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Bi-Level Optimization for Available Transfer Capability Evaluation in Deregulated Electricity Market

Author

Listed:
  • Beibei Wang

    (School of Electrical Engineering, Southeast University, Nanjing, Jiangsu 210018, China)

  • Xin Fang

    (Department of Electrical Engineering and Computer Science, the University of Tennessee, Knoxville, TN 37996, USA)

  • Xiayang Zhao

    (State Grid International Development Corp., Xuanwumen Nei Street 108, Xicheng District, Beijing 100120, China)

  • Houhe Chen

    (Department of Electrical Engineering, Northeast Dianli University, Jilin 132012, Jilin, China)

Abstract

Available transfer capability (ATC) is the transfer capability remaining in the physical transmission network for further commercial activity over and above already committed uses which needs to be posted in the electricity market to facilitate competition. ATC evaluation is a complicated task including the determination of total transfer capability (TTC) and existing transfer capability (ETC). In the deregulated electricity market, ETC is decided by the independent system operator’s (ISO’s) economic dispatch (ED). TTC can then be obtained by a continuation power flow (CPF) method or by an optimal power flow (OPF) method, based on the given ED solutions as well as the ETC. In this paper, a bi-level optimization framework for the ATC evaluation is proposed in which ATC results can be obtained simultaneously with the ED and ETC results in the deregulated electricity market. In this bi-level optimization model, ATC evaluation is formulated as the upper level problem and the ISO’s ED is the lower level problem. The bi-level model is first converted to a mathematic program with equilibrium constraints (MPEC) by recasting the lower level problem as its Karush-Kuhn-Tucher (KKT) optimality condition. Then, the MPEC is transformed into a mixed-integer linear programming (MILP) problem, which can be solved with the help of available optimization software. In addition, case studies on PJM 5-bus, IEEE 30-bus, and IEEE 118-bus systems are presented to demonstrate the proposed methodology.

Suggested Citation

  • Beibei Wang & Xin Fang & Xiayang Zhao & Houhe Chen, 2015. "Bi-Level Optimization for Available Transfer Capability Evaluation in Deregulated Electricity Market," Energies, MDPI, vol. 8(12), pages 1-17, November.
  • Handle: RePEc:gam:jeners:v:8:y:2015:i:12:p:12370-13360:d:59378
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    References listed on IDEAS

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    1. Yanan Zheng & Jin Yang & Zhaoguang Hu & Ming Zhou & Gengyin Li, 2015. "Credibility Theory-Based Available Transfer Capability Assessment," Energies, MDPI, vol. 8(6), pages 1-20, June.
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    Cited by:

    1. Nur Mohammad & Yateendra Mishra, 2018. "The Role of Demand Response Aggregators and the Effect of GenCos Strategic Bidding on the Flexibility of Demand," Energies, MDPI, vol. 11(12), pages 1-22, November.
    2. Xin Fang & Venkat Krishnan & Bri-Mathias Hodge, 2018. "Strategic Offering for Wind Power Producers Considering Energy and Flexible Ramping Products," Energies, MDPI, vol. 11(5), pages 1-19, May.
    3. Acuña, Luceny Guzmán & Ríos, Diana Ramírez & Arboleda, Carlos Paternina & Ponzón, Esneyder González, 2018. "Cooperation model in the electricity energy market using bi-level optimization and Shapley value," Operations Research Perspectives, Elsevier, vol. 5(C), pages 161-168.
    4. Ikram Ullah & Wolfgang Gawlik & Peter Palensky, 2016. "Analysis of Power Network for Line Reactance Variation to Improve Total Transmission Capacity," Energies, MDPI, vol. 9(11), pages 1-20, November.

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