Methodology for Developing a Maintenance Action Program for Power Units of Captive Power Plants Based on an Integrated Priority Indicator

The study develops and implements a methodology for prioritizing power units (PUs) of captive power plants (CPPs) to support the development of maintenance and repair (M&R) programs considering their actual technical condition (TC) and reliability indicators. The proposed approach is based on the joint assessment of the technical condition index (TCI), the consumed technical resource (CTR), and the risk level (RL) of the PUs. To describe the statistical patterns of failures, a two-parameter Weibull distribution is applied, while the temporal change in the TCI is approximated by a linear relationship that accounts for differences between actual and nominal operating conditions. The CTR is defined as an integral characteristic reflecting the deviation between the actual and nominal TCI degradation functions. The RL is evaluated as a function of the probability of failure and the consequences of PU failure. Based on these individual indicators, an integrated priority index is formed to provide an unambiguous ranking of PUs. The methodology was implemented using actual operational data from a fleet of PUs of an energy company. The results demonstrate that using the TCI alone does not fully reflect the actual TC of the PUs, whereas the combined consideration of TC, CTR, and RL enables a more justified formation of M&R programs. The practical significance of the study lies in the possibility of applying the developed methodology for reliability management of PUs at CPPs under resource constraints.

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Publication Details

Journal
Energies
Published
2026-03-23
DOI
https://doi.org/10.3390/en19061584
Primary Topic
Reliability and Maintenance Optimization
Type
article
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article

Methodology for Developing a Maintenance Action Program for Power Units of Captive Power Plants Based on an Integrated Priority Indicator

Konstantin Suslov, Aleksandr NAZARYCHEV, H. Beloev, Ivan Beloev et al.
Energies
Reliability and Maintenance Optimization
article

Methodology for Developing a Maintenance Action Program for Power Units of Captive Power Plants Based on an Integrated Priority Indicator

Konstantin Suslov, Aleksandr NAZARYCHEV, H. Beloev, Ivan Beloev, Daniel Manukian, Iliya Iliev
article en

Abstract

The study develops and implements a methodology for prioritizing power units (PUs) of captive power plants (CPPs) to support the development of maintenance and repair (M&R) programs considering their actual technical condition (TC) and reliability indicators. The proposed approach is based on the joint assessment of the technical condition index (TCI), the consumed technical resource (CTR), and the risk level (RL) of the PUs. To describe the statistical patterns of failures, a two-parameter Weibull distribution is applied, while the temporal change in the TCI is approximated by a linear relationship that accounts for differences between actual and nominal operating conditions. The CTR is defined as an integral characteristic reflecting the deviation between the actual and nominal TCI degradation functions. The RL is evaluated as a function of the probability of failure and the consequences of PU failure. Based on these individual indicators, an integrated priority index is formed to provide an unambiguous ranking of PUs. The methodology was implemented using actual operational data from a fleet of PUs of an energy company. The results demonstrate that using the TCI alone does not fully reflect the actual TC of the PUs, whereas the combined consideration of TC, CTR, and RL enables a more justified formation of M&R programs. The practical significance of the study lies in the possibility of applying the developed methodology for reliability management of PUs at CPPs under resource constraints.

EnergiesVol. 19(6)
Moscow Power Engineering Institute (RU), Saint Petersburg Mining University (RU), Irkutsk National Research Technical University (RU), Angel Kanchev University of Ruse (BG)
Openalex Percentile: Top 10%
Reliability and Maintenance Optimization
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