Improve of Human Reliability by Identifying and Evaluating Potential and Actual Roots of Maintenance Team Errors in the Power Transmission Grids

Subject Areas : Renewable energy

Mehdi  Tavakoli ¹ (Department of Electrical Engineering- Marvdasht Branch, Islamic Azad University, Marvdasht, Iran)
Mehdi  Nafar ² (Department of Electrical Engineering- Marvdasht Branch, Islamic Azad University, Marvdasht, Iran)

Received: 2020-12-06 Accepted : 2021-01-28 Published : 2021-08-23

Keywords: maintenance groups, human error, classification system method, human factors analysis, power transmission,

Abstract :

Human life and the economy of a country are becoming more and more dependent on electricity. However, events that occur due to various factors in the power grids, affect the quality of electrical energy delivered to subscribers. The human error of maintenance teams is one of the most important causes of automatic outputs of electrical equipment. Human error, in addition to the economic consequences of not transiting electrical energy due to equipment outages, may also cause health damage to personnel. The purpose of this study is to propose a method for analyzing the human reliability of maintenance teams in power transmission grids, which has been implemented as a case study on power transmission grids teams in Fars. The first step is to identify the roots of human error. So far, no comprehensive studies have been conducted on the root causes of human error in power transmission grids. Therefore, in this article, the actual and potential roots of various aspects such as organization, individual moods, supervision, etc. are identified and predicted in the framework of the method of human factors analysis and classification system. Then, a method is proposed to estimate the probability of the root event to use its results to prioritize the necessary control and corrective measures to reduce human error.

References:

[1] H.H. Alhelou, M.E. Hamedani-Golshan, T.C. Njenda, P. Siano, “A survey on power system blackout and cascading events: Research motivations and challenges”, Energies, vol. 12, no. 4, pp. 682, 2019 (doi: /10.33­9­0/e­n12040682).

[2] M. Prasad, A.J. Gaikwad, “Human error probability estimation by coupling simulator data and deterministic analysis”, Progress in Nuclear Energy, vol. 8, pp. 22-29, May 2015 (doi: 10.1016/j.pnucene.2015.01.008).

[3] O.P. Veloza, F. Santamaria, “Analysis of major blackouts from 2003 to 2015: Classification of incidents and review of main causes”, The Electricity Journal, vol. 29, no. 7, pp. 42-49, Sept. 2016 (doi: 10.1016/j.te­j.20­1­6.­08.006).

[4] Z. Wang, M. Rahnamay-Naeini, J.M. Abreu, R.A. Shuvro, P. Das, A.A. Mammoli, N. Ghani, M.M. Hayat, “Impacts of operators’ behavior on reliability of power grids during cascading failures”, IEEE Trans. on Power Systems, vol. 33, no. 6, pp. 6013–6024, Nov. 2018 (doi: 10.1109/TPWRS.2018.2825348).

[5] Y. Bao, J. Guo, J. Tang, Z. Li, S. Pang, C. Guo, “Analysis of power system operation reliability incorp­ora­ti­n­g human errors”, Proceeding of the IEEE/ICEMS, pp. 1052-1056, Hangzhou, China, Oct. 2014 (doi: 10.11­0­9/IC­EMS.2014.7013625).

[6] J. Tang, Y. Bao, L. Wang, H. Lu, Y. Wang, C. Guo, J. Liu, B. Zhou, “A Bayesian network approach for human reliability analysis of power system”, Proceeding of the IEEE/APPEEC, pp. 1-6, Kowloon, China, Dec. 2013 (doi: 10.1109/APPEEC.2013.6837128).

[7] R. Peach, H. Ellisl, J.K. Visserl, “A maintenance performance measurement framework that includes maintenance human factors: a case study from the electricity transmission industry”, South African Journal of Industrial Engineering, vol. 27, no. 2, pp. 177-189, Aug. 2016 (doi: 10.7166/27-2-1492).

[8] H. Silva-Santos, T. Araújo-dos-Santos, A.S. Alves, M.N. Silva, H.O.G. Costa, C.M.M. Melo, “Error-producing conditions in nursing staff work”, Rev Bras Enferm., vol. 71, no. 4, pp. 1858-1864, Jul-Aug. 2018 (doi:10.1590/0034-7167-2017-0192).

[9] H. Akbari, M. Motalebi-Kashani, Z. Asadi, M. Kaveh, H. Saberi , “The relationship between job satisfaction and the incidence of unsafe acts in metal smelting industry workers in 2017”, International Archives of Health Sciences, vol. 6, no. 3, pp. 127-13, Jan. 2019 (doi: 10.4103/iahs.iahs_40_19).

[10] B. Song, Z. Wang, Y. Lu, X. Teng, X. Chen, Y. Zhou, H. Ye, S. Fu, “A multidimensional workload assessment method for power grid dispatcher”, Proceeding of the EPCE, pp: 55-68, Las Vegas, USA, July 2018 (doi: 10.1007/978-3-319-91122-9_5).

[11] Y. Bao, C. Guo, J. Zhang, J. Wu, S. Pang, Z. Zhang, “Impact analysis of human factors on power system operation reliability”,  Modern Power Systems and Clean Energy, vol. 6, no. 1, pp. 27–39, Jan. 2018 (doi: 10.1007/s40565-016-0231-6).

[12] L. Peng-cheng, Ch. Guo-hua, D. Li-cao, Z. Li, “A fuzzy Bayesian network approach to improve the quantification of organizational influences in HRA frameworks”, Safety Science, vol. 50, no. 7, pp. 1569-1583, Aug. 2012 (doi: 10.1016/j.ssci.2012.03.017).

[13] X. Pan, Y. Lin, C. He, “A review of cognitive models in human reliability analysis”, Quality and Reliability Engineering International, vol. 33,  no. 7, pp. 1299-1316, Nov. 2017 (doi: 10.1002/qre.2111).

[14] “Fars power transmission network events analysis report-2018”, FREC annual report, 2018 (in Persian).

[15] V.N. Aju kumar, M.S. Gandhib, O.P. Gandhic, “Identification and assessment of factors influencing human reliability in maintenance using fuzzy cognitive maps”, Quality and Reliability Engineering International, vol. 31, no. 2, pp. 169-181, Mar. 2015 (doi: 10.1002/qre.1569).

[16] V.N. Aju kumar, O.P. Gandhi, “Quantification of human error in maintenance using graph theory and matrix approach”, Quality and Reliability Engineering International, vol. 27, no. 8, pp. 1145-1172, Dec. 2011 (doi: 10.1002/qre.1202).

[17] P.M. Salmon, M. Cornelissen, M.J. Trotter, “Systems-based accident analysis methods: A comparison of Accimap, HFACS and STAMP”, Safety Science, vol. 50, no. 4, pp. 1158–1170, Apr. 2012 (doi: 10.10­16/j.­ssc­i.2011.11.009).

[18] M.T. Baysari, C. Caponecchia, A.S. McIntosh, J.R. Wilson, “Classification of errors contributing to rail incidents and accidents: A comparison of two human error identification techniques”, Safety Science, vol. 47, no. 7,  pp. 948-957, Aug. 2009 (doi: 10.1016/j.ssci.2008.09.012).

[19] A.Y. Daramola, “An investigation of air accidents in Nigeria using the Human Factor Analysis and Classification System framework”, Journal of Air Transport Management, vol. 35, pp. 39-50, Mar. 2014 (doi: 10.1016/j.jairtraman.2013.11.004).

[20] T. Diller, G. Helmrich, S. Dunning, S. Cox, A. Buchanan, S. Shappell, “The Human Factors Analysis Classification System (HFACS) applied to health care”, Am J Med Qual., vol. 29, no. 3, pp. 181-190, May-June 2014 (doi: 10.1177/1062860613491623).

[21] S.A. Shappell, D.A. Wiegmann, “Applying reason: the human factors analysis and classification system (HFACS)”, Human Factors and Aerospace Safety, vol. 1, no. 1, pp. 59–86, Jan. 2001.

[22] S.W.A. Dekker, “Reconstructing human contributions to accidents: the new view on error and perform­ance”, Safety Research, vol. 33, no. 3,  pp. 371-385, Oct. 2002 (doi: 10.1016/S0022-4375(02)00032-4).

[23] A. Boquet, C. Detwiler, S. Shappell, “A human factors analysis of U.S. emergency medical transport accidents”, Air medical journal, vol. 23, no. 5 pp. 34-44, Sept. 2004 (doi: 10.1016/j.amj.2004.08.014).

[24] G. Grigoraş, C. Bărbulescu, “Human errors monitoring in electrical transmission networks based on a partitioning algorithm”, Electrical Power & Energy Systems, vol. 49, pp. 128-136, Jul. 2013 (doi: 10.101­6/j.i­jepes.2012.12.016).

[25] V.R. Renjith, G. Madhu, V.L.G. Nayagam, A.B. Bhasi, “Two-dimensional fuzzy fault tree analysis for chlorine release from a chlor-alkali industry using expert elicitation”, Journal of Hazardous Materials,  vol. 183, no. 1-3, pp. 103-110, Nov. 2010 (doi:10.1016/j.jhazmat.2010.06.116).