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Duvnjak Zarkovic, S., Weiss, X. & Hilber, P. (2024). Addressing Data Deficiencies in Outage Reports: A Qualitative and Machine Learning Approach. In: : . Paper presented at 2024 Power Systems Computation Conference (PSCC), Paris, France. Paris
Open this publication in new window or tab >>Addressing Data Deficiencies in Outage Reports: A Qualitative and Machine Learning Approach
2024 (English)Conference paper (Other academic)
Abstract [en]

This study investigates outage statistics in the Swedish power system. More specifically, this paper delves into the critical analysis and enhancement of data quality, focusing on inconsistencies and missing values, i.e. unknown outage causes and unidentified faulty equipment. By carefully examining the data, noticeable gaps and deficiencies are revealed. Thus, a format for improving outage reporting using a database with 3 relations (outage summary, outage breakdown and customer breakdown) is proposed. In addition to a qualitative analysis of the data, various machine learning algorithms are explored and tested for their capability to predict the unknown values within the dataset, thereby offering a twofold solution: enhancing the accuracy of outage data and facilitating deeper, more accurate analytical capabilities. The findings and proposals within this work not only illuminate the current challenges within outage data management but also pave the way for more robust, data-driven decision-making in outage management and policy formation. 

Place, publisher, year, edition, pages
Paris: , 2024
Keywords
Data analysis, Power outages, Machine learning, Decision-making, Data processing, Technical reports
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-342705 (URN)
Conference
2024 Power Systems Computation Conference (PSCC), Paris, France
Funder
SweGRIDS - Swedish Centre for Smart Grids and Energy Storage, CP26Swedish Energy Agency
Note

QC 20240130

Available from: 2024-01-26 Created: 2024-01-26 Last updated: 2024-01-30Bibliographically approved
Li, Z., Hilber, P., Laneryd, T., Diaz, G. P. & Ivanell, S. (2024). Impact of turbine availability and wake effect on the application of dynamic thermal rating of wind farm export transformers. Energy Reports, 11, 1399-1411
Open this publication in new window or tab >>Impact of turbine availability and wake effect on the application of dynamic thermal rating of wind farm export transformers
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2024 (English)In: Energy Reports, E-ISSN 2352-4847, Vol. 11, p. 1399-1411Article in journal (Refereed) Published
Abstract [en]

Dynamic thermal rating allows transformers to operate beyond the nameplate rating according to the actual weather and loading conditions. This paper proposes a methodology to improve the application of this technology in the design of new transformers or in the operation of existing transformers connected to wind farms by accurately predicting their load profiles, accounting for the influence of wake effect and turbine availability. Specifically, the variation of turbine availability due to the intermittent wind is considered in the load profile estimation. Additionally, a correction method, which can be incorporated into any wake model, is proposed to improve the accuracy of wake loss computation. A case study shows that the wake effect and the changing turbine availability shorten the time that the transformers maintain at full load, thereby reducing the aging rate of the wind farm export transformers. The findings suggest that considering these two factors in the DTR application can benefit the longevity and efficiency of wind farm exported transformers.

Place, publisher, year, edition, pages
Elsevier BV, 2024
Keywords
Transformer aging, Transformer loading, Turbine availability, Wake effect, Wind farm reliability
National Category
Energy Engineering Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-342617 (URN)10.1016/j.egyr.2023.12.042 (DOI)2-s2.0-85182519809 (Scopus ID)
Note

QC 20240201

Available from: 2024-01-25 Created: 2024-01-25 Last updated: 2024-02-01Bibliographically approved
Koziel, S. E. & Hilber, P. (2024). Profitable sensor network design in the distribution grid - updated.
Open this publication in new window or tab >>Profitable sensor network design in the distribution grid - updated
2024 (English)Other (Other academic)
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-344437 (URN)
Available from: 2024-03-17 Created: 2024-03-17 Last updated: 2024-03-22Bibliographically approved
Naim, W., Hilber, P. & Shayesteh, E. (2023). Data Challenges in Asset Management of Power Distribution Systems: Review and Observations. In: 2023 IEEE Belgrade PowerTech, PowerTech 2023: . Paper presented at 2023 IEEE Belgrade PowerTech, PowerTech 2023, Belgrade, Serbia, Jun 25 2023 - Jun 29 2023. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Data Challenges in Asset Management of Power Distribution Systems: Review and Observations
2023 (English)In: 2023 IEEE Belgrade PowerTech, PowerTech 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023Conference paper, Published paper (Refereed)
Abstract [en]

Power system asset management involves several multidisciplinary activities to ensure the reliable, efficient, and safe operation of power equipment. One aspect of effective asset management is that planning and decision making have to be data driven. However, the use of data comes with a set of challenges. In this paper, we review the state-of-the-art of asset management, data management, and their links to power systems in particular. Previous literature is reviewed methodically based on keyword search and setting scores for different parameters of interest. Asset management strategies and activities are reviewed along with trends in data management. The review concludes with an observation that data quality and data availability are the most pressing current challenges in power system asset management.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Keywords
asset management, data availability, data quality, power distribution
National Category
Reliability and Maintenance
Identifiers
urn:nbn:se:kth:diva-336731 (URN)10.1109/PowerTech55446.2023.10202707 (DOI)001055072600043 ()2-s2.0-85169458415 (Scopus ID)
Conference
2023 IEEE Belgrade PowerTech, PowerTech 2023, Belgrade, Serbia, Jun 25 2023 - Jun 29 2023
Note

Part of ISBN 9781665487788

QC 20230919

Available from: 2023-09-19 Created: 2023-09-19 Last updated: 2024-01-05Bibliographically approved
Habib, M. Z., Duvnjak Zarkovic, S., Taylor, N., Hilber, P. & Shayesteh, E. (2023). Distributed fault-passage indicators versus central fault location: Comparison for reliability centred planning of resonant-earthed distribution systems. Energy Reports, 9, 1731-1742
Open this publication in new window or tab >>Distributed fault-passage indicators versus central fault location: Comparison for reliability centred planning of resonant-earthed distribution systems
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2023 (English)In: Energy Reports, E-ISSN 2352-4847, Vol. 9, p. 1731-1742Article in journal (Refereed) Published
Abstract [en]

Fault location methods are crucial for reducing fault restoration time, and thus improving a network's system average interruption duration index (SAIDI) and customer outage cost. Resonant-earthed systems pose problems for traditional fault location methods, leading to poor accuracy and a need for additional complexity. In this context, methods that detect fault direction (fault-passage indicators, FPI) at multiple points in the network may show advantages over a central distance-estimation method using fault locators (FL) of poor accuracy. This paper includes a comparative study of these two major fault location methods, comparing the reliability benefit from a varied number of FPIs or a central method. The optimal placement of the fault locating devices is found by formulating a mixed-integer linear programming (MILP) optimization approach that minimizes both outage and investment costs and assesses SAIDI. This approach has been tested on an example distribution system. However, to justify the universality of the algorithm, the RBTS reliability test system has also been analysed. The comparison of location methods and placement method of FPIs are useful for reliability centred planning of resonant-earthed distribution systems where fault location is to be used. Results show that a small number of FPIs that give accurate identification of direction may give more cost effective increase in reliability than a distance estimate by FL with typical levels of inaccuracy.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Fault location methods, Distribution system planning, Resonant-earthed system, SAIDI, Mixed-integer programming
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-324053 (URN)10.1016/j.egyr.2022.12.077 (DOI)000919166400001 ()2-s2.0-85145980006 (Scopus ID)
Note

QC 20230222

Available from: 2023-02-22 Created: 2023-02-22 Last updated: 2023-02-22Bibliographically approved
Li, Z., Hilber, P., Ivanell, S. & Laneryd, T. (2023). Maximizing Power Dispatch of Wind-Storage System with Dynamic Thermal Rating Considering Battery Degradation Costs. In: Proceedings of 2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023: . Paper presented at 2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023, Grenoble, France, Oct 23 2023 - Oct 26 2023. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Maximizing Power Dispatch of Wind-Storage System with Dynamic Thermal Rating Considering Battery Degradation Costs
2023 (English)In: Proceedings of 2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023Conference paper, Published paper (Refereed)
Abstract [en]

In the wind farm expansion stage, installing battery energy storage systems (BESSs) assists in mitigating the time of overloading the connected transmission systems by peak shaving. Applying dynamic thermal rating (DTR) improves the utilization of the transmission systems based on monitoring real-time environmental conditions. DTR and BESS are combined in this paper to maximize power dispatch of an expanded wind farm without expanding the transmission system. The novelty of this paper lies in considering DTR of transformer and degradation cost of the batteries in the proposed optimization framework. Results show that the utilization of DTR and BESS mitigates wind power curtailment and applying DTR reduces degradation costs of the batteries. The findings also indicate the importance of carefully planning the size and control strategy of BESSs in order to minimize operational costs, especially for expanded wind farms and the connected transmission systems applying DTR.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Keywords
battery degradation, battery storage, dynamic thermal rating, transformer, wind farm expansion
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-344030 (URN)10.1109/ISGTEUROPE56780.2023.10407543 (DOI)2-s2.0-85185228534 (Scopus ID)
Conference
2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023, Grenoble, France, Oct 23 2023 - Oct 26 2023
Note

QC 20240229

Part of ISBN 979-8-3503-9678-2

Available from: 2024-02-28 Created: 2024-02-28 Last updated: 2024-02-29Bibliographically approved
Duvnjak Zarkovic, S., Hilber, P. & Shayesteh, E. (2023). Outage Statistics and Trends in Sweden – What does data tell us?. In: Prof. Jinyue Yan (Ed.), Energy Proceedings: . Paper presented at 15th International Conference on Applied Energy - ICAE2023, Dec. 3-7, 2023, Doha, Qatar Energy Proceedings.
Open this publication in new window or tab >>Outage Statistics and Trends in Sweden – What does data tell us?
2023 (English)In: Energy Proceedings / [ed] Prof. Jinyue Yan, 2023Conference paper, Published paper (Refereed)
Abstract [en]

Data analysis plays a pivotal role in identifying patterns and relationships within data sets. By examining historical outage statistics in power systems, trends in system performance can be revealed, contributing to a better understanding of its behavior. Furthermore, by understanding the past performance of the power system, utility companies can make better decisions to enhance system reliability and resilience. This study investigates outage statistics in the Swedish power system from 2009 to 2019 and examines in depth the reporting mechanism. The data is clustered and analyzed according to three different criteria: voltage level of the breaking device, cause of the failure, and faulty equipment. Although the presented overview highlights key trends in system performance, the analysis has uncovered issues related to data quality and availability, such as missing values and inconsistencies that require further attention.

Keywords
data analysis, outage statistics, power system, decision-making, reporting system
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-342703 (URN)
Conference
15th International Conference on Applied Energy - ICAE2023, Dec. 3-7, 2023, Doha, Qatar Energy Proceedings
Funder
SweGRIDS - Swedish Centre for Smart Grids and Energy Storage, CP26
Note

QC 20240130

Available from: 2024-01-26 Created: 2024-01-26 Last updated: 2024-01-30Bibliographically approved
Vincenti, H., Koziel, S. E. & Hilber, P. (2023). Profitability of Condition Monitoring in the Electric Distribution Grid. In: IET Conference Proceedings: . Paper presented at 27th International Conference on Electricity Distribution, CIRED 2023, Rome, Italy, Jun 12 2023 - Jun 15 2023 (pp. 362-366). Institution of Engineering and Technology
Open this publication in new window or tab >>Profitability of Condition Monitoring in the Electric Distribution Grid
2023 (English)In: IET Conference Proceedings, Institution of Engineering and Technology , 2023, p. 362-366Conference paper, Published paper (Other academic)
Abstract [en]

The deployment of sensors enables the development of condition-based maintenance, as opposed to the traditional time-based and corrective maintenance. This work explores the conditions under which the use of sensors to improve maintenance scheduling on overhead lines is economically profitable. We propose a novel methodology that converts sensor measurements into an asset condition assessment, and then into a maintenance decision. The cost of predictive maintenance is then compared to the cost of corrective maintenance over several decades, ultimately allowing to evaluate the profitability of investing into sensors. This work enables to identify the parameter values that result in profitable investments in sensors. The results show that the use of sensors is particularly justified for short-lived assets, supplying many clients.

Place, publisher, year, edition, pages
Institution of Engineering and Technology, 2023
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-342405 (URN)10.1049/icp.2023.0309 (DOI)2-s2.0-85181536809 (Scopus ID)
Conference
27th International Conference on Electricity Distribution, CIRED 2023, Rome, Italy, Jun 12 2023 - Jun 15 2023
Note

QC 20240118

Available from: 2024-01-17 Created: 2024-01-17 Last updated: 2024-03-17Bibliographically approved
Koziel, S. E. & Hilber, P. (2023). Profitable sensor network design in the distribution grid. In: 2023 IEEE Belgrade PowerTech, PowerTech 2023: . Paper presented at 2023 IEEE Belgrade PowerTech, PowerTech 2023, Belgrade, Serbia, Jun 25 2023 - Jun 29 2023. Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Profitable sensor network design in the distribution grid
2023 (English)In: 2023 IEEE Belgrade PowerTech, PowerTech 2023, Institute of Electrical and Electronics Engineers Inc. , 2023Conference paper, Published paper (Refereed)
Abstract [en]

With an aging infrastructure and complexifying grid, sensors become essential to monitor the state of power system components. They are part of the evolution of power grids into smarter grids, as well as of the development of digital twins. Currently, sensors are largely absent from distribution grids. While much research literature exists in optimal sensor placement with cost minimization under performance constraints, few publications quantify the profitability of such sensors for distribution grid operators (DSOs). This work aims to bridge this gap and to offer a novel methodology that enables DSOs to assess if and where sensors would be profitable in the context of asset management. The methodology is based on modeling the effects of sensors on maintenance activities and then on grid reliability. We formulate a binary non linear optimization problem, and apply it to study the case of sensors that monitor the condition of power lines. Results show that sensor profitability depends on several factors including i) the component age, ii) the current replacement practice, and iii) the component importance. Thus, this work gives a tool for DSOs to decide whether and where to invest into sensors.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2023
Keywords
optimization, reliability, replacement scheduling, sensors, smart grids
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Computer Sciences
Identifiers
urn:nbn:se:kth:diva-336733 (URN)10.1109/PowerTech55446.2023.10202877 (DOI)001055072600203 ()2-s2.0-85169475467 (Scopus ID)
Conference
2023 IEEE Belgrade PowerTech, PowerTech 2023, Belgrade, Serbia, Jun 25 2023 - Jun 29 2023
Note

Part of ISBN 9781665487788

QC 20230919

Available from: 2023-09-19 Created: 2023-09-19 Last updated: 2023-10-16Bibliographically approved
Weiss, X., Nordström, L., Hilber, P. & Rolander, A. (2023). Weather Event Preparedness Modelling for Distribution Systems. In: Proceedings of 2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023: . Paper presented at 2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023, Grenoble, France, Oct 23 2023 - Oct 26 2023. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Weather Event Preparedness Modelling for Distribution Systems
2023 (English)In: Proceedings of 2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023Conference paper, Published paper (Refereed)
Abstract [en]

Distribution level outages generally affect fewer customers than regional or transmission level outages. However, as global temperatures continue to rise, the radial topology and overhead lines typical at this level make it particularly vulnerable to High Impact Low Probability weather events. A Machine Learning model is therefore proposed that uses Multinomial Logistic Regression (MLR) to predict the likelihood of an outage given the weather conditions and the composition of the Distribution System Operator (DSO). The model is tuned by using a traditional binary classification problem as ground truth, but is evaluated based on its probability distributions near outage events. Results show a greater classification confidence for true outages than false outages as well as a probability distribution that is skewed towards actual outage events.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Keywords
Forecasting, Power outages, Regression analysis, Resilience, Resilient systems, Risk analysis, Weather
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:kth:diva-344563 (URN)10.1109/ISGTEUROPE56780.2023.10407604 (DOI)2-s2.0-85187311764 (Scopus ID)
Conference
2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023, Grenoble, France, Oct 23 2023 - Oct 26 2023
Note

Part of ISBN 9798350396782

QC 20240321

Available from: 2024-03-20 Created: 2024-03-20 Last updated: 2024-03-21Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2964-7233

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