URSES - Uncertainty Reduction in Smart Energy Systems 

Research Themes: software technology & intelligent systems, high-tech

A TRL is a measure to indicate the matureness of a developing technology. When an innovative idea is discovered it is often not directly suitable for application. Usually such novel idea is subjected to further experimentation, testing and prototyping before it can be implemented. The image below shows how to read TRL’s to categorise the innovative ideas.

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Summary of the project

In the future, the increase in generation of energy from renewable sources will intensify stability problems and will increase the uncertainties in planning and operation of electric power systems. Unexpected disturbances and inadequate system monitoring can cause catastrophic failures such as blackouts. Existing monitoring and control schemes often cannot cope with these problems due to the lack of coordinated control when the system is affected by large disturbances. The researchers aim to create a wide-area intelligent system, that empowers the future power grids by providing real-time information, quickly assessing system vulnerability, and performing timely corrective control actions based on system-wide considerations. The researcher developed algorithms that can help in deciding when and where to split parts of the grid in order to maintain the grid stability, prevent blackouts, and minimize the impact on the power consumers.

What's next?

The innovative idea has been developed for monitoring and control of the stability of medium to large scale electric power grids up to the European scale. The next step could be to apply the found solution for protecting a realistic power grid. Furthermore, some enhancements in terms of modelling would be desirable to capture the full degree of complexity of large-scale power grids. 

Contribution to the Energy transition?

With a new way for timely corrective control the researchers aim to prevent catastrophic blackouts, independent of any future network generation mix, unpredictable topology and load profile.

dr. Ilya Tyuryukanov

dr. Matija Naglic

dr.ir. Marjan Popov

Faculties involved

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