Algorithm for Automatic Calculation of SAIDI and SAIFI Reliability Indices Based on Metering System Data

A 10–35 kV power distribution grid is considered, in which an automated information and measuring electricity metering system operates. It is assumed that the metering system head unit (instrument) contains data on the electrical network feeder’s and on the number of consumers (subscribers) connected to all of its outgoing lines. The head unit communicates with the feeder’s outgoing line meters that record the date, time, and duration of sustained (more than five-minute) interruptions of power supply to consumers. The appropriate meters transmit, on a monthly basis, data on power supply interruptions in the outgoing lines to the head unit, where the power distribution grid’s SAIDI and SAIFI reliability indices are calculated according to the developed algorithm. These reliability indices are automatically calculated according to the method outlined in IEEE Standard 1366™-2012, intended for use in modern information and measurement electricity metering systems. Computational experiments have confirmed the accuracy of calculating the SAIDI and SAIFI indices using the developed algorithm and calculation software. The study results are beneficial for both existing metering systems and those under development with SAIDI and SAIFI reliability indices monitoring functions. Such calculations can be used to determine and maintain the required level of power supply reliability of the power distribution grid consumers.

Authors

Publication Details

Journal
Elektrichestvo
Published
2024-09-16
DOI
https://doi.org/10.24160/0013-5380-2024-9-60-69
Primary Topic
Evaluation Methods in Various Fields
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Algorithm for Automatic Calculation of SAIDI and SAIFI Reliability Indices Based on Metering System Data

М. И. Данилов, И. Г. Романенко, Nelli Kononova, Tatiana Morozova et al.
Elektrichestvo
Evaluation Methods in Various Fields
article

Algorithm for Automatic Calculation of SAIDI and SAIFI Reliability Indices Based on Metering System Data

М. И. Данилов, И. Г. Романенко, Nelli Kononova, Tatiana Morozova, M. Demin
article en

Abstract

A 10–35 kV power distribution grid is considered, in which an automated information and measuring electricity metering system operates. It is assumed that the metering system head unit (instrument) contains data on the electrical network feeder’s and on the number of consumers (subscribers) connected to all of its outgoing lines. The head unit communicates with the feeder’s outgoing line meters that record the date, time, and duration of sustained (more than five-minute) interruptions of power supply to consumers. The appropriate meters transmit, on a monthly basis, data on power supply interruptions in the outgoing lines to the head unit, where the power distribution grid’s SAIDI and SAIFI reliability indices are calculated according to the developed algorithm. These reliability indices are automatically calculated according to the method outlined in IEEE Standard 1366™-2012, intended for use in modern information and measurement electricity metering systems. Computational experiments have confirmed the accuracy of calculating the SAIDI and SAIFI indices using the developed algorithm and calculation software. The study results are beneficial for both existing metering systems and those under development with SAIDI and SAIFI reliability indices monitoring functions. Such calculations can be used to determine and maintain the required level of power supply reliability of the power distribution grid consumers.

Elektrichestvo(9)
Openalex Percentile: Top 95%
Evaluation Methods in Various Fields
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.