Development of Maintainability Metrics for Power Systems
DOI:
https://doi.org/10.25729/esr.2026.01.0007Keywords:
power system, maintainability, adequacy,, maintenance scheduling, partial integer programming, Monte Carlo simulationsAbstract
This study focuses on developing methods to assess the optimality of maintenance campaign in terms of various criteria and the effect of maintenance on power system reliability. The assessment is based on a new set of metrics represented by power system maintainability indices. Adequacy metrics, in general, are ill-suited to deal with this problem: although the scope of power system adequacy assessment covers maintenance, the way it is done is either rudimentary or limited to a pre-specified list of maintenance requests. This study is centered on maintenance scheduling.
Several metrics of power system maintainability are conceptualized, detailed, and tested. The analysis of the metrics employs Monte Carlo simulations. The metrics are tested by simulations on a modified standard test system to demonstrate that they are suitable for use in maintainability assessment of power systems. They perform best, however, when evaluating the criticality of generators and power transmission lines within the context of maintenance campaign. The findings from this study underscore the potential for further enhancement of the described procedures. Priority must be given to formulating indices and accelerating their calculation.
References
E. Zio, G. Sansavini, “Vulnerability of smart grids with variable generation and consumption: A system of systems perspective,” IEEE Trans. Syst., Man, Cybern. A, Syst. Humans, vol. 43, no. 3, pp. 477–487, 2013. DOI: 10.1109/TSMCA.2012.2207106.
Y. Fang, G. Sansavini, E. Zio, “An optimization-based framework for the identification of vulnerabilities in electric power grids exposed to natural hazards,” Risk Anal., vol. 39, no. 9, pp. 1949–1969, 2019. DOI: 10.1111/risa.13287.
Yu. Ya. Chukreyev, M. Yu. Chukreyev, “Adequacy metrics for substantiating the components of the regulation-compliant capacity reserve in today's context of the UES of Russia development,” Izv. RAN. Energetika, no. 5, pp. 22–35, 2022. (In Russian)
G. A. Fedotova, “Methodology for comprehensive optimization of power supply reliability for consumers in power interconnections with weak ties,” Operativnoye Upravleniye v Elektroenergetike, Podgotovka Personala Podderzhaniye Ego Kvalifikatsii, no. 2, 2020. (In Russian)
P. Yu. Gubin, V. P. Oboskalov, “Application of the differential evolution method to maintenance scheduling of generation units,” Izv. RAN. Energetika, no. 2, pp. 50–64, 2021. (In Russian)
N. I. Voropai, G. A. Fedotova, “Planning maintenance of power generating equipment in market environment with regard for reliability,” Autom Remote Control, vol. 71, pp. 1442–1446, 2010. DOI: 10.1134/S0005117910070180.
V. G. Kitushin, E. V. Ivanova, “Reliability-centric planning of maintenance and replacement of power grid equipment,” Control Sciences, no. 5, pp. 46–51, 2011. (In Russian)
A. I. Reznitskii, B. M. Shtil'man, “Application of the 'PIONEER' method in automation of power equipment maintenance planning,” Automation and Remote Control, no. 11, pp. 147–153, 1983. (In Russian)
Yu. N. Rudenko, M. B. Chel'tsov, Reliability and redundancy in electric power systems. Research methods. Novosibirsk, USSR: Nauka, 1974. (In Russian)
G. A. Fedotova, N. I. Voropai, “Optimization of reliability of power supply to consumers,” Reliability: Theory and Applications, no. 2, pp. 126–139, 2007. (In Russian)
I. M. Sobol', “Sensitivity estimates for nonlinear mathematical models,” Mathematical Modeling and Computational Experiment, vol. 1, no. 4, pp. 407–414, 1993. (In Russian)
X. Liu, E. Ferrario, E. Zio, “Identifying resilient-important elements in interdependent critical infrastructures by sensitivity analysis,” Rel. Eng. & Syst. Safety, vol. 189, pp. 423–434, 2019. DOI: 10.1016/j.ress.2019.04.017.
J. F. Franco, L. F. Ochoa, R. Romero, “AC OPF for smart distribution networks: An efficient and robust quadratic approach,” IEEE Trans. Smart Grid, vol. 9, no. 5, pp. 4613–4623, 2018.
A. V. Pazderin, P. Yu. Bannykh, P. I. Bartolomei, A. E. Gavrilova, “Identification of maximum load operating conditions in a given controlled section by optimal power flow analysis,” Power Engineering: Research, Equipment, Technology, vol. 26, no. 12, pp. 49–57, 2024. (In Russian)
R. Billinton, W. Li, Reliability Assessment of electric power systems using Monte Carlo methods. New York, NY, USA: Springer, 1994.
S. Maher, M. Miltenberger, J. P. Pedroso, D. Rehfeldt, R. Schwarz, F. Serrano, “PySCIPOpt: Mathematical Programming in Python with the SCIP Optimization Suite,” in Int. Congress Math. Software, 2016, pp. 301–307.
T. Achterberg, T. Berthold, T. Koch, K. Wolter, “Constraint integer programming: A new approach to integrate CP and MIP,” in Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, 2008, pp. 6–20.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Energy Systems Research

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
