The Identification of Human Errors in the Power Dispatching Based on the TRACEr Method

  • Xiaobi Teng
  • Yanyu LuEmail author
  • Zhen Wang
  • Bingbing Song
  • Hai Ye
  • Yi Zhou
  • Shan Fu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10906)


Most of the power dispatching accidents were caused by human errors. Human error should be symptoms of systemic problems and opportunities to learn about the features of complex systems. Therefore, the identification and analysis of the human errors in the power dispatching is the significant to guide against the human risk and ensure the stable and safe operation of power nets. Human error identification methods have been used to identify the nature of the human errors and causal factors, and recovery strategies in many industrial domains such as the aviation, nuclear power and chemical processing industries. The Technique for Retrospective and Predictive Analysis of Cognitive Errors (TRACEr) is a human error identification technique that was developed for use in the air traffic control domain. In this study, the TRACEr was improved in the combination of the task features of the power dispatching and human information processing, and was used to identify the human errors in the power dispatching. A total of seventy-two incidents or accidents performed by operators were analyzed. The analyzing processing was carried out with the objective of classifying task error, identifying external error modes, internal error modes and psychological error mechanisms, and identifying the performance shaping factors. The performance factors analysis considered the time, interface, training and experience, procedures, organization, stress and complexity which may have an impact to the task and help to propose some recovery strategies. The results revealed that the identification was a necessary and effective step toward the safety improvement of power dispatching.


Human factors Power dispatching Human error identification 


  1. 1.
    Yang, F., Wu, C., Wang, F., Ma, S.: Review of studies on human reliability researches during 1998 to 2008. Sci. Technol. Rev. 27(8), 87–94 (2009)Google Scholar
  2. 2.
    Stanton, N.A., Salmon, P.M., Rafferty, L.A., Walker, G.H., Baber, C.: Human Factors Methods: A Practical Guide for Engineering and Design. Ashgate Publishing Limited, Farnham (2013)CrossRefGoogle Scholar
  3. 3.
    Reason, J.: Human Error. Cambridge University Press, Cambridge (1990)CrossRefGoogle Scholar
  4. 4.
    Dekker, S.: The Field Guide to Understanding Human Error. Ashgate Publishing Company, Farnham (2006)Google Scholar
  5. 5.
    Marshall, A., Stanton, N., Young, M., Salmon, P., Harris, D., Demagalski, J., Waldmann, T., Dekker, S.: Development of the human error template–a new methodology for assessing design induced errors on aircraft flight decksGoogle Scholar
  6. 6.
    Kletz, T.A.: HAZOP and HAZAN: notes on the identification and assessment of hazards. J. Hazard. Mater. 8(4), 385–386 (1984)CrossRefGoogle Scholar
  7. 7.
    Swann, C.D., Preston, M.L.: Twenty-five years of HAZOPs. J. Loss Prev. Process Ind. 8(6), 349–353 (1995)CrossRefGoogle Scholar
  8. 8.
    Hollnagel, E.: Cognitive Reliability and Error Analysis Method (CREAM). Elsevier, Oxford (1998)Google Scholar
  9. 9.
    Kirwan, B.: A guide to practical human reliability assessment. Int. J. Ind. Ergon. 17(1), 69 (1994)Google Scholar
  10. 10.
    Shappell, S.A., Wiegmann, D.A.: A human error approach to accident investigation: the taxonomy of unsafe operations. Int. J. Aviat. Psychol. 7(4), 269–291 (1997)CrossRefGoogle Scholar
  11. 11.
    Shappell, S.A., Wiegmann, D.A.: The human factors analysis and classification system-HFACS. Am. Libr. 1(1), 20–46 (2000)Google Scholar
  12. 12.
    Shorrock, S.T., Kirwan, B.: Development and application of a human error identification tool for air traffic control. Appl. Ergon. 33(4), 319–336 (2002)CrossRefGoogle Scholar
  13. 13.
    Baysari, M.T., Caponecchia, C., Mcintosh, A.S., Wilson, J.R.: Classification of errors contributing to rail incidents and accidents: a comparison of two human error identification techniques. Saf. Sci. 47(7), 948–957 (2009)CrossRefGoogle Scholar
  14. 14.
    Hofmann, S., Schröder-Hinrichs, J.U.: CyClaDes Task 1.2 Incident and accident analysis. Document ID Code: CY112. 00.02. 041.041, WMU (2013)Google Scholar
  15. 15.
    Graziano, A., Teixeira, A.P., Soares, C.G.: Classification of human errors in grounding and collision accidents using the TRACEr taxonomy. Saf. Sci. 86, 245–257 (2016)CrossRefGoogle Scholar
  16. 16.
    Wickens, C.D.: Engineering Psychology and Human Performance. Charles E. Merrill Publishing Company, Columbus (1992)Google Scholar
  17. 17.
    Guttromson, R.T., Schur, A., Greitzer, F.L., Paget, M.L.: Human factors for situation assessment in grid operations (2007)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Xiaobi Teng
    • 2
  • Yanyu Lu
    • 1
    Email author
  • Zhen Wang
    • 1
  • Bingbing Song
    • 2
  • Hai Ye
    • 2
  • Yi Zhou
    • 2
  • Shan Fu
    • 1
  1. 1.School of Electronics, Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghaiChina
  2. 2.East China Branch of State Grid Corporation of ChinaShanghaiChina

Personalised recommendations