Cascading outages in power systems are costly events that can quickly result in power outages for millions of customers and a widespread blackout. Usually, large power system blackouts or major power outages are not caused by a single fault; it is more likely to be the result of a sequence of disturbances, including initial events, additional failures, consequent protective actions, and accelerated cascading outages, leading to a loss of stability. If system operators had real-time information about the risk of cascading outages, appropriate counteraction could be taken in critical situations to avoid further cascading outages and an eventual system blackout.
Responsibilities and tasks
The PhD project focuses on research and development of methods that give an early warning for cascading outages in electric power systems in real time. For the method development, real-time wide area PMU measurements are used to provide full observability of the system conditions.
The methodology will focus on how relevant information regarding the risk of cascading outages can be extracted out of a given PMU snapshot of the system condition. For this purpose, graph theory based algorithms could e.g. be developed for identifying the smallest set of tripped branches that result in cascading outages.
Main tasks:
- Develop methods for assessing the vulnerability of the system against cascading outages
- Develop methods for determining preventive actions when conditions for cascading outages have been identified
- Implementation and test of the developed method in DTU based research laboratory facilities for electric power and energy -PowerLabDK
