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Exploring the reliability effects on the short term AC security-constrained unit commitment: A stochastic evaluation

Author

Listed:
  • Aghaei, Jamshid
  • Nikoobakht, Ahmad
  • Siano, Pierluigi
  • Nayeripour, Majid
  • Heidari, Alireza
  • Mardaneh, Mohammad

Abstract

This paper proposes a stochastic model for the scheduling of short-term AC security-constrained unit commitment (AC-SCUC) considering reliability and the value of lost load (VOLL). The uncertainty of load and wind power generation, active and reactive power losses, voltage profile of the network’ buses and congestion management for different VOLLs are investigated in this paper. Furthermore, the random outages of generating unit and transmission lines are modeled based on the scenario trees in the Monte Carlo simulation and the reserve requirements of the power system are implicitly scheduled based on the VOLL and by considering corrective actions of the generation units. A computationally efficient two-stage algorithm based on bender's decomposition is proposed to solve the proposed problem. The first stage deals with the base case where all the network components, the units' outputs and on/off status can be determined based on the forecasting load and wind farms' output. The second stage investigates the stochastic part of the problem and runs the possible scenarios in parallel for all the network elements and the available units of the base case. In the case of any violation for a scenario, a bender's cut is added to the first stage which modifies the commitment state and the power units' outputs in order to tackle the violation for that scenario. The method is applied to the IEEE 118/300-bus test system to assess its applicability and capability.

Suggested Citation

  • Aghaei, Jamshid & Nikoobakht, Ahmad & Siano, Pierluigi & Nayeripour, Majid & Heidari, Alireza & Mardaneh, Mohammad, 2016. "Exploring the reliability effects on the short term AC security-constrained unit commitment: A stochastic evaluation," Energy, Elsevier, vol. 114(C), pages 1016-1032.
    • Handle: RePEc:eee:energy:v:114:y:2016:i:c:p:1016-1032
    DOI: 10.1016/j.energy.2016.08.073
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    1. Leahy, Eimear & Tol, Richard S.J., 2011. "An estimate of the value of lost load for Ireland," Energy Policy, Elsevier, vol. 39(3), pages 1514-1520, March.
    2. 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.
    3. Anthony Papavasiliou & Shmuel S. Oren, 2013. "Multiarea Stochastic Unit Commitment for High Wind Penetration in a Transmission Constrained Network," Operations Research, INFORMS, vol. 61(3), pages 578-592, June.
    4. PAPAVASILIOU, Anthony & OREN, Schmuel S., 2013. "Multiarea stochastic unit commitment for high wind penetration in a transmission constrained network," LIDAM Reprints CORE 2500, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Aghaei, J. & Shayanfar, H.A. & Amjady, N., 2009. "Joint market clearing in a stochastic framework considering power system security," Applied Energy, Elsevier, vol. 86(9), pages 1675-1682, September.
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    5. Nikoobakht, Ahmad & Aghaei, Jamshid & Mardaneh, Mohammad, 2017. "Securing highly penetrated wind energy systems using linearized transmission switching mechanism," Applied Energy, Elsevier, vol. 190(C), pages 1207-1220.
    6. Isuru, Mohasha & Hotz, Matthias & Gooi, H.B. & Utschick, Wolfgang, 2020. "Network-constrained thermal unit commitment fortexhybrid AC/DC transmission grids under wind power uncertainty," Applied Energy, Elsevier, vol. 258(C).
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    9. Shunjiang Lin & Guansheng Fan & Yuan Lu & Mingbo Liu & Yi Lu & Qifeng Li, 2019. "A Mixed-Integer Convex Programming Algorithm for Security-Constrained Unit Commitment of Power System with 110-kV Network and Pumped-Storage Hydro Units," Energies, MDPI, vol. 12(19), pages 1-24, September.
    10. Jasiūnas, Justinas & Lund, Peter D. & Mikkola, Jani & Koskela, Liinu, 2021. "Linking socio-economic aspects to power system disruption models," Energy, Elsevier, vol. 222(C).
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