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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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    5. Wen, Le & Suomalainen, Kiti & Sharp, Basil & Yi, Ming & Sheng, Mingyue Selena, 2022. "Impact of wind-hydro dynamics on electricity price: A seasonal spatial econometric analysis," Energy, Elsevier, vol. 238(PC).
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    9. 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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    13. Han, Chanok & Vinel, Alexander, 2022. "Reducing forecasting error by optimally pooling wind energy generation sources through portfolio optimization," Energy, Elsevier, vol. 239(PB).
    14. Balkhair, Khaled S. & Rahman, Khalil Ur, 2017. "Sustainable and economical small-scale and low-head hydropower generation: A promising alternative potential solution for energy generation at local and regional scale," Applied Energy, Elsevier, vol. 188(C), pages 378-391.
    15. 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.
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