A Configuration-Component-Based Hybrid Model for Combined-Cycle Units in MISO Day-Ahead Market

Chenxi Dai, Yonghong Chen, Fengyu Wang, Jie Wan, Lei Wu

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

This paper proposes a hybrid combined-cycle gas turbine (CCGT) model for day-ahead market clearing, in order to enhance the operation flexibility of CCGTs in practice. The proposed hybrid model, by taking benefits of combined offers from market participants on both configurations and individual physical turbines, can more accurately reflect physical operation features of CCGTs than existing CCGT models. A comprehensive review on existing CCGT models in academia and industry practice with their advantages and shortcomings is conducted. By taking benefits of the two most investigated models, i.e., configuration-based model and component-based model, the mapping relationship between these two models is revealed for deriving the proposed hybrid model. Tight formulations are further discussed for achieving the better computational performance. The proposed hybrid model is tested and compared with other CCGT models via the modified IEEE 118-bus system and the midcontinent independent system operator system. Results show notable benefits in maintaining operation flexibility and enhancing social welfare.

Original languageEnglish
Article number8477120
Pages (from-to)883-896
Number of pages14
JournalIEEE Transactions on Power Systems
Volume34
Issue number2
DOIs
StatePublished - Mar 2019

Keywords

  • Combined-cycle gas turbine
  • hybrid model
  • mixed-integer programming
  • security-constrained unit commitment
  • tight formulation

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