Final Report Summary - PROFILINGBLACKOUTS (Cascading failures in electrical networks: stochastic analysis and distributed prevention methods)
The need to reduce CO2 emissions is fundamentally changing the way the electricity grid will be operated and designed. Variable renewable generation sources such as wind and solar are less predictable and less controllable than conventional generators. In order to cost effectively integrate these sources it will be critical to adopt a range of smart grid technologies with the objective to enhance the utilisation of electricity system infrastructure. The potential benefits of this smart grid transformation are very significant and well-studied, but it is not clear what this will mean for the reliability performance of the future electricity supply systems.
The PROFILINGBLACKOUTS project aims to investigate and develop novel advanced statistical methods and tools to assess the resilience and improve the reliability performance of the electricity grid, with a particular focus on high-impact low probability events. A prime example of such events are cascading outages, where an initial outage triggers follow-up outages thus potentially leading to large-scale blackouts. The likelihood of such events occurring is vanishingly small so these events are easily overlooked. However, the impact is so significant that the possibility of such an event must not be ignored.
The research has led to the development of an efficient model for cascading outages on large random networks. The model provides insight into the fundamental parameters that affect the resilience of the realistic large-scale electricity grid. The resilience is quantified through conducting a large number of computer simulations, and the results are analysed with a novel data analysis method that accurately accounts for statistical fluctuations. This leads to results with strict reliability bounds. In addition, the research project has resulted in a novel stochastic control method for domestic refrigerators that can support real time balancing of demand of supply. It enables individual appliances to take actions that collectively stabilise the electricity grid, thus significantly increasing the grid’s resilience at a very competitive cost.
The PROFILINGBLACKOUTS project aims to investigate and develop novel advanced statistical methods and tools to assess the resilience and improve the reliability performance of the electricity grid, with a particular focus on high-impact low probability events. A prime example of such events are cascading outages, where an initial outage triggers follow-up outages thus potentially leading to large-scale blackouts. The likelihood of such events occurring is vanishingly small so these events are easily overlooked. However, the impact is so significant that the possibility of such an event must not be ignored.
The research has led to the development of an efficient model for cascading outages on large random networks. The model provides insight into the fundamental parameters that affect the resilience of the realistic large-scale electricity grid. The resilience is quantified through conducting a large number of computer simulations, and the results are analysed with a novel data analysis method that accurately accounts for statistical fluctuations. This leads to results with strict reliability bounds. In addition, the research project has resulted in a novel stochastic control method for domestic refrigerators that can support real time balancing of demand of supply. It enables individual appliances to take actions that collectively stabilise the electricity grid, thus significantly increasing the grid’s resilience at a very competitive cost.
