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Reliability Evaluation of Power Cables Considering the Restoration Characteristic
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).ORCID-id: 0000-0002-5863-0748
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).ORCID-id: 0000-0002-3495-2961
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).ORCID-id: 0000-0002-7796-5201
KTH Royal Institute of Technology, Stockholm, Sweden.ORCID-id: 0000-0002-3543-9326
Visa övriga samt affilieringar
2019 (Engelska)Ingår i: International Journal of Electrical Power & Energy Systems, ISSN 0142-0615, E-ISSN 1879-3517, Vol. 105, s. 622-631Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

In this paper Weibull parametric proportional hazard model (PHM) is used to estimate the failure rate of every individual cable based on its age and a set of explanatory factors. The required information for the proposed method is obtained by exploiting available historical cable inventory and failure data. This data-driven method does not require any additional measurements on the cables, and allows the cables to be ranked for maintenance prioritization and repair actions.

Furthermore, the results of reliability analysis of power cables are compared when the cables are considered as repairable or non-repairable components. The paper demonstrates that the methods which estimate the time-to-the-first failure (for non-repairable components) lead to incorrect conclusions about reliability of repairable power cables.

The proposed method is used to evaluate the failure rate of each individual Paper Insulated Lead Cover (PILC) underground cables in a distribution grid in the south of Sweden. © 2018 Elsevier Ltd

Ort, förlag, år, upplaga, sidor
London: Elsevier, 2019. Vol. 105, s. 622-631
Nyckelord [en]
Power cable, historical data, reliability, proportional hazard model, preventive maintenance.
Nationell ämneskategori
Elektroteknik och elektronik Annan elektroteknik och elektronik
Identifikatorer
URN: urn:nbn:se:hh:diva-35470DOI: 10.1016/j.ijepes.2018.08.047ISI: 000449447200055Scopus ID: 2-s2.0-85053080255OAI: oai:DiVA.org:hh-35470DiVA, id: diva2:1159949
Tillgänglig från: 2017-11-24 Skapad: 2017-11-24 Senast uppdaterad: 2019-03-19Bibliografiskt granskad
Ingår i avhandling
1. Data-Driven Methods for Reliability Evaluation of Power Cables in Smart Distribution Grids
Öppna denna publikation i ny flik eller fönster >>Data-Driven Methods for Reliability Evaluation of Power Cables in Smart Distribution Grids
2017 (Engelska)Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

This research aims to develop data-driven methods that automatically exploit historical data in smart distribution grids for reliability evaluation, i.e., analyzing frequency of failures, and modeling components’ lifetime. The results enable power distribution companies to change from reactive maintenance to predictive maintenance by deriving benefits from historical data. In particular, the data is exploited for two purposes: (a) failure pattern discovery, and (b) reliability evaluation of power cables. To analyze failure characteristics it is important to discover which failures share common features, e.g., if there are any types of failures that happen mostly in certain parts of the grid or at certain times. This analysis provides information about correlation between different features and identifying the most vulnerable components. In this case, we applied statistical analysis and association rules to discover failure patterns. Furthermore, we propose an easy-to-understand visualization of the correlations between different factors representing failures by using an approximated Bayesian network. We show that the Bayesian Network constructed based on the interesting rules of two items is a good approximation of the real dataset. The main focus of reliability evaluation is on failure rate estimation and reliability ranking. In case of power cables, the limited amount of recorded events makes it difficult to perform failure rate modeling, i.e., estimating the function that describes changes in the rate of failure depending on age. Therefore, we propose a method for interpreting the results of goodness-of-fit measures with confidence intervals, estimated using synthetic data. To perform reliability ranking of power cables, in addition to the age of cables, we consider other factors. Then, we use the Cox proportional hazard model (PHM) to assess the impact of the factors and calculate the failure rate of each individual cable. In reliability evaluation, it is important to consider the fact that power cables are repairable components. We show that the conclusions about different factors in PHM and cables ranking will be misleading if one considers the cables as non-repairable components. The developed methods of (a) are applied on data from Halmstad Energi och Miljö (HEM Nät), Öresundskraft, Göteborg Energy, and Växjö Energy, four different distribution system operators in Sweden. The developed methods of (b) are applied on data from HEM Nät.

Ort, förlag, år, upplaga, sidor
Halmstad: Halmstad University Press, 2017. s. 70
Serie
Halmstad University Dissertations ; 34
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
urn:nbn:se:hh:diva-35147 (URN)978-91-87045-70-7 (ISBN)978-91-87045-71-4 (ISBN)
Presentation
2017-09-29, Halda, Visionen/house J, Halmstad University, Kristian IV:s väg 3, Halmstad, 10:00 (Engelska)
Opponent
Handledare
Forskningsfinansiär
KK-stiftelsen
Anmärkning

Funding: Knowledge Foundation & HEM Nät

Tillgänglig från: 2017-11-24 Skapad: 2017-10-04 Senast uppdaterad: 2018-01-13Bibliografiskt granskad
2. Data analytics for weak spot detection in power distribution grids
Öppna denna publikation i ny flik eller fönster >>Data analytics for weak spot detection in power distribution grids
2019 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

This research aims to develop data-driven methods that extract information from the available data in distribution grids for detecting weak spots, including the components with degraded reliability and areas with power quality problems. The results enable power distribution companies to change from reactive maintenance to predictive maintenance by deriving benefits from available data. In particular, the data is exploited for three purposes: (a) failure pattern discovery, (b) reliability evaluation of power cables, and (c) analyzing and modeling propagation of power quality disturbances (PQDs) in low-voltage grids.

To analyze failure characteristics it is important to discover which failures share common features, e.g., if there are any types of failures that happen mostly in certain parts of the grid or at certain times. This analysis provides information about correlation between different features and identifying the most vulnerable components. In this case, we applied statistical analysis and association rules to discover failure patterns. Furthermore, we propose a visualization of the correlations between different factors representing failures by using an approximated Bayesian network. We show that the Bayesian Network constructed based on the interesting rules of two items is a good approximation of the real dataset.

The main focus of reliability evaluation is on failure rate estimation and reliability ranking. In case of power cables, the limited amount of recorded events makes it difficult to perform failure rate modeling. Therefore, we propose a method for interpreting the results of goodness-of-fit measures with confidence intervals, estimated using synthetic data.

To perform reliability ranking of power cables, in addition to the age of cables, we consider other factors. Then, we use the proportional hazard model (PHM) to assess the impact of the factors and calculate the failure rate of each individual cable. In reliability evaluation, it is important to consider the fact that power cables are repairable components. We discuss that the conclusions about different factors in PHM and cables ranking will be misleading if one considers the cables as non-repairable components.

In low-voltage distribution grids, analyzing PQDs is important as we are moving towards smart grids with the next generation of producers and consumers. Installing Power Quality and Monitoring Systems (PQMS) at all the nodes in the network, for monitoring the impacts of the new consumer/producer, is prohibitively expensive. Instead, we demonstrate that power companies can utilize the available smart meters, which are widely deployed in the low-voltage grids, for monitoring power quality events and identifying areas with power quality problems. In particular, several models for propagation of PQDs, within neighbor customers in different levels of the grid topology, are investigated. The results show that meters data can be used to detect and describe propagation in low-voltage grids.

The developed methods of (a) failure pattern discovery are applied on data from Halmstad Energi och Miljö (HEM Nät), Öresundskraft, Göteborg Energy, and Växjö Energy, four different distribution system operators in Sweden. The developed methods of (b) reliability evaluation of power cables and (c) analyzing and modeling propagation of PQDs are applied on data from HEM Nät.

Ort, förlag, år, upplaga, sidor
Halmstad: Halmstad University Press, 2019. s. 117
Nationell ämneskategori
Annan elektroteknik och elektronik
Identifikatorer
urn:nbn:se:hh:diva-39067 (URN)978-91-88749-18-5 (ISBN)978-91-88749-19-2 (ISBN)
Disputation
2019-04-24, Haldasalen, Kristian IV:s väg 3, Halmstad, 13:00 (Engelska)
Opponent
Handledare
Tillgänglig från: 2019-03-19 Skapad: 2019-03-18 Senast uppdaterad: 2019-04-03Bibliografiskt granskad

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Mashad Nemati, HassanPinheiro Sant'Anna, AnitaNowaczyk, SławomirJürgensen, Jan HenningHilber, Patrik
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