The 2019 UK blackout was a warning sign. Whilst it was a rare event – having two major power stations fail within minutes of each other is not a common scenario in an engineer’s handbook – it did raise a number of red flags and posed the question whether action could have been taken sooner to prevent it in the first place.
Two years on and pressure on the grid continues to grow at an unsustainable rate. This is compounded by capacity lost due to a fire on the critical IFA Interconnector subsea power cable connecting the UK and France, where most of the former’s back-up power is sourced from, in September, with fears that it will not be back to full operating potential for another two years.
The surging demand for ‘clean’ energy has led to power being sourced from less conventional sources, that are impacting the grid in ways not previously anticipated. For all the investment and target-setting, risks remain.
This will always likely be the case. But the severity and likelihood of these events can be managed whilst the wider discussions around infrastructure resilience take place. Developments in technology and the gathering of historic and real-time data reveals how much pressure a specific area of the grid can operate under before disturbances result in lost power. As stated in N-1 Reliability Criteria, a system needs to be able to withstand the sudden outage of a particular component and continue operating at a sufficient level.
Big data, which is used in Vysus Group’s Promaps probabilistic risk assessment software, has the ability to provide an overall view of the current likelihood of faults in real-time and the impacted areas, therefore making it easier to prioritise and justify operational actions such as the rerouting of power and tasks such as maintenance, as well as how these actions mitigate the cost of bringing in reserve power.
Real-time probability assessments ensure that the most accurate information is provided for making critical decisions with little delay. On many previous occasions, this information is derived from a non-quantifiable source, often an educated assumption. The use of big data, in conjunction with real-time analysis software, quantifies these assumptions and allows swift decision-making.
As we have already seen this year with the major outage in Texas, caused by a winter storm, initiating protocols at certain levels of disruption can prevent much wider problems. According to officials, blackouts were purposely implemented in order to prevent the entire Texas grid going offline completely. But why did these decisions have to be made in the first instance? And what has not been done to prevent a worse outage when it should?
These questions are becoming increasingly urgent with the threat from adverse weather intensifying. For all the warnings about changing weather patterns and the frequency of significant metrological events, preventative action is still lacking.
If we use the analogy of a UK smart-motorway giving advanced warning of an accident, Promaps works in much the same way. It would be impractical, not to mention dangerous, to bring all the lanes of traffic to a sudden stop from 70mph, hence the gradual reduction of the speed limit and rerouting traffic, and a similar approach should be taken with grid faults. By understanding the consequences of specific actions, backed up by clear, factual data, operators have the chance to implement the measure that will cause the least disruption and costly for utility operators and, as we are already seeing, the consumer.
At Vysus Group, we are seeing this approach already being used across the North Sea in Norway where probabilistic risk management is facilitating a stronger working relationship between government and grid operators across multiple regions. Challenges arise when critical components of the grid lie on the boundaries between two or more different localities as it is not always clear how a particular action will affect the neighbouring nodes in the event of a fault. Taking preventative measures in these instances removes the likelihood of the ‘wrong’ action having further repercussions.
Of course, any changes to the ways in which grid operators manage the arterial networks that keep our lights on will not happen overnight. While the future has never been so impossible to predict, lessons will need to be learned so that we are not caught cold this winter.