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A Mixed-Integer Convex Programming Algorithm for Security-Constrained Unit Commitment of Power System with 110-kV Network and Pumped-Storage Hydro Units

Author

Listed:
  • Shunjiang Lin

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China)

  • Guansheng Fan

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China)

  • Yuan Lu

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China)

  • Mingbo Liu

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China)

  • Yi Lu

    (The Power Dispatching Control Center of Shenzhen Power Supply Bureau, Shenzhen 518001, China)

  • Qifeng Li

    (Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL 32816, USA)

Abstract

The secure operation of 110-kV networks should be considered in the optimal generation dispatch of regional power grids in large central cities. However, since 110-kV lines do not satisfy the premise of R << X in the direct current power flow (DCPF) model, the DCPF, which is mostly applied in the security-constrained unit commitment (SCUC) problem of high-voltage power grids, is no longer suitable for describing the active power flow of regional power grids in large central cities. Hence, the quadratic active power flow (QAPF) model considering the resistance of lines is proposed to describe the network security constraints, and an SCUC model for power system with 110-kV network and pumped-storage hydro (PSH) units is established. The analytical expressions of the spinning reserve (SR) capacity of PSH units are given considering different operational modes, and the SR capacity of PSH units is included in the constraint of the SR capacity requirement of the system. The QAPF is a set of quadratic equality constraints, making the SCUC model a mixed-integer nonlinear non-convex programming (MINNP) model. To reduce the computational complexity of solving the model when applied in actual large-scale regional networks, the QAPF model is relaxed by its convex hull, and the SCUC model is transformed into a mixed-integer convex programming (MICP) model, which can be solved to obtain the global optimal solution efficiently and reliably by the mature commercial solver GUROBI (24.3.3, GAMS Development Corporation, Guangzhou, China). Test results on the IEEE-9 bus system, the PEGASE 89 bus system and the Shenzhen city power grid including the 110-kV network demonstrate that the relaxed QAPF model has good calculation accuracy and efficiency, and it is suitable for solving the SCUC problem in large-scale regional networks.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:19:p:3646-:d:270240
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    References listed on IDEAS

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    3. 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.
    4. Varkani, Ali Karimi & Daraeepour, Ali & Monsef, Hassan, 2011. "A new self-scheduling strategy for integrated operation of wind and pumped-storage power plants in power markets," Applied Energy, Elsevier, vol. 88(12), pages 5002-5012.
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    Cited by:

    1. Xing Chen & Suhua Lou & Yanjie Liang & Yaowu Wu & Xianglu He, 2021. "Optimal Scheduling of a Regional Power System Aiming at Accommodating Clean Energy," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
    2. Harun Or Rashid Howlader & Oludamilare Bode Adewuyi & Ying-Yi Hong & Paras Mandal & Ashraf Mohamed Hemeida & Tomonobu Senjyu, 2019. "Energy Storage System Analysis Review for Optimal Unit Commitment," Energies, MDPI, vol. 13(1), pages 1-21, December.

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