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N-1-1 contingency-constrained unit commitment with renewable integration and corrective actions

  • S.I.: Scalable Optimization and Decision Making in OR
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Abstract

Meeting the customer’s power demands is crucial for energy companies, even when unexpected and consecutive failures are present. This task has considerably increased its complexity due to the high integration of renewable energies and their intermittent behaviors. Therefore, it is important to achieve reliable power supply based on a criterion closer to real-life system operations and capable of addressing consecutive failures. The N-1-1 contingency involves the loss of a single transmission line or generation unit, followed by systems adjustments. Afterward, the power system experiences a subsequent loss of an additional generation unit or transmission line. This paper presents a power system unit commitment problem considering the N-1-1 reliability criterion with operations compliance check on economic dispatch and power flows under contingency states and renewable energy integration. Corrective actions are also included to determine the time that the failed components are restored. To address the complexity caused by renewable energy integration, the reliable unit commitment is achieved under the worst-case renewable output. The formulation results in an extremely large-scale adaptive robust mixed-integer linear programming model. For an efficient solution, a variation of the nested column-and-constraint generation algorithm is designed. Besides using the susceptance and phase angles to model the power flow, the linear sensitivity factors are also applied for improving the computational performance. The proposed models and algorithms are evaluated on modified IEEE 6-bus, 14-bus, and 118-bus test systems to confirm their effectiveness.

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Acknowledgements

D. A. Zuniga Vazquez and J. L. Ruiz Duarte are supported by the Mexican National Council of Science and Technology (CONACYT) and the Mexican Department of Energy (SENER) for their PhD program. An allocation of computer time from the UA Research Computing High Performance Computing (HPC) at the University of Arizona is gratefully acknowledged.

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Authors and Affiliations

  1. Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ, 85721, USA

    Daniel A. Zuniga Vazquez & Neng Fan

  2. Department of Marketing and Business Analytics, San Jose State University, San Jose, CA, 95192, USA

    Jose L. Ruiz Duarte

  3. Energy Systems Division, Argonne National Laboratory, Argonne, IL, 60439, USA

    Feng Qiu

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  1. Daniel A. Zuniga Vazquez
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  2. Jose L. Ruiz Duarte
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  3. Neng Fan
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  4. Feng Qiu
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Correspondence to Neng Fan.

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Zuniga Vazquez, D.A., Ruiz Duarte, J.L., Fan, N. et al. N-1-1 contingency-constrained unit commitment with renewable integration and corrective actions. Ann Oper Res 316, 493–511 (2022). https://doi.org/10.1007/s10479-021-04204-y

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  • DOI: https://doi.org/10.1007/s10479-021-04204-y

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