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Towards accurate modeling of dynamic startup/shutdown and ramping processes of thermal units in unit commitment problems

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  • Liu, Yikui
  • Wu, Lei
  • Li, Jie

Abstract

The unit commitment problem is fundamental to the optimal operation of power systems, which is solved by Independent System Operators routinely in day-ahead markets to guarantee operational security and economics. Continuously enhancing the unit commitment model to improve modeling accuracy in response to future market challenges and participants’ requests has always been one of Independent System Operators’ main tasks, for deriving physically feasible and operationally reliable unit commitment and dispatch schedules that can render better economic efficiency. Thermal units account for 68% of the total installed electricity generation capacity and supply 63% of total electricity consumption in U.S.. Startup time of thermal units could vary from hours to days, and the corresponding startup cost could be 100 times different and as high as $500,000 per startup. To this end, this paper accurately accesses detailed startup and shutdown procedures of thermal units by simulating dynamic unit temperature evolution and modeling sequential unit operation stages. In addition, dynamic ramping and forbidden zones are also considered to further enhance the modeling accuracy. A modified IEEE 118-bus system is adopted to validate and evaluate the proposed models.

Suggested Citation

  • Liu, Yikui & Wu, Lei & Li, Jie, 2019. "Towards accurate modeling of dynamic startup/shutdown and ramping processes of thermal units in unit commitment problems," Energy, Elsevier, vol. 187(C).
    • Handle: RePEc:eee:energy:v:187:y:2019:i:c:s0360544219315634
    DOI: 10.1016/j.energy.2019.115891
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    References listed on IDEAS

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    5. Abdul Rauf & Mahmoud Kassas & Muhammad Khalid, 2022. "Data-Driven Optimal Battery Storage Sizing for Grid-Connected Hybrid Distributed Generations Considering Solar and Wind Uncertainty," Sustainability, MDPI, vol. 14(17), pages 1-27, September.

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