This study presents a model based on partial least squares (PLS) regression for dynamic line rating (DLR). The model has been verified using data from field measurements, lab tests and outdoor experiments. Outdoor experimentation has been conducted both to verify the model predicted DLR and also to provide training data not available from field measurements, mainly heavily loaded conditions. The proposed model, unlike the direct measurement based DLR techniques, enables prediction of line rating for periods ahead of time whenever a reliable weather forecast is available. The PLS approach yields a very simple statistical model that accurately captures the physical performance of the conductor within a given environment without requiring a predetermination of parameters as required by many physical modelling techniques. Accuracy of the PLS model has been tested by predicting the conductor temperature for measurement sets other than those used for training. Being a linear model, it is straightforward to estimate the conductor ampacity for a set of predicted weather parameters. The PLS estimated ampacity has proven its accuracy through an outdoor experiment on a piece of the line conductor in real weather conditions.

References

1. 1)
  - 16. Working Group 22.12, CIGRE: ‘Thermal behaviour of overhead conductors’, 2002.
2. 2)
  - 19. Abdelhader, S., Abbott, S., Fu, J., et al: ‘Dynamic monitoring of overhead line rating in wind intensive areas’, Proc. European Wind Energy Conf. and Exhibition (EWEA 2009), France, March 2009.
3. 3)
  - 12. Price, C., Gibbon, R.: ‘Statistical approach to thermal rating of overhead lines for power transmission and distribution’, IEE Gener. Transm. Distrb., 1983, 130, pp. 245–256 (doi: 10.1049/ip-c.1983.0047).
4. 4)
  - P. Geladi , B.R. Kowalski . Partial least-squares regression – a tutorial. Anal. Chim. Acta , 1 - 17
5. 5)
  - 1. Department of Energy and Climate Change: ‘UK renewable energy roadmap’, 2011. Available at: http://www.decc.gov.uk/assets/decc/11/meeting-energy-demand/renewable-energy/2167-uk-renewable-energy-roadmap.pdf.
6. 6)
  - 13. Hall, J., Deb, A., Savoullis, J.: ‘Wind tunnel studies of transmission line conductor temperatures’, IEEE Trans. PWRD, 1988, 3, pp. 801–812.
7. 7)
  - 16. Working Group 22.12, CIGRE: ‘Thermal behaviour of overhead conductors’, 2002.
8. 8)
  - 17. Morgan, V.T.: ‘The current carrying capacities of overhead line conductors’. Paper A75 575–3, IEEE/PES Summer Meeting, Los Angeles, CA, 1978.
9. 9)
  - 4. Engelhardt, J., Basu, S.: ‘Design, installation, and field experience with an overhead transmission dynamic line rating system’. IEEE Proc. Transmission and Distribution Conf., 1996, pp. 366–370.
10. 10)
  - 11. Foss, S.D., Lin, S.H., Carberry, R.: ‘Significance of the conductor radial temperature gradient within a dynamic line rating methodology’, IEEE Trans. PWRD, 1987, 2, pp. 502–511.
11. 11)
  - 5. Mensah-Bonsu, C., Heydt, G.T.: ‘Real-time digital processing of GPS measurements for transmission engineering’, IEEE Trans. PWRD, 2003, 18, pp. 177–182.
12. 12)
  - 8. Liao, Y.: ‘Power transmission line parameter estimation and optimal meter placement’. Proc. IEEE Southeast Conf., 2010, 2010, pp. 250–254.
13. 13)
  - 7. Mahajan, S.M., Singareddy, U.M.: ‘A real-time conductor sag measurement system using a differential GPS’, IEEE Trans. PWRD, 2012, 27, pp. 475–480.
14. 14)
  - 9. Albizu, I., Fernandez, V., Eguia, P., Torres, E., Mazón, A.J.: ‘Tension and ampacity monitoring system for overhead lines’, IEEE Trans. PWRD, 2013, 28, pp. 3–10.
15. 15)
  - 3. Foss, S.D., Maraio, R.: ‘Dynamic line rating in the operating environment’, IEEE Trans. PWRD, 1990, 5, pp. 1095–1105.
16. 16)
  - 15. IEEE T & D Committee: ‘IEEE standard for calculating the current-temperature of bare overhead conductors’. IEEE Standard 738, 2007.
17. 17)
  - 19. Abdelhader, S., Abbott, S., Fu, J., et al: ‘Dynamic monitoring of overhead line rating in wind intensive areas’, Proc. European Wind Energy Conf. and Exhibition (EWEA 2009), France, March 2009.
18. 18)
  - 12. Price, C., Gibbon, R.: ‘Statistical approach to thermal rating of overhead lines for power transmission and distribution’, IEE Gener. Transm. Distrb., 1983, 130, pp. 245–256 (doi: 10.1049/ip-c.1983.0047).
19. 19)
  - 1. Department of Energy and Climate Change: ‘UK renewable energy roadmap’, 2011. Available at: http://www.decc.gov.uk/assets/decc/11/meeting-energy-demand/renewable-energy/2167-uk-renewable-energy-roadmap.pdf.
20. 20)
  - 14. Fu, J., Abbott, S., Fox, B., Morrow, D., Abdelkader, S.: ‘Wind cooling effect on dynamic overhead line ratings’. Proc. 45th Int. Universities Power Engineering Conf. (UPEC), 2010, pp. 1–6.
21. 21)
  - 6. Mensah-Bonsu, C., Krekeler, U.F., Heydt, G.T., Hoverson, Y., Schilleci, J., Agrawal, B.L.: ‘Application of the global positioning system to the measurement of overhead power transmission conductor sag’, IEEE Trans. PWRD, 2002, 17, pp. 273–278.
22. 22)
  - 21. Morgan, V.T.: ‘The radial temperature distribution and effective radial thermal conductivity in bare solid and stranded conductors’, IEEE Trans. PWRD, 1990, 5, pp. 1443–1452.
23. 23)
  - 18. Geladi, P., Kowalski, B.R.: ‘Partial least-squares regression: a tutorial’, Anal. Chim. Acta, 1986, 185, pp. 1–17 (doi: 10.1016/0003-2670(86)80028-9).
24. 24)
  - 2. Howington, B., Ramon, G.: ‘Dynamic thermal line rating summary and status of the state-of-the-art technology’, IEEE Tran. PWRD, 1987, 2, pp. 851–858.
25. 25)
  - 10. Deb, A.K.: ‘Power line ampacity system’ (CRC Press LLC, 2000), pp. 63–66.
26. 26)
  - 20. Black, W.Z., Collins, S.S., Hall, J.F.: ‘Theoretical model for temperature gradients within bare overhead conductors’, IEEE Trans. PWRD, 1988, 3, pp. 707–715.

Experimentally validated partial least squares model for dynamic line rating

References

Related content