Methods for quantifying and communicating risks and uncertainties related to extraordinary events in power systems

Abstract

Society is dependent on a reliable electricity supply for its normal operation. Blackouts can have severe societal consequences and are sometimes termed extraordinary events. These events are often associated with a high impact and a low probability of occurring. Extraordinary events can have consequences that are deemed unacceptable, yet due to their low probability of occurrence they are not sufficiently identified and communicated through the means of traditional reliability analysis. Operators need tools to plan and operate the power system to ensure that the risk of extraordinary events is reduced in a cost-efficient manner. As a response to this, it is necessary to develop new methods to understand, analyze and communicate the risks and uncertainties related to extraordinary events in power systems. This thesis contributes to this task in four ways: • A method of calculating transmission line unavailability due to correlated threat exposure is proposed. The method contributes to an improved understanding of the probability of an unwanted event. • Protection system misoperation can further weaken the power system following an initial event, and is an important part of many extraordinary events. A compact and generalized method of including protection system failures and misoperation in power system reliability analysis is developed. The method is used to study the interaction between adverse weather and protection system misoperations. • Extraordinary events that are caused by natural hazards are often associated with long outage durations due to physical infrastructure damage. However, limitations in the available data can make it diffi cult to parameterize models which include outage durations. A model to predict transmission line down-times is constructed as a possible solution to this challenge. • Appropriate communication of risk is necessary for stakeholders to make sound risk-informed decisions. The thesis develops novel risk visualizations to support this. The risk visualizations incorporates both the consequences in terms of energy not supplied and also a measure of the criticality for the affected end-users.