access icon free Optimal selection of voltage sag mitigating devices for micro-level customer in distribution system

Power quality is a vital issue in distribution systems. Power quality issues have become important for the extensive use of sensitive equipment and integration of renewable generation. Several researchers have proposed for voltage sag mitigation devices to minimise financial losses arising from voltage sag. Augmentation of micro-level units like housing complex, super-specialty hospitals, rapid urbanisation has opened up demand for electricity. Modernisation in life has led to coextensive requirement for good quality power. Importance of micro-level consumers is to be considered while looking into the matter of optimal selection of voltage sag mitigation devices. In this study, a new framework is proposed for optimal selection of voltage sag mitigation devices to minimise voltage sag occurrence in a distribution system based on Nested Logit model. Nested Logit model has the essential characteristic for selection of optimal option by allowing equal preference to all the available customers’ choice. This model gives unbiased and equal importance to all the available mitigation devices. The optimal selection of mitigation devices is obtained using aggregate forecasting. Voltage sag severity index is used for placement of optimally selected voltage sag mitigation device. Two case studies are described to validate the proposed approach.

Inspec keywords: power supply quality; power distribution economics

Other keywords: nested logit model; voltage sag mitigating devices; optimal option selection; aggregate forecasting; microlevel units; super-specialty hospitals; voltage sag occurrence minimisation; distribution systems; housing complex; power quality; financial loss minimisation; voltage sag mitigation devices; renewable generation integration; voltage sag severity index; microlevel customer

Subjects: Distribution networks; Power system management, operation and economics; Power supply quality and harmonics

References

    1. 1)
      • 19. Zhang, Y., Milanović, J.V.: ‘Global voltage sag mitigation with FACTS-based devices’, IEEE Trans. Power Deliv., 2010, 25, (4), pp. 28422850.
    2. 2)
      • 3. Bollen Math, H.J.: ‘Understanding power quality problems: voltage sags and interruptions’ (A John-wiley & Sons, Inc. Publication, Hoboken, NJ, USA, 2000).
    3. 3)
      • 33. https://www.indiamart.com/, accessed 30 December 2017.
    4. 4)
      • 36. Amanulla, B., Chakrabarti, S., Singh, S.N.: ‘Reconfiguration of power distribution systems considering reliability and power loss’, IEEE Trans. Power Deliv., 2012, 27, (2), pp. 918926.
    5. 5)
      • 4. Bollen, M.H.J.: ‘Voltage sags: effects, mitigation and prediction’, Power Eng. J., 1996, 10, (3), pp. 129135.
    6. 6)
      • 20. Alabduljabbar, A.A., Milanovic, J.V.: ‘Assessment of techno-economic contribution of FACTS devices to power system operation’, Electr. Power Syst. Res., 2010, 80, pp. 12471255.
    7. 7)
      • 29. Nelson, R.: ‘Probability, stochastic processes, and queuing theory’ (Springer, Berlin, Heidelberg, Germnay, 1995).
    8. 8)
      • 30. Koppelman, F.S., Bhat, C.: ‘A self instructing course in mode choice modeling: multinomial and Nested Logit models’ (U.S. Department of Transportation Federal Transit Administration, Washington, DC, USA, 2006).
    9. 9)
      • 6. Baldwin, T.: ‘Voltage sag analysis for making economic decisions on mitigation’. 1999 IEEE Power Engineering Society Summer Meeting. Conf. Proc. (Cat. No.99CH36364), Edmonton, Alta., 1999, vol. 1, pp. 482483.
    10. 10)
      • 31. IEEE Standard 1564, 2014: ‘IEEE guide for voltage sag indices’.
    11. 11)
      • 28. Taylor, H.M., Karlin, S.: ‘An introduction to stochastic modelling’ (Academic Press, New York, NY, USA, 1984).
    12. 12)
      • 37. Ghosh, S., Das, D.: ‘Method for load-flow solution of radial distribution networks’, IEE Proc., Gener. Transm. Distrib., 1999, 146, (6), pp. 641648.
    13. 13)
      • 24. Xiao, X.-Y., Ma, Y.-Q., Zhang, Y., et al: ‘Premium power valuation method based on customer perception of utility for high-technology manufacturing customers’, IEEE Trans. Power Deliv., 2016, 31, (4), pp. 16551662.
    14. 14)
      • 18. Milanovic, J.V., Zhang, Y.: ‘Global minimization of financial losses due to voltage sags with FACTS based devices’, IEEE Trans. Power Deliv., 2010, 25, (1), pp. 298306.
    15. 15)
      • 35. Mitra, R., Goswami, A.K., Tiwari, P.K.: ‘Voltage sag assessment using type-2 fuzzy system considering uncertainties in distribution system’, IET Gener. Transm. Distrib., 2017, 11, (6), pp. 14091419.
    16. 16)
      • 26. Cheng, L., Chang, Y., Huang, R.: ‘Mitigating voltage problem in distribution system with distributed solar generation using electric vehicles’, IEEE Trans. Sustain. Energy, 2015, 6, (4), pp. 14751484.
    17. 17)
      • 13. Wijekoon, H.M., Vilathgamuwa, D.M., Choi, S.S.: ‘Interline dynamic voltage restorer: an economical way to improve interline power quality’, IEE Proc., Gener. Transm. Distrib., 2003, 150, (5), pp. 513520.
    18. 18)
      • 2. Vegunta, S.C., Milanovic, J.V.: ‘Estimation of cost of downtime of industrial process due to voltage sags’, IEEE Trans. Power Deliv., 2011, 26, (2), pp. 576587.
    19. 19)
      • 21. Liao, H., Milanović, J.V.: ‘On capability of different FACTS devices to mitigate a range of power quality phenomena’, IET Gener. Transm. Distrib., 2017, 11, (5), pp. 12021211.
    20. 20)
      • 14. Patel, D., Goswami, A.K., Singh, S.K.: ‘Voltage sag mitigation in an Indian distribution system using dynamic voltage restorer’, Electr. Power Energy Syst., 2015, 71, pp. 231241.
    21. 21)
      • 22. Hosseini, S.A., Madahi, S.S.K., Razavi, F., et al: ‘Optimal sizing and siting distributed generation resources using a multiobjective algorithm’, Turk. J. Electr. Eng. Comput. Sci., 2013, 21, pp. 825850.
    22. 22)
      • 15. Rauf, A.M., Khadkikar, V.: ‘An enhanced voltage sag compensation scheme for dynamic voltage restorer’, IEEE Trans. Ind. Electron., 2015, 62, (5), pp. 26832692.
    23. 23)
      • 12. Khera, P.P., Dickey, K.C.: ‘Analysis and mitigation of voltage disturbances at an industrial customer's corporate campus’, IEEE Trans. Ind. Appl., 1998, 34, (5), pp. 893896.
    24. 24)
      • 34. IEEE Std. 1346-1998: ‘IEEE recommended practice for evaluating electric power system compatibility with electronic process equipment’.
    25. 25)
      • 27. Math, B., Fainan, H.: ‘Integration of distributed generation in the power system’ (A John-wiley & Sons, Inc. Publication, Hoboken, NJ, USA, 2011).
    26. 26)
      • 25. Chan, J.Y., Milanović, J.V.: ‘Assessment of the economic value of voltage sag mitigation devices to sensitive industrial plants’, IEEE Trans. Power Deliv., 2015, 30, (6), pp. 23742382.
    27. 27)
      • 32. Hertem, D.V., Didden, M., Driesen, J., et al: ‘Choosing the correct mitigation method against voltage dips and interruptions: a customer-based approach’, IEEE Trans. Power Deliv., 2007, 22, (1), pp. 331339.
    28. 28)
      • 1. Milanovic, J.V., Gupta, C.P.: ‘Probabilistic assessment of financial losses due to interruptions and voltage sags-part I: the methodology’, IEEE Trans. Power Deliv., 2006, 21, (2), pp. 918924.
    29. 29)
      • 8. Cebrian, J.C., Milanović, J.V., Kagan, N.: ‘Probabilistic assessment of financial losses in distribution network due to fault-induced process interruptions considering process immunity time’, IEEE Trans. Power Deliv., 2015, 30, (3), pp. 14781486.
    30. 30)
      • 11. Arias-Guzmán, S., Ruiz-Guzmán, O.A., Garcia-Arías, L.F., et al: ‘Analysis of voltage sag severity case study in an industrial circuit’, IEEE Trans. Ind. Appl., 2017, 53, (1), pp. 1521.
    31. 31)
      • 17. Zhan, Y.Q., Choi, S.S., Mahinda Vilathgamuwa, D.: ‘A voltage-sag compensation scheme based on the concept of power quality control center’, IEEE Trans. Power Deliv., 2006, 21, (1), pp. 296304.
    32. 32)
      • 9. Liao, H., Abdelrahman, S., Guo, Y., et al: ‘Identification of weak areas of power network based on exposure to voltage sags—part I: development of sag severity index for single-event characterization’, IEEE Trans. Power Deliv., 2015, 30, (6), pp. 23922400.
    33. 33)
      • 23. Cavalcanti, M.C., Limongi, L.R., Gomes, M.D.B., et al: ‘Eight-switch power conditioner for current harmonic compensation and voltage sag mitigation’, IEEE Trans. Ind. Electron., 2015, 62, (8), pp. 46544664.
    34. 34)
      • 7. Chan, J.Y., Milanović, J.V., Delahunty, A.: ‘Risk-based assessment of financial losses due to voltage sag’, IEEE Trans. Power Deliv., 2011, 26, (2), pp. 492500.
    35. 35)
      • 16. Chang, C.S., Yu, Z.: ‘Distributed mitigation of voltage sag by optimal placement of series compensation devices based on stochastic assessment’, IEEE Trans. Power Syst., 2004, 19, (2), pp. 788795.
    36. 36)
      • 5. Milanović, J.V., Zhang, Y.: ‘Modelling of FACTS devices for voltage sag mitigation studies in large power systems’, IEEE Trans. Power Deliv., 2010, 25, (4), pp. 30443052.
    37. 37)
      • 10. Liao, H., Abdelrahman, S., Guo, Y., et al: ‘Identification of weak areas of network based on exposure to voltage sags—part II: assessment of network performance using sag severity index’, IEEE Trans. Power Deliv., 2015, 30, (6), pp. 24012409.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-rpg.2018.5289
Loading

Related content

content/journals/10.1049/iet-rpg.2018.5289
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading