Reliability Evaluation of Distribution Systems Considering Failure Modes and Network Configuration

University dissertation from KTH Royal Institute of Technology

Abstract: Power distribution networks are recognized as the constituent part of power systems with the highest concentration of failure events. Even though the faults in distribution networks have a local effect when compared to the generation and transmission sides, major contingency escalation events are being more frequently reported from this section. The various aspects regarding the reliability and performance of distribution networks are identified as an important topic. Integration of new technologies, automation and increased penetration of distributed generation is expected to make improving and even sustaining high reliability standards a complex task. This thesis presents developed approaches to quantify and analyze the complex correlated failure probabilities of different failure modes in distribution networks. A theoretical simulation model that relates to real world data to measure false tripping probabilities is developed and tested. More simplified approaches that utilities can exercise with readily available data in fault registers are also established.  Optimal configurations that could improve system performance and respective investment costs are analyzed and savings in system reliability at the cost of grid investments are modelled. The optimization helps in prioritizing the most critical investments by considering the system impact of reconfigurations focusing on meeting customer demands and respecting transfer capacities of weak links. The value of existing networks and willingness of the grid owner in investing can be integrated into suggestive alterations to assist decision making in planning and maintenance allocation. The thesis makes both system specific and generalizable observations from detailed data collection from power utilities. The observations and results have potential in aiding future research by giving important understanding of the reliability impacts of network structures and of control and protection equipment.

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