Using contingency analysis to keep the distribution network secure and reliable: UK Power Network’s Kent Active System Management

Ahead of the Low Carbon Network Innovation (LCNI) Conference, taking place from the 6th – 7th December in Telford, we will be posting introductions to some of the ground-breaking innovation projects that will be presented there by our members.

Alex Jakeman, Innovation Project Lead at UK Power Networks, discusss the Kent Active System Management (KASM) and how the project has been exploring the value of contingency analysis software in operational timeframes on the network in East Kent.

The renewable energy rush of the last five years has meant that in some parts of the country, like Kent, the amount of energy generated sometimes exceeds local demand. To meet this challenge we came up with Kent Active System Management, or KASM. We want to allow more renewable energy connect to our network at lower cost.

KASM is trialling the use of contingency analysis and forecasting tools on the GB electricity distribution network. Its contingency analysis is an advanced form of power flow modelling that can evaluate the impact of different conditions, such as planned outages or rapid changes in energy flow on the network in close to real-time.

As the project draws to a close at the end of this year, it has demonstrated that advanced modelling and forecasting can help us get more out our existing infrastructure.

For the first time ever, it has established a co-ordinated real-time data exchange with the national transmission system so that control engineers can get an even greater understanding of power flow when they’re the network.

When we set out, our aim was to allow more energy from distributed generation onto the network. By sharing data with the national transmission system and developing new software tools we are now able to analyse many complex scenarios in seconds and predict the possible impacts of control decisions as they are made. Our engineers now have the confidence to allow more distributed energy onto the network.

So far the software has analysed more than 11,000 different case studies of running the network. Up until now analysis like this would have been done manually and we’d typically have got through fewer than 500 year. We’ve simulated what would have happened on the network during the summer outage season when works are carried out, and proved that KASM would have given us the confidence to allow more energy onto the network. By 2030 we have calculated it will save customers £65m.

Feedback from our engineers has been really encouraging. They said it helped them identify the key challenges when assessing new renewable energy connections in the region, and that visibility of the national transmission system was a “critical” piece of information to create more accurate models.

But KASM is doing much more than just providing tools that benefits our customers today – it’s also one of the building blocks of the electricity network of the future. The more accurate data it provides, the more that we are able to operate our network in a pragmatic way rather than always just considering worst case scenario. That means lower costs and quicker connection times for renewable energy generators.

As we undertake the transition towards a Distribution System Operator, managing a much more complex and interconnected energy system, KASM allows us to put the customer first.

Alex Jakeman is at the LCNI Conference at 11.20am on Thursday 7th December.

For more information about KASM, please click here.

UK Power Networks will be presenting an update on the KASM project at the LCNI conference on Thursday 7th December.

For more information about LCNI, and to buy tickets, please click here.





Comments (1)

  1. The renewable energy rush of the last five years has meant that the amount of energy generated sometimes exceeds local demand.

    What a great issue to be having, and good to see you are designing new systems to make sure that it doesn't hamper the further growth of renewable energy in the future.

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