This is the published version of a paper published in Electric power systems research. Citation for the original published paper (version of record):Jürgensen, J H., Nordström, L., Hilber, P. (2016) Individual failure rates for transformers within a population based on diagnostic measures. The high monetary value of a transformer has placed the transformer life-time optimization into the focus of asset management. The average failure rate has created reasonable results within reliability modeling, however, it cannot reflect the probability of failure for an individual transformer. In this paper, a method is introduced to calculate individual failure rates for a transformer population based on failure statistics and diagnostic measurements such as dissolved gas, and 2-furfuraldehyde analysis. The method is applicable to all types of components and the comprehensibility makes it effective for practical implementation. The results are evaluated against two health indices based on a weight factor and fuzzy logic. It can be observed that the presented individual failure rates are plausible representatives of the transformer's probability of failure. Therefore, the results can also be utilized for asset management decision-making.

No abstract

This paper propose an approach to multi-objective maintenance policy definition for electrical networks. Maximum asset performance is one of the major goals for electric power system managers. To reach this goal, minimal life cycle cost and maintenance optimization becomes crucial, while meeting demands from customers and regulators. This necessitates the determination of the optimal balance between preventive and corrective maintenance in order to obtain the lowest total cost. The approach of this paper is to study the problem of balance between preventive and corrective maintenance as a multiobjective optimization problem, where we have the customer interruptions on one hand and on the other hand the maintenance budget of the network operator. The problem is solved with meta-heuristics developed for the specific problem, as well as with an Evolutionary Particle Swarm Optimization algorithm. The maintenance optimization is applied in a case study to an urban distribution system in Stockholm, Sweden. Despite a general decreased level of maintenance (lower total maintenance cost) a better network performance can be given to the customers. This is achieved by focusing the preventive maintenance on components with a high potential for improvements. Beside this, the paper constitutes a display of the value in introducing more maintenance alternatives for every component and to choose the right level of maintenance for the components with respect to network performance.

Abstract-This paper proposes a method to allocate resources in power distribution planning and also introduces a new reliability index category, , flexibility to adjust to different laws or distribution system operator (DSO) policies of long outages. Possible legal consequences for distribution system operators are first identified and studied. A vulnerability-analysis method is introduced, including a statistical validation. The overall idea is to identify and evaluate possible states of power distribution systems using quantitative reliability analyses. Results should thus indicate how available resources (both human recourses and equipment) could be better utilized, e.g., in maintenance and holiday scheduling and in evaluating whether additional security should be deployed for certain forecasted weather conditions.To evaluate the method, an application study has been performed based on hourly weather measurements and about 65 000 detailed failure reports over eight years for two distribution systems in Sweden. Months, weekdays, and hours have been compared and the vulnerability of several weather phenomena in these areas has been evaluated. Of the weather phenomena studied, only heavy snowfall and strong winds, especially in combination, significantly affect the reliability. Temperature (frost), rain, and snow depth have a relatively low or no impact.

No abstract

Power system components usually have standard static ratings that determine the load constraints. Load constraints are designed for extreme conditions and are one of the reasons, why power systems do not use all of their potential transmission capacity. In the 21st century, efficiency and the cost of energy production and distribution have become a very popular topic, because the energy production and its transmission cost has a direct influence on sustainability. Dynamic Rating is a smart grid application, which allows using more of the system capacity by monitoring system conditions. This paper presents a literature review on the topic of Dynamic Rating. We focus on Dynamic Rating of overhead lines. Overhead lines are of great interest for Dynamic Rating applications, because of their high cost and high potential for further improvement. Different tools for analysis of real time data and ways of application of Dynamic Rating to the power system are taken into consideration.

QC 20170629

This paper propose an approach to multi-objective maintenance policy definition for electrical networks. Maximum asset performance is one of the major goals for electric power system managers. To reach this goal, minimal life cycle cost and maintenance optimization becomes crucial, while meeting demands from customers and regulators. This necessitates the determination of the optimal balance between preventive and corrective maintenance in order to obtain the lowest total cost. The approach of this paper is to study the problem of balance between preventive and corrective maintenance as a multiobjective optimization problem, where we have the customer interruptions on one hand and on the other hand the maintenance budget of the network operator. The problem is solved with meta-heuristics developed for the specific problem, as well as with an Evolutionary Particle Swarm Optimization algorithm. The maintenance optimization is applied in a case study to an urban distribution system in Stockholm, Sweden. Despite a general decreased level of maintenance (lower total maintenance cost) a better network performance can be given to the customers. This is achieved by focusing the preventive maintenance on components with a high potential for improvements. Beside this, the paper constitutes a display of the value in introducing more maintenance alternatives for every component and to choose the right level of maintenance for the components with respect to network performance.

No abstract