Estimation of Confidence Intervals for Power Distribution Reliability Indices (SAIFI and SAIDI)
DOI:
https://doi.org/10.25729/esr.2026.01.0013Keywords:
Distribution system reliability, reliability indices, SAIDI, SAIFI, confidence interval estimation, stochastic modeling, power outage analysisAbstract
Power distribution reliability indices, system average interruption duration index (SAIDI) and system average interruption frequency index (SAIFI), depend on the number of service interruptions per year, the number of customers affected by each interruption, and power supply restoration time. All three factors are stochastic and can vary widely even when the network structure and the technical condition of the electrical equipment remain unchanged. This leads to random year-to-year fluctuations in SAIDI and SAIFI values. Determining the range of these stochastic variations is essential for comparing the indices and assessing their compliance with regulatory standards. Currently, formal methodologies for estimating confidence intervals for reliability indices remain underdeveloped both in Russia and internationally. This paper proposes an algorithm for calculating confidence intervals for SAIDI and SAIFI based on daily segmentation and numerical simulation. The proposed algorithm is validated using a case study of distribution systems in Moscow and the Moscow region.
References
D. B. Gvozdev, D. M. Gabdushev, R. Yu. Goenko, D. I. Klimkina, D. A. Buyankov, A. S. Vanin, “Analysis of domestic and international experience in standardization of distribution network reliability,” Electric power. Transmission and Distribution, no. 5(80), pp. 26–32, 2023. (In Russian)
R. Brown, Electric Power Distribution Reliability. Boca Raton, FL, USA: Taylor & Francis Group, 2009.
Order of the Ministry of Energy of the Russian Federation (2016, Nov. 29), No. 1256, On approval of methodological guidelines for calculating the level of reliability and quality of supplied goods and provided services for the organization managing the Unified National (All-Russian) Electric Grid and territorial grid companies (with amendments and additions). Moscow, Russia, 2016. (In Russian)
Order of the Ministry of Energy of the Russian Federation (2017, Oct. 18), No. 976, On approval of baseline reliability indicators, permissible deviation coefficients of actual reliability indicators from planned ones, and maximum dynamics of improvement for planned reliability indicators for groups of territorial grid companies with comparable economic and technical characteristics or operating conditions, using the analog comparison method. Moscow, Russia, 2017. (In Russian)
D. B. Gvozdev, A. A. Korolev, S. V. Shpilevoy, V. N. Tulsky, A. S. Vanin, D. M. Gabdushev, “Assessment of the permissible reliability level of electrical networks under current operating conditions,” Electric power. Transmission and Distribution, no. 3(84), pp. 46–55, 2024. (In Russian)
Annual Report of PJSC Rosseti Moscow Region for 2020. Moscow, Russia, 2021. (In Russian)
Annual Report of PJSC Rosseti Moscow Region for 2021. Moscow, Russia, 2022. (In Russian)
Annual Report of PJSC Rosseti Moscow Region for 2022. Moscow, Russia, 2023. (In Russian)
Annual Report of PJSC Rosseti Moscow Region for 2023. Moscow, Russia, 2024. (In Russian)
IEEE Guide for Electric Power Distribution Reliability Indices, IEEE Std 1366-2022, Nov. 22, 2022.
B. Efron, R. Tibshirani, An introduction to the bootstrap. New York, NY, USA: Chapman & Hall, 1993.
G. Box, G. Jenkins. Time Series Analysis: Forecasting and Control. Hoboken, NJ, USA: Wiley, 2015.
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