Neural BB: An innovative tool to improve stability studies for grid operators

As we continue our journey to deliver a decarbonised, efficient and secure energy system, the diversity of generator types providing our power will increase. 

The most common of these will be Inverter-Based Resources (IBR). IBR are generators that are connected to a converter rather than a spinning turbine that is synchronous to the grid such as battery energy systems, wind and solar generators.

IBR have faster dynamic behaviours than synchronous generators such as gas, nuclear or biomass. The most common analysis methods we currently use are Root Mean Square (RMS) based, which excel at modelling synchronous generators and a lot of system events accurately and quickly. However, this may not be suitable for faster transient behaviour, when the power supplied changes momentarily, which is common in a network dominated by IBRs.

Electromagnetic Transient (EMT) simulation can capture the faster fluctuations in power but takes longer to run simulations and more complex models. Neural BB is bridging the gap using lightweight models that offer the same level of accuracy with lower simulation times.

Creating a more efficient model

EMT models are more detailed, complex and require more processing power and time to run than RMS models. To bridge the simulation time gap, we are working with Transmission Excellence, The University of Bristol and The University of Bath to form a methodology to use neural networks to create a trained model for EMT, which is faster and provides the same accuracy of the complex parent model due to machine learning.

How will Neural BB solve this and what are the benefits?

By utilising this method of machine learning, we can create accurate models that can be used in future stability studies. Accurate EMT simulation could reduce costs by increasing our visibility of potential issues, accurately representing different generation types, reducing complexity and allowing more detailed models to be used more often.

Successful delivery of the project will allow margins of safety to reduce, which could lead to additional savings, particularly across system boundaries that might be constrained on the network.

How can I find out more? 

Throughout the duration of the project, you’ll be able to see a series of reports that will share project outcomes, lessons learned, and best practices on the ENA portal. 

View here