Optimisation for unit restarting sequence considering decreasing trend of unit start-up efficiency after a power system blackout

Xueping Gu; Wenxuan Liu; Cong Sun

Optimisation for unit restarting sequence considering decreasing trend of unit start-up efficiency after a power system blackout

View Fulltext

Author(s): Xueping Gu ¹ ; Wenxuan Liu ¹ ; Cong Sun ¹
- Affiliations: 1: School of Electrical and Electronic Engineering, North China Electric Power University, Baoding, Hebei Province, 071003, People's Republic of China
Source: Volume 10, Issue 16, 08 December 2016, p. 4187 – 4196
DOI: 10.1049/iet-gtd.2016.0797 , Print ISSN 1751-8687, Online ISSN 1751-8695

Received 25/05/2016, Accepted 20/08/2016, Revised 31/07/2016, Published 08/12/2016

The unit start-up efficiency, which has a great effect on unit start-up time and rapidity of connecting to the grid, will decline with time elapse after outages. In this context, an optimisation method for unit restarting sequence is proposed in this study. The temperature of steam-turbine cylinder is selected as an index to indicate the unit status. According to diverse temperature drop trend of steam-turbine cylinders with time, a fuzzy membership function is designed to describe the start-up time of unit in different status, and the time of unit's start-up is estimated. The sum of the equivalent ramp rates for restorable units is employed as the optimisation objective. Based on the average attenuation rate of unit start-up efficiency, a ranking principle is defined to select the units to be recovered in each time stage. The optimisation model of unit restoration sequence is established, and the multiple population genetic algorithm is employed to obtain the optimal unit restoration sequence. The effectiveness of the proposed method is validated by the optimisation results on the New England 10-unit 39-bus power system and the southern power system of Hebei in China.

References

1. 1)
  - 6. UCTE: ‘Final Report of the Investigation Committee on the 28 September 2003 Blackout in Italy’, http://www.ucte.org/library/otherreports/20040427_UCTE_IC_ Final_report.pdf, accessed April 2004.
2. 2)
  - 35. Ren, Q., Li, B., Saroj, B., et al: ‘A BDI multi-agent approach for power restoration’. Proc. Int. Conf. Resilient Control Systems, Denver, Colorado, USA, August 2014, pp. 1–6.
3. 3)
  - 31. Lu, E., Wang, N., Qin, Z., et al: ‘Black-start strategy for power grids including fast cut thermal power units’. Proc. Int. Conf. Power and Energy Society, Vancouver, British Columbia, Canada, July 2013, pp. 1–5.
4. 4)
  - 19. Liu, C.C., Yamashita, K., Li, J., et al: ‘Learning to recognize vulnerable patterns of cascaded events’. Proc. Int. Conf. EPRI, Palo Alto, California, USA, February 2008, Technical Report.
5. 5)
  - 10. Hain, Y., Schweitzer, I.: ‘Analysis of the power blackout of June 8, 1995 in the Israel electric corporation’, Trans. Power Syst., 1997, 12, (4), pp. 1752–1758 (doi: 10.1109/59.627887).
6. 6)
  - 9. Rampurkar, V., Pentayya, P., Mangalvedekar, H.A., et al: ‘Cascading failure analysis for Indian power grid’, IEEE Trans. Smart Grid, 2016, 26, (3), pp. 1357–1366.
7. 7)
  - 13. Nagata, T., Sasaki, H.: ‘A multi-agent approach to power system restoration’, IEEE Trans. Power Syst., 2002, 17, (2), pp. 457–462 (doi: 10.1109/TPWRS.2002.1007918).
8. 8)
  - 12. Dobson, I., Kim, J., Wierzbicki, K.R.: ‘Testing branching process estimators of cascading failure with data from a simulation of transmission line outages’. Proc. Int. Conf. Risk Analysis, 2010, vol. 30, no. 4, pp. 650–662.
9. 9)
  - 5. Sun, W., Liu, C.C., Zhang, L.: ‘Optimal generator start-up strategy for bulk power system restoration’, IEEE Trans. Power Syst., 2011, 26, (3), pp. 1357–1366 (doi: 10.1109/TPWRS.2010.2089646).
10. 10)
  - 42. Tică, A., Gueguen, H., Dumur, D., et al: ‘Hierarchical nonlinear model predictive control for combined cycle start-up optimization’. Proc. Int. Conf. Decision and Control, Hawaii, USA, December 2012, pp. 2593–2598.
11. 11)
  - 26. Mota, A.A., Mota, L.T.M., Morelato, A.: ‘Visualization of power system restoration plans using CPM/PERT graphs’, IEEE Trans. Power Syst., 2007, 22, (3), pp. 1322–1329 (doi: 10.1109/TPWRS.2007.901118).
12. 12)
  - 5. IEEE PES Power System Dynamic Performance Committee: ‘Causes of the 2003 major grid blackouts in North America and Europe, and recommended means to improve system dynamic performance’, IEEE Trans. Power Syst., 2005, 20, (4), pp. 1922–1928 (doi: 10.1109/TPWRS.2005.857942).
13. 13)
  - 5. Berizzi, A.: ‘The Italian 2003 blackout’. Proc. Int. Conf. Power and Energy Society, Denver, Colorado, USA, June 2004, pp. 1673–1679.
14. 14)
  - 29. Liu, C.C., Liou, K.L., Chu, R.F., et al: ‘Generation capability dispatch for bulk power system restoration: a knowledge-based approach report’, IEEE Trans. Power Syst., 1993, 8, (1), pp. 316–325 (doi: 10.1109/59.221225).
15. 15)
  - 4. Corsi, S., Sabelli, C.: ‘General blackout in Italy Sunday September 28th, 2003, h 03:28:00’. Proc. Int. Conf. Power and Energy Society, Denver, Colorado, USA, June 2004, pp. 1691–1702.
16. 16)
  - 33. Sun, W., Liu, C.C.: ‘Optimal transmission path search in power system restoration’. Proc. Int. Conf. Bulk Power System Dynamics and Control, Rethymno, Greece, August 2013, pp. 1–5.
17. 17)
  - 13. Wang, H., Liu, Y.: ‘Research on the black start field test of Shandong power grid based on PDCA cycle’. Proc. Int. Conf. Electrical and Control Engineering, Wuhan, China, June 2010, pp. 4144–4148.
18. 18)
  - 27. Liu, Q., Ni, Y.X., Zhou, M., et al: ‘A new solution to generators start-up sequence during power system restoration’. Proc. Int. Conf. Electric Utility Deregulation and Restructuring and Power Technologies, Nanjing, China, April 2008, pp. 2845–2849.
19. 19)
  - 18. Dobson, I., Carreras, B.A., Newman, D.E.: ‘How many occurrences of rare blackout events are needed to estimate event probability?’, IEEE Trans. Power Syst., 2013, 28, (3), pp. 3509–3510 (doi: 10.1109/TPWRS.2013.2242700).
20. 20)
  - 24. Gu, X., Zhong, H.: ‘Optimisation of network reconfiguration based on a two-layer unit-restarting framework for power system restoration’, IET Gener. Transm. Distrib., 2012, 6, (7), pp. 693–700 (doi: 10.1049/iet-gtd.2011.0591).
21. 21)
  - 2. U.S.-Canada Power System Outage Task Force: ‘Final Report on the August 14th blackout in the United States and Canada’, https://reports.energy.gov/BlackoutFinal-Web.pdf, accessed April 2004.
22. 22)
  - 41. Winterton, R.H.S.: ‘Newton's law of cooling’, Contemporary Phys., 1999, 40, (3), pp. 205–212 (doi: 10.1080/001075199181549).
23. 23)
  - 44. Aziz, A.M.: ‘Effects of fuzzy membership function shapes on clustering performance in multisensor-multitarget data fusion systems’. Proc. Int. Conf. Fuzzy Systems, Jeju Island, Korea, August 2009, pp. 1839–1844.
24. 24)
  - 30. Liu, C.C., Wu, M., Deng, Y.: ‘Start-up sequence of generators in power system restoration avoiding the backtracking algorithm’. Proc. Int. Conf. Power and Energy Society, Vancouver, British Columbia, Canada, July 2013, pp. 1–5.
25. 25)
  - 36. Liao, S., Wei, Y., Han, X., et al: ‘Two-stage optimization method for network reconfiguration and load recovery during power system restoration’. Proc. Int. Conf. Power and Energy Society, Denver, Colorado, USA, July 2015, pp. 1–5.
26. 26)
  - 18. Liu, W., Lin, Z., Wen, F., et al: ‘A wide area monitoring system based load restoration method’, IEEE Trans. Power Syst., 2013, 28, (2), pp. 2025–2034 (doi: 10.1109/TPWRS.2013.2249595).
27. 27)
  - 25. Adibi, M.: ‘Development of a knowledge based system for power system restoration’ (Wiley-IEEE Press, 2009), pp. 443–449.
28. 28)
  - 20. Datta, S., Kolluri, S., He, T., et al: ‘Development of an alternative black- start plan for system restoration’. Proc. Int. Conf. Power Systems Conf. and Exposition, Atlanta, Georgia, USA, October 2006, pp. 1833–1839.
29. 29)
  - 43. Albanesi, C., Bossi, L., Magni, J., et al: ‘Optimization of the start-up procedure of a combined cycle power plant’. Proc. Int. Conf. Decision and Control, California, USA, December 2006, pp. 1840–1845.
30. 30)
  - 3. Larsson, S., Erik, E.: ‘The blackout in Southern Sweden and Eastern Denmark, September 23, 2003’. Proc. Int. Conf. Power and Energy Society, Denver, Colorado, USA, June 2004, pp. 1668–1672.
31. 31)
  - 7. UCTE: ‘Final Report on the Disturbances of 4 November 2006’, http://www.ucte.org/library/otherreports/Final-Report-20070130.pdf, accessed January 2007.
32. 32)
  - 24. Liang, H., Gu, X., Zhao, D.: ‘Optimization of system partitioning schemes for power system black-start restoration based on genetic algorithms’. Proc. Int. Conf. Power and Energy Engineering, Chengdu, China, March 2010, pp. 1–4.
33. 33)
  - 23. El-Zonkoly, A., Desouki, H., Farghaly, A.: ‘Firefly based approach for optimal power system black-start restoration’. Proc. Int. Conf. Electric Power Engineering, 2014, pp. 11–16.
34. 34)
  - 25. Ye, H., Liu, Y.: ‘A new method for standing phase angle reduction in system restoration by incorporating load pickup as a control means’, Int. J. Electr. Power, 2013, 53, pp. 664–674 (doi: 10.1016/j.ijepes.2013.05.039).
35. 35)
  - 14. Fendin, H., Hansen, T., Hemmingsson, M., et al: ‘Black start test of the Swedish power system’. Proc. Int. Conf. PowerTech, Trondheim, Norway, June 2011, pp. 1–5.
36. 36)
  - 32. Shen, C., Paul, K., Martin, B.: ‘Optimizing the generator start-up sequence after a power system blackout’. Proc. Int. Conf. Power and Energy Society, National Harbor, Maryland, USA, July 2014, pp. 1–5.
37. 37)
  - 17. Yamashita, K., Li, J., Zhang, P., et al: ‘Analysis and control of major blackout events’. Proc. Int. Conf. Power Systems and Exposition, Seattle, USA, March 2009, pp. 1–4.
38. 38)
  - 8. Romero, J.J.: ‘Blackouts illuminate India's power problems’, IEEE Spectrum, 2012, 49, (10), pp. 11–12 (doi: 10.1109/MSPEC.2012.6309237).
39. 39)
  - 21. Negnevitsky, M., Voropai, N., Kurbatsky, V.: ‘Development of an intelligent system for preventing large-scale emergencies in power systems’. Proc. Int. Conf. Power and Energy Society, Vancouver, British Columbia, Canada, July 2013, pp. 1–5.
40. 40)
  - 45. Lei, Y., Li, S., Nan, X., et al: ‘Industrial enterprise distribution network planning based on multiple population genetic algorithm’. Proc. Int. Conf. Power System Technology, Chengdu, China, October 2014, pp. 550–555.
41. 41)
  - 38. Qin, Z., Hou, Y., Liu, C., et al: ‘Coordinating generation and load pickup during load restoration with discrete load increments and reserve constraints’, IET Gener. Transm. Distrib., 2015, 9, (15), pp. 2437–2446 (doi: 10.1049/iet-gtd.2015.0240).
42. 42)
  - 40. Henshaw, R.E., Robert, E.: ‘Thermoregulation during hibernation: application of Newton's law of cooling’, J. Theor. Biol., 1968, 20, (1), pp. 79–90 (doi: 10.1016/0022-5193(68)90093-3).
43. 43)
  - 5. Daggle, J.E.: ‘Postmortem analysis of power grid blackouts-the role of measurement systems’, IEEE Power Energy Mag., 2006, 4, (5), pp. 30–35 (doi: 10.1109/MPAE.2006.1687815).
44. 44)
  - 39. Xia, Y.: ‘Simulation system on the thermal stress and fatigue life loss of startup and shutdown for a domestic 600 MW steam turbo generator unit’. Proc. Int. Conf. Energy and Environment Technology, Guilin, Guangxi, China, October 2009, pp. 818–823.
45. 45)
  - 11. Kim, J., James, A.B., Dobson, I.: ‘Splitting method for speedy simulation of cascading blackouts’, IEEE Transactions on Power Systems, 2013, 28, (3), pp. 3010–3017 (doi: 10.1109/TPWRS.2012.2231887).

Login

Not registered yet?

Share

Tools

Login to add to favourites

Key

Optimisation for unit restarting sequence considering decreasing trend of unit start-up efficiency after a power system blackout

References

Related content