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Impact of health indicators on maintenance management and operation of power systems

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  • Peyman Mazidi
  • Miguel A Sanz Bobi
  • Ebrahim Shayesteh
  • Patrik Hilber

Abstract

This article proposes a maintenance management and risk reduction approach. The approach introduces two reliability-based indexes called condition indicator and risk indicator. Condition indicator is a unit-less parameter that comes directly from monitored condition of a component and converts the categorical condition into a numerical value. Risk indicator in megawatt represents the risk imposed by the health of a component onto the system. To demonstrate application of the indicators, they are implemented through an hourly network constraint unit commitment problem and applied in a test system where the analysis of impact of condition of the generators to the operation is the new contribution. The results demonstrate how addition of such indicators will impact the operation of the grid and maintenance scheduling. The results show the benefit for the system operator as the overall failure risk in the system is taken into account, and the benefit for the asset owner as the direct impact of the maintenance to be carried out can be investigated. Two of the main outcomes of the maintenance management and risk reduction approach are as follows: asset owners can analyze their maintenance strategies and evaluate their impacts in the maintenance scheduling, and system operators can operate the grid with higher security and lower risk of failure.

Suggested Citation

  • Peyman Mazidi & Miguel A Sanz Bobi & Ebrahim Shayesteh & Patrik Hilber, 2017. "Impact of health indicators on maintenance management and operation of power systems," Journal of Risk and Reliability, , vol. 231(6), pages 716-731, December.
    • Handle: RePEc:sae:risrel:v:231:y:2017:i:6:p:716-731
    DOI: 10.1177/1748006X17731901
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    1. D. G. Nguyen & D. N. P. Murthy, 1981. "Optimal Preventive Maintenance Policies for Repairable Systems," Operations Research, INFORMS, vol. 29(6), pages 1181-1194, December.
    2. Dahal, Keshav & Al-Arfaj, Khalid & Paudyal, Krishna, 2015. "Modelling generator maintenance scheduling costs in deregulated power markets," European Journal of Operational Research, Elsevier, vol. 240(2), pages 551-561.
    3. Wang, Hongzhou, 2002. "A survey of maintenance policies of deteriorating systems," European Journal of Operational Research, Elsevier, vol. 139(3), pages 469-489, June.
    4. Peyman Mazidi & Yaser Tohidi & Miguel A. Sanz-Bobi, 2017. "Strategic Maintenance Scheduling of an Offshore Wind Farm in a Deregulated Power System," Energies, MDPI, vol. 10(3), pages 1-20, March.
    5. Volkanovski, Andrija & ÄŒepin, Marko & Mavko, Borut, 2009. "Application of the fault tree analysis for assessment of power system reliability," Reliability Engineering and System Safety, Elsevier, vol. 94(6), pages 1116-1127.
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    Cited by:

    1. Xia, Tangbin & Dong, Yifan & Xiao, Lei & Du, Shichang & Pan, Ershun & Xi, Lifeng, 2018. "Recent advances in prognostics and health management for advanced manufacturing paradigms," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 255-268.

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