The aim of the project was to develop control algorithms that will improve system stability and enable higher levels of renewable energy generation sources, such as wind energy, to be safely integrated into the electrical system.
The techniques developed make use of data gathered from all over the network and are able to account for the uncertainty inherent in future systems.
The computational models and control algorithms developed by this research can be applied to both new and existing High Voltage Direct Current (HVDC) power lines, exploiting the fast controllability of this technology to significantly improve the stability of the entire network.
Power systems have to be constantly balanced to ensure that power generation and consumption are equal at every moment of time.
If there is a mismatch the system can start to cascade towards a total blackout, with enormous economic and social consequences. Managing this balance when there are many uncertain renewable energy sources is problematic and new methods of maintaining system stability are vital.
HVDC systems provide an efficient method of not only delivering electrical power from distant renewable resources to customers, but also actively managing the stability of the system as a whole. This in turn enables the integration of higher levels of renewable generation into the power system – reducing the amount of CO2 released as a result of electricity generation.
The number of HVDC lines being installed is growing rapidly worldwide. There is a huge potential to develop the controllers from this research for trial applications within real systems.
- R Preece, J V Milanovic, “Tuning of a Damping Controller for Multi-terminal VSC-HVDC Grids using the Probabilistic Collocation Method”, IEEE Transactions on Power Delivery Special Issue on “HVDC Systems and Technologies”,vol. 29, pp. 318-326,2014.
- R Preece, J V Milanovic, A M Almutairi, O Marjanovic, “Damping of inter-area oscillations in mixed AC/DC networks using WAMS based supplementary controller” IEEE Transactions on Power Systems, vol. 28, pp. 1160-1169, 2013.