coordinates the GENCO’s hourly wind generation schedule with that of natural gas (NG) units (with volatile gas prices) and hydro units (with water inflow forecast) for maximizing the GENCO’s payoff. The proposed midterm GENCO model applies market price forecasts to the risk-constrained stochastic price-based unit commitment (PBUC) for calculating the GENCO’s risk in energy and ancillary services markets. The proposed PBUC minimizes the cost of (a) NG contracts, storage, startup and shutdown, (b) startup and shutdown of cascaded hydro units, and (c) penalty for defaulting on the scheduled power delivery. Simulation results show that the diversification of generating assets including bilateral contracts (BCs) could enhance the GENCO’s midterm planning by increasing the expected payoff and decreasing the financial risk.

Suggested Citation

  • Sahin, Cem & Shahidehpour, Mohammad & Erkmen, Ismet, 2012. "Generation risk assessment in volatile conditions with wind, hydro, and natural gas units," Applied Energy, Elsevier, vol. 96(C), pages 4-11.
    • Handle: RePEc:eee:appene:v:96:y:2012:i:c:p:4-11
    DOI: 10.1016/j.apenergy.2011.11.007
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    References listed on IDEAS

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    1. Tuohy, Aidan & Meibom, Peter & Denny, Eleanor & O'Malley, Mark, 2009. "Unit commitment for systems with significant wind penetration," MPRA Paper 34849, University Library of Munich, Germany.
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    2. Fotouhi Ghazvini, Mohammad Ali & Canizes, Bruno & Vale, Zita & Morais, Hugo, 2013. "Stochastic short-term maintenance scheduling of GENCOs in an oligopolistic electricity market," Applied Energy, Elsevier, vol. 101(C), pages 667-677.
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    11. Diagoupis, Theodoros D. & Andrianesis, Panagiotis E. & Dialynas, Evangelos N., 2016. "A planning approach for reducing the impact of natural gas network on electricity markets," Applied Energy, Elsevier, vol. 175(C), pages 189-198.
    12. Devlin, Joseph & Li, Kang & Higgins, Paraic & Foley, Aoife, 2017. "Gas generation and wind power: A review of unlikely allies in the United Kingdom and Ireland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 757-768.
    13. Esmaeili Aliabadi, Danial & Kaya, Murat & Sahin, Guvenc, 2017. "Competition, risk and learning in electricity markets: An agent-based simulation study," Applied Energy, Elsevier, vol. 195(C), pages 1000-1011.
    14. Fan, Zhi-Ping & Cai, Siqin & Guo, Dongliang & Xu, Bo, 2022. "Facing the uncertainty of renewable energy production: Production decisions of a power plant with different risk attitudes," Renewable Energy, Elsevier, vol. 199(C), pages 1237-1247.
    15. Chertkov, Michael & Backhaus, Scott & Lebedev, Vladimir, 2015. "Cascading of fluctuations in interdependent energy infrastructures: Gas-grid coupling," Applied Energy, Elsevier, vol. 160(C), pages 541-551.
    16. Quan, Hao & Srinivasan, Dipti & Khambadkone, Ashwin M. & Khosravi, Abbas, 2015. "A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources," Applied Energy, Elsevier, vol. 152(C), pages 71-82.

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