Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Optimal wind turbine allocation and network reconfiguration for enhancing resiliency of system after major faults caused by natural disaster considering uncertainty

This study proposes a two-stage stochastic optimisation model for jointly wind turbine (WT) allocation and network reconfiguration (NR) so as to increase the resiliency of distribution system in face of natural disasters. In this regard, in the first level, a possibilistic-scenario method is proposed to select the line outage scenarios. The proposed model is capable with distribution systems and considers different failure probabilities for system components subject to the intensity of natural disaster in its associated zone. After selecting the line outage scenarios, in the second level, a multi-stage optimisation framework is proposed for jointly NR and WT allocation in a multi-zone and multi-fault system, considering the uncertainty of system load and wind power generation. This strategy makes an interconnection between NR and islanded WTs to increase the resiliency of system and decreases the load shedding. Different economic objectives including, costs of load shedding and power generation are considered in the model. In addition, hardening budget is taken into consideration for the transmission lines, which is minimised during the optimisation process. The simulation results demonstrate the capability and necessity of proposed resiliency-oriented method and prove the importance of hardening budgets.

References

    1. 1)
      • 3. Gholami, A., Aminifar, F., Shahidehpour, M.: ‘Front lines against the darkness: enhancing the resilience of the electricity grid through microgrid facilities’, IEEE Electrif. Mag., 2016, 4, pp. 1824.
    2. 2)
      • 32. Baran, M.E., Wu, F.F.: ‘Network reconfiguration in distribution systems for loss reduction and load balancing’, IEEE Trans. Power Deliv., 1989, 4, (2), pp. 14011407.
    3. 3)
      • 16. Chen, C., Wang, J., Qiu, F., et al: ‘Resilient distribution system by microgrids formation after natural disasters’, IEEE Trans. Smart Grid, 2016, 7, (2), pp. 958966.
    4. 4)
      • 35. Yang, B., Jiang, L., Wang, L., et al: ‘Nonlinear maximum power point tracking control and modal analysis of DFIG based wind turbine’, Int. J. Electr. Power Energy Syst., 2016, 74, pp. 429436.
    5. 5)
      • 2. Campbell, R.J.: ‘Weather-related power outages and electric system resiliency’. Congressional Research Service, Library of Congress, Washington, DC, 2012.
    6. 6)
      • 8. Liu, X., Shahidehpour, M., Li, Z., et al: ‘Microgrids for enhancing the power grid resilience in extreme conditions’, IEEE Trans. Smart Grid, 2017, 8, (2), pp. 589597.
    7. 7)
      • 21. Krishnamurthy, V., Kwasinski, A.: ‘Effects of power electronics, energy storage, power distribution architecture, and lifeline dependencies on microgrid resiliency during extreme events’, IEEE J. Emerging Sel. Top. Power Electron., 2016, 4, (4), pp. 13101323.
    8. 8)
      • 29. Mohseni-Bonab, S.M., Rabiee, A., Mohammadi-Ivatloo, B.: ‘Voltage stability constrained multi-objective optimal reactive power dispatch under load and wind power uncertainties: a stochastic approach’, Renew. Energy, 2016, 85, pp. 598609.
    9. 9)
      • 19. Gholami, A., Shekari, T., Aminifar, F., et al: ‘Microgrid scheduling with uncertainty: the quest for resilience’, IEEE Trans. Smart Grid, 2016, 7, (6), pp. 28492858.
    10. 10)
      • 9. AlMajali, A., Viswanathan, A., Neuman, C.: ‘Resilience evaluation of demand response as spinning reserve under cyber-physical threats’, Electronics, 2017, 6, (1), pp. 114.
    11. 11)
      • 27. Lin, Y., Bie, Z.: ‘Tri-level optimal hardening plan for a resilient distribution system considering reconfiguration and DG islanding’, Appl. Energy, 2017, 210, pp. 12661279.
    12. 12)
      • 30. Nikkhah, S., Rabiee, A.: ‘Optimal wind power generation investment, considering voltage stability of power systems’, Renew. Energy, 2018, 115, pp. 308325.
    13. 13)
      • 11. Bie, Z., Lin, Y., Li, G., et al: ‘Battling the extreme: a study on the power system resilience’, Proc. IEEE, 2017, 105, (7), pp. 12531266.
    14. 14)
      • 22. Olamaei, J., Niknam, T., Gharehpetian, G.B.: ‘Application of particle swarm optimization for distribution feeder reconfiguration considering distributed generators’, Appl. Math. Comput., 2008, 201, pp. 575586.
    15. 15)
      • 25. Wang, Z., Shen, C., Xu, Y., et al: ‘Risk-limiting load restoration for resilience enhancement with intermittent energy resources’, arXiv2:1704.05411, 2017.
    16. 16)
      • 10. Ding, T., Lin, Y., Bie, Z., et al: ‘A resilient microgrid formation strategy for load restoration considering master-slave distributed generators and topology reconfiguration’, Appl. Energy, 2017, 199, pp. 205216.
    17. 17)
      • 17. Wang, Z., Wang, J.: ‘Self-healing resilient distribution systems based on sectionalization into microgrids’, IEEE Trans. Power Syst., 2015, 30, (6), pp. 31393149.
    18. 18)
      • 13. Ma, S., Chen, B., Wang, Z.: ‘Resilience enhancement strategy for distribution systems under extreme weather events’, IEEE Trans. Smart Grid, 2017, 9, (2), pp. 14421451.
    19. 19)
      • 1. Executive Office of the President, Council of Economic Advisers: ‘Economic benefits of increasing electric grid resilience to weather outages’, Presidential Administration, USA, 2013.
    20. 20)
      • 34. Bussieck, R.M., Vigerske, S.: ‘MINLP solver software’, in Cochran, J.J., Cox, L.A., Keskinocak, P., et al (Eds.): ‘Wiley Encyclopedia of Operations Research and Management Science’ (Wiley, New York, 2010).
    21. 21)
      • 24. Yang, B., Yu, T., Shu, H., et al: ‘Robust sliding-mode control of wind energy conversion systems for optimal power extraction via nonlinear perturbation observers’, Appl. Energy, 2018, 210, pp. 711723.
    22. 22)
      • 4. Gao, H., Chen, Y., Xu, Y., et al: ‘Dynamic load shedding for an islanded microgrid with limited generation resources’, IET Gener. Transm. Distrib., 2016, 10, (12), pp. 29532961.
    23. 23)
      • 20. Shang, D.R.: ‘Pricing of emergency dynamic microgrid power service for distribution resilience enhancement’, Energy Policy, 2017, 111, pp. 321335.
    24. 24)
      • 14. Salman, A.M., Li, Y., Stewart, M.G.: ‘Evaluating system reliability and targeted hardening strategies of power distribution systems subjected to hurricanes’, Reliab. Eng. Syst. Saf., 2015, 144, pp. 319333.
    25. 25)
      • 5. Khodaei, A.: ‘Resiliency-oriented microgrid optimal scheduling’, IEEE Trans. Smart Grid, 2014, 5, (4), pp. 15841591.
    26. 26)
      • 31. Rabiee, A., Soroudi, A., Mohammadi-Ivatloo, B., et al: ‘Corrective voltage control scheme considering demand response and stochastic wind power’, IEEE Trans. Power Syst., 2014, 29, (6), pp. 29652973.
    27. 27)
      • 15. Wang, X., Li, Z., Shahidehpour, M., et al: ‘Robust line hardening strategies for improving the resilience of distribution systems with variable renewable resources’, IEEE Trans. Sustain. Energy, 2017, early access, DOI: 10.1109/TSTE.2017.2788041.
    28. 28)
      • 6. Manshadi, S.D., Khodayar, M.E.: ‘Resilient operation of multiple energy carrier microgrids’, IEEE Trans. Smart Grid, 2015, 6, (5), pp. 22832292.
    29. 29)
      • 12. Xu, Y., Liu, C.C., Schneider, K., et al: ‘Microgrids for service restoration to critical load in a resilient distribution system’, IEEE Trans. Smart Grid, 2016, 9, (1), pp. 426437.
    30. 30)
      • 26. Hurricane Katrina 2005. Available at https://sites.google.com/a/mail.snu.edu/earth-s-natural-disasters-online/e-n-d---spring-2012-online/bowie-courtney.
    31. 31)
      • 23. Yang, B., Yu, T., Shu, H., et al: ‘Passivity-based sliding-mode control design for optimal power extraction of a PMSG based variable speed wind turbine’, Renew. Energy, 2018, 119, pp. 577589.
    32. 32)
      • 18. Rahimi, K., Davoudi, M.: ‘Electric vehicles for improving resilience of distribution systems’, Sustain. Cities Soc., 2018, 36, pp. 246256.
    33. 33)
      • 33. Soroudi, A.: ‘Power system optimization modeling in GAMS’ (Springer, Berlin, 2017).
    34. 34)
      • 28. Panteli, M., Mancarella, P., Trakas, D., et al: ‘Metrics and quantification of operational and infrastructure resilience in power systems’, IEEE Trans. Power Syst., 2017, 32, (6), pp. 47324742.
    35. 35)
      • 7. Mousavizadeh, S., Haghifam, M.R., Shariatkhah, M.H.: ‘A linear two-stage method for resiliency analysis in distribution systems considering renewable energy and demand response resources’, Appl. Energy, 2018, 211, pp. 443460.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-rpg.2018.5237
Loading

Related content

content/journals/10.1049/iet-rpg.2018.5237
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address