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A Multi-Layer Data-Driven Security Constrained Unit Commitment Approach with Feasibility Compliance

Author

Listed:
  • Ali Feliachi

    (Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26505, USA)

  • Talha Iqbal

    (Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26505, USA)

  • Muhammad Choudhry

    (Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26505, USA)

  • Hasan Ul Banna

    (Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26505, USA)

Abstract

Security constrained unit commitment is an essential part of the day-ahead energy markets. The presence of discrete and continuous variables makes it a complex, mixed-integer, and time-hungry optimization problem. Grid operators solve unit commitment problems multiple times daily with only minor changes in the operating conditions. Solving a large-scale unit commitment problem requires considerable computational effort and a reasonable time. However, the solution time can be improved by exploiting the fact that the operating conditions do not change significantly in the day-ahead market clearing. Therefore, in this paper, a novel multi-layer data-driven approach is proposed, which significantly improves the solution time (90% time-reduction on average for the three studied systems). The proposed approach not only provides a near-optimal solution (<1% optimality gap) but also ensures that it is feasible for the stable operation of the system (0% infeasible predicted solutions). The efficacy of the developed algorithm is demonstrated through numerical simulations on three test systems, namely a 4-bus system and the IEEE 39-bus and 118-bus systems, and promising results are obtained.

Suggested Citation

  • Ali Feliachi & Talha Iqbal & Muhammad Choudhry & Hasan Ul Banna, 2022. "A Multi-Layer Data-Driven Security Constrained Unit Commitment Approach with Feasibility Compliance," Energies, MDPI, vol. 15(20), pages 1-19, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:20:p:7754-:d:948044
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