Predicting Reliability of Electric Power Distribution Grid Using Historical Outage Data

Erwin Normanyo; Godwin Diamenu

doi:doi:10.11648/j.epes.20221104.11

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Predicting Reliability of Electric Power Distribution Grid Using Historical Outage Data

Erwin Normanyo, Godwin Diamenu

Published in American Journal of Electrical Power and Energy Systems (Volume 11, Issue 4)

Received: 22 October 2021 Accepted: 25 January 2022 Published: 29 July 2022

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Abstract

Demand for energy is on the increase posing serious complexity issues to power systems in general impacting reliability negatively. The electric power distribution grid is one of the most important entities in a power system contributing up to 90% of reliability problems. Reliability of the electric service provided to end users or load points can be altered by the faults originated either inside or outside of the functional zones of an electric power distribution grid. Reliability analyses of electric power systems in general is based on historical analysis approach where the historical outage data is used to assess the reliability performance of the generation, transmission or the distribution component of the power system. This approach even though gives the appropriate reliability indices indicating the performance of the electric power system component under consideration; however, the computed reliability indices are usually historic making any improvement decision(s) taken to be reactive. In this research article, the historical outage data is rather used to predict the performance of the electric power distribution grid into its future operations and maintenance activities. Analysis of predictive reliability (PR) normally helps in determining the performance state that the design, planning, and operation of the grid will attain when certain reliability objectives and associated performance outcomes are met. The PR is conducted by computing reliability indices using present fault rates, outage durations and number of affected customers. The predicted SAIFI, SAIDI, CAIDI, CAIFI and ASAI values of the years 2020, 2025, and 2030 gave an indication that the reliability of the electric power distribution grid within the metropolis would see varying monthly but improved yearly performances. Better performances regarding these indices are envisaged as the years advance towards the year 2030.

Published in	American Journal of Electrical Power and Energy Systems (Volume 11, Issue 4)
DOI	10.11648/j.epes.20221104.11
Page(s)	66-78
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Distribution Grid, Predictive, Outage Data, Reliability Indices, Reliability Analysis

References

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Erwin Normanyo, Godwin Diamenu. (2022). Predicting Reliability of Electric Power Distribution Grid Using Historical Outage Data. American Journal of Electrical Power and Energy Systems, 11(4), 66-78. https://doi.org/10.11648/j.epes.20221104.11

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Erwin Normanyo; Godwin Diamenu. Predicting Reliability of Electric Power Distribution Grid Using Historical Outage Data. Am. J. Electr. Power Energy Syst. 2022, 11(4), 66-78. doi: 10.11648/j.epes.20221104.11

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AMA Style

Erwin Normanyo, Godwin Diamenu. Predicting Reliability of Electric Power Distribution Grid Using Historical Outage Data. Am J Electr Power Energy Syst. 2022;11(4):66-78. doi: 10.11648/j.epes.20221104.11

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@article{10.11648/j.epes.20221104.11,
  author = {Erwin Normanyo and Godwin Diamenu},
  title = {Predicting Reliability of Electric Power Distribution Grid Using Historical Outage Data},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {11},
  number = {4},
  pages = {66-78},
  doi = {10.11648/j.epes.20221104.11},
  url = {https://doi.org/10.11648/j.epes.20221104.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20221104.11},
  abstract = {Demand for energy is on the increase posing serious complexity issues to power systems in general impacting reliability negatively. The electric power distribution grid is one of the most important entities in a power system contributing up to 90% of reliability problems. Reliability of the electric service provided to end users or load points can be altered by the faults originated either inside or outside of the functional zones of an electric power distribution grid. Reliability analyses of electric power systems in general is based on historical analysis approach where the historical outage data is used to assess the reliability performance of the generation, transmission or the distribution component of the power system. This approach even though gives the appropriate reliability indices indicating the performance of the electric power system component under consideration; however, the computed reliability indices are usually historic making any improvement decision(s) taken to be reactive. In this research article, the historical outage data is rather used to predict the performance of the electric power distribution grid into its future operations and maintenance activities. Analysis of predictive reliability (PR) normally helps in determining the performance state that the design, planning, and operation of the grid will attain when certain reliability objectives and associated performance outcomes are met. The PR is conducted by computing reliability indices using present fault rates, outage durations and number of affected customers. The predicted SAIFI, SAIDI, CAIDI, CAIFI and ASAI values of the years 2020, 2025, and 2030 gave an indication that the reliability of the electric power distribution grid within the metropolis would see varying monthly but improved yearly performances. Better performances regarding these indices are envisaged as the years advance towards the year 2030.},
 year = {2022}
}

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TY  - JOUR
T1  - Predicting Reliability of Electric Power Distribution Grid Using Historical Outage Data
AU  - Erwin Normanyo
AU  - Godwin Diamenu
Y1  - 2022/07/29
PY  - 2022
N1  - https://doi.org/10.11648/j.epes.20221104.11
DO  - 10.11648/j.epes.20221104.11
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 66
EP  - 78
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20221104.11
AB  - Demand for energy is on the increase posing serious complexity issues to power systems in general impacting reliability negatively. The electric power distribution grid is one of the most important entities in a power system contributing up to 90% of reliability problems. Reliability of the electric service provided to end users or load points can be altered by the faults originated either inside or outside of the functional zones of an electric power distribution grid. Reliability analyses of electric power systems in general is based on historical analysis approach where the historical outage data is used to assess the reliability performance of the generation, transmission or the distribution component of the power system. This approach even though gives the appropriate reliability indices indicating the performance of the electric power system component under consideration; however, the computed reliability indices are usually historic making any improvement decision(s) taken to be reactive. In this research article, the historical outage data is rather used to predict the performance of the electric power distribution grid into its future operations and maintenance activities. Analysis of predictive reliability (PR) normally helps in determining the performance state that the design, planning, and operation of the grid will attain when certain reliability objectives and associated performance outcomes are met. The PR is conducted by computing reliability indices using present fault rates, outage durations and number of affected customers. The predicted SAIFI, SAIDI, CAIDI, CAIFI and ASAI values of the years 2020, 2025, and 2030 gave an indication that the reliability of the electric power distribution grid within the metropolis would see varying monthly but improved yearly performances. Better performances regarding these indices are envisaged as the years advance towards the year 2030.
VL  - 11
IS  - 4
ER  -

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Author Information

Erwin Normanyo

Department of Electrical and Electronic Engineering, Faculty of Engineering, University of Mines and Technology (UMaT), Tarkwa, Ghana
Godwin Diamenu

Department of Electrical and Electronic Engineering, Faculty of Engineering, University of Mines and Technology (UMaT), Tarkwa, Ghana

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APA Style

Erwin Normanyo, Godwin Diamenu. (2022). Predicting Reliability of Electric Power Distribution Grid Using Historical Outage Data. American Journal of Electrical Power and Energy Systems, 11(4), 66-78. https://doi.org/10.11648/j.epes.20221104.11

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ACS Style

Erwin Normanyo; Godwin Diamenu. Predicting Reliability of Electric Power Distribution Grid Using Historical Outage Data. Am. J. Electr. Power Energy Syst. 2022, 11(4), 66-78. doi: 10.11648/j.epes.20221104.11

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AMA Style

Erwin Normanyo, Godwin Diamenu. Predicting Reliability of Electric Power Distribution Grid Using Historical Outage Data. Am J Electr Power Energy Syst. 2022;11(4):66-78. doi: 10.11648/j.epes.20221104.11

Copy | Download

@article{10.11648/j.epes.20221104.11,
  author = {Erwin Normanyo and Godwin Diamenu},
  title = {Predicting Reliability of Electric Power Distribution Grid Using Historical Outage Data},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {11},
  number = {4},
  pages = {66-78},
  doi = {10.11648/j.epes.20221104.11},
  url = {https://doi.org/10.11648/j.epes.20221104.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20221104.11},
  abstract = {Demand for energy is on the increase posing serious complexity issues to power systems in general impacting reliability negatively. The electric power distribution grid is one of the most important entities in a power system contributing up to 90% of reliability problems. Reliability of the electric service provided to end users or load points can be altered by the faults originated either inside or outside of the functional zones of an electric power distribution grid. Reliability analyses of electric power systems in general is based on historical analysis approach where the historical outage data is used to assess the reliability performance of the generation, transmission or the distribution component of the power system. This approach even though gives the appropriate reliability indices indicating the performance of the electric power system component under consideration; however, the computed reliability indices are usually historic making any improvement decision(s) taken to be reactive. In this research article, the historical outage data is rather used to predict the performance of the electric power distribution grid into its future operations and maintenance activities. Analysis of predictive reliability (PR) normally helps in determining the performance state that the design, planning, and operation of the grid will attain when certain reliability objectives and associated performance outcomes are met. The PR is conducted by computing reliability indices using present fault rates, outage durations and number of affected customers. The predicted SAIFI, SAIDI, CAIDI, CAIFI and ASAI values of the years 2020, 2025, and 2030 gave an indication that the reliability of the electric power distribution grid within the metropolis would see varying monthly but improved yearly performances. Better performances regarding these indices are envisaged as the years advance towards the year 2030.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Predicting Reliability of Electric Power Distribution Grid Using Historical Outage Data
AU  - Erwin Normanyo
AU  - Godwin Diamenu
Y1  - 2022/07/29
PY  - 2022
N1  - https://doi.org/10.11648/j.epes.20221104.11
DO  - 10.11648/j.epes.20221104.11
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 66
EP  - 78
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20221104.11
AB  - Demand for energy is on the increase posing serious complexity issues to power systems in general impacting reliability negatively. The electric power distribution grid is one of the most important entities in a power system contributing up to 90% of reliability problems. Reliability of the electric service provided to end users or load points can be altered by the faults originated either inside or outside of the functional zones of an electric power distribution grid. Reliability analyses of electric power systems in general is based on historical analysis approach where the historical outage data is used to assess the reliability performance of the generation, transmission or the distribution component of the power system. This approach even though gives the appropriate reliability indices indicating the performance of the electric power system component under consideration; however, the computed reliability indices are usually historic making any improvement decision(s) taken to be reactive. In this research article, the historical outage data is rather used to predict the performance of the electric power distribution grid into its future operations and maintenance activities. Analysis of predictive reliability (PR) normally helps in determining the performance state that the design, planning, and operation of the grid will attain when certain reliability objectives and associated performance outcomes are met. The PR is conducted by computing reliability indices using present fault rates, outage durations and number of affected customers. The predicted SAIFI, SAIDI, CAIDI, CAIFI and ASAI values of the years 2020, 2025, and 2030 gave an indication that the reliability of the electric power distribution grid within the metropolis would see varying monthly but improved yearly performances. Better performances regarding these indices are envisaged as the years advance towards the year 2030.
VL  - 11
IS  - 4
ER  -

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