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Optimisation model for online generators when a new generator is about to get started during power system restoration process

Optimisation model for online generators when a new generator is about to get started during power system restoration process

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Rapid restoration of power systems is vitally important following an outage; however, existing optimal objectives and models to start up all the generators may cause problems where by some generators are ramping while others are waiting shown in the calculation results. To address this problem considering the generator regulation characteristics, a variable-constrained maximum-value minimisation model is proposed in this study to describe the practical problem. By introducing the time variable t, the variable-constrained optimisation problem is converted to a constrained optimal power flow problem, which can be solved using common optimisation approaches. Applying the proposed model and method, the optimisation method is discussed considering the characteristics of generators during power system black start. Numerical results show that the algorithm is effective and can significantly reduce the restoration time. The algorithm described here is applied to the Guangdong power grid self-healing decision-making system.

References

    1. 1)
      • 1. Qiulan, W.: ‘Theory study for self-healing of large power grid’, Autom. Electr. Power Syst., 2009, 33, no., pp. 2932.
    2. 2)
      • 2. Jinhuan, Y.: ‘Discussion on several issues concerning FCB’, Electr. Power, 2007, 40, (5), pp. 5962.
    3. 3)
    4. 4)
      • 4. Yunhai, Z., Yong, M., Bin, Y.: ‘Decision support system for black-start’, Autom. Electr. Power Syst., 2001, 25, no., pp. 4346.
    5. 5)
    6. 6)
      • 6. Ketabi, A., Asmar, H., Ranjbar, A.M., et al: ‘An approach for optimal units start-up during bulk power system restoration’. 2001 Large Engineering Systems Conf. on Power Engineering, 2001. LESCOPE '01., 2001, vol., no., pp. 190194.
    7. 7)
    8. 8)
      • 8. Zhong, H.-r., Gu, X.-p.: ‘Determination of optimal unit start-up sequences based on fuzzy AHP in power system restoration’. 2011 fourth Int. Conf. on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 6–9 July 2011, pp. 15411545.
    9. 9)
      • 9. Zhong, H., Gu, X.P., Zhu, X.: ‘Optimization method for unit restarting during power system black-start restoration’. Power and Energy Engineering Conf. (APPEEC), 2012, Asia-Pacific, 27-29 March 2012, pp. 14.
    10. 10)
      • 10. Linfeng, Y., Jinbao, J., Daolan, H.: ‘Multiple centrality corrections interior point optimal power flow algorithm based on optimal centering parameter’, Proc. CSEE, 2012, 32, (4), pp. 136144.
    11. 11)
      • 11. Liu, C., Wu, M., Deng, Y.: ‘Start-up sequence of generators in power system restoration avoiding the backtracking algorithm’. 2013 IEEE Power and Energy Society General Meeting, Vancouver, Canada, 21–25 July 2013.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2016.0331
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