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A decomposition method for network-constrained unit commitment with AC power flow constraints

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  • Bai, Yang
  • Zhong, Haiwang
  • Xia, Qing
  • Kang, Chongqing
  • Xie, Le

Abstract

To meet the increasingly high requirement of smart grid operations, considering AC power flow constraints in the NCUC (network-constrained unit commitment) is of great significance in terms of both security and economy. This paper proposes a decomposition method to solve NCUC with AC power flow constraints. With conic approximations of the AC power flow equations, the master problem is formulated as a MISOCP (mixed integer second-order cone programming) model. The key advantage of this model is that the active power and reactive power are co-optimised, and the transmission losses are considered. With the AC optimal power flow model, the AC feasibility of the UC result of the master problem is checked in subproblems. If infeasibility is detected, feedback constraints are generated based on the sensitivity of bus voltages to a change in the unit reactive power generation. They are then introduced into the master problem in the next iteration until all AC violations are eliminated. A 6-bus system, a modified IEEE 30-bus system and the IEEE 118-bus system are used to validate the performance of the proposed method, which provides a satisfactory solution with approximately 44-fold greater computational efficiency.

Suggested Citation

  • Bai, Yang & Zhong, Haiwang & Xia, Qing & Kang, Chongqing & Xie, Le, 2015. "A decomposition method for network-constrained unit commitment with AC power flow constraints," Energy, Elsevier, vol. 88(C), pages 595-603.
    • Handle: RePEc:eee:energy:v:88:y:2015:i:c:p:595-603
    DOI: 10.1016/j.energy.2015.05.082
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    References listed on IDEAS

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    1. Kim, Jong Suk & Edgar, Thomas F., 2014. "Optimal scheduling of combined heat and power plants using mixed-integer nonlinear programming," Energy, Elsevier, vol. 77(C), pages 675-690.
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    1. Kyu-Hyung Jo & Mun-Kyeom Kim, 2018. "Stochastic Unit Commitment Based on Multi-Scenario Tree Method Considering Uncertainty," Energies, MDPI, vol. 11(4), pages 1-17, March.
    2. Akhlaghi, M. & Moravej, Z. & Bagheri, A., 2022. "Maximizing wind energy utilization in smart power systems using a flexible network-constrained unit commitment through dynamic lines and transformers rating," Energy, Elsevier, vol. 261(PA).
    3. Li, Chaoshun & Wang, Wenxiao & Wang, Jinwen & Chen, Deshu, 2019. "Network-constrained unit commitment with RE uncertainty and PHES by using a binary artificial sheep algorithm," Energy, Elsevier, vol. 189(C).
    4. Ahmed Al-Shafei & Hamidreza Zareipour & Yankai Cao, 2022. "High-Performance and Parallel Computing Techniques Review: Applications, Challenges and Potentials to Support Net-Zero Transition of Future Grids," Energies, MDPI, vol. 15(22), pages 1-58, November.
    5. Zhang, Jingrui & Tang, Qinghui & Chen, Yalin & Lin, Shuang, 2016. "A hybrid particle swarm optimization with small population size to solve the optimal short-term hydro-thermal unit commitment problem," Energy, Elsevier, vol. 109(C), pages 765-780.
    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).
    7. Fattahi, Salar & Ashraphijuo, Morteza & Lavaei, Javad & Atamtürk, Alper, 2017. "Conic relaxations of the unit commitment problem," Energy, Elsevier, vol. 134(C), pages 1079-1095.
    8. Kyu-Hyung Jo & Mun-Kyeom Kim, 2018. "Improved Genetic Algorithm-Based Unit Commitment Considering Uncertainty Integration Method," Energies, MDPI, vol. 11(6), pages 1-18, May.
    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. Chen, Dongwen & Hu, Xiao & Li, Yong & Abbas, Zulkarnain & Wang, Ruzhu & Li, Dehong, 2023. "Nodal conservation principle of potential energy flow analysis for energy flow calculation in energy internet," Energy, Elsevier, vol. 263(PA).
    11. Kim, Tae Hyun & Shin, Hansol & Kwag, Kyuhyeong & Kim, Wook, 2020. "A parallel multi-period optimal scheduling algorithm in microgrids with energy storage systems using decomposed inter-temporal constraints," Energy, Elsevier, vol. 202(C).
    12. Shunjiang Lin & Zhibin Yang & Guansheng Fan & Mingbo Liu & Sen He & Zhiqiang Tang & Yunong Song, 2019. "A Mixed-Integer Second-Order Cone Programming Algorithm for the Optimal Power Distribution of AC-DC Parallel Transmission Channels," Energies, MDPI, vol. 12(19), pages 1-16, September.
    13. Min Xie & Yuxin Du & Peijun Cheng & Wei Wei & Mingbo Liu, 2019. "A Cross-Entropy-Based Hybrid Membrane Computing Method for Power System Unit Commitment Problems," Energies, MDPI, vol. 12(3), pages 1-18, February.

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