University of Surrey energy algorithm can drive greener grids
Researchers at the higher education institution believe they have developed a solution that can lead to a more balanced and efficient electricity network.
The University of Surrey team has unveiled an algorithm which can model how smaller power networks distribute energy, which is a key step in ensuring grids are capable of transitioning to renewable and low emission sources.
Renewable sites, along with devices fitted to buildings such as heat pumps and batteries, all contribute to a very different grid from those fuelled by oil and gas. Not only are networks best managed at a local level, some sources, such as wind, can vary in reliability, meaning there could be times when too much energy is produced compared with demand, or too little is available during peak hours in calmer weather.
The result requires a far more complex approach to energy management to avoid the need to switch off things like wind turbines or reintroduce highly polluting fossil fuels to make up the difference. According to those in Surrey, the answer may come in a kind of predictive automation, which can gauged when localised grids are likely to be unbalanced, and either recommend steps to avoid this.
This might involve limiting the number of heat pumps allowed in a single area. Or prioritising battery storage to prevent systems becoming overwhelmed when there is too much power. The process takes into account current prices, available government subsidies, modelling demand and more, to ensure the most accurate and impactful steps are taken.
‘Changes in energy prices, the cost of batteries, or government subsidies, can all have large effects on which solutions are best for a particular location,’ said Dr Ishanki De Mel, who worked on the algorithm project. ‘Our research could help shape Government policy – revealing clearly how effective subsidies and system design can pave the way for net zero initiatives.’
‘Greening the grid is essential, yet it’s an enormous challenge – and it is clear from our modelling that there is no one-size-fits-all approach. Instead, our model shows how local constraints need to be considered when designing new power networks,’ said Dr Michael Short, Senior Lecturer on Process Systems Engineering at the University of Surrey. ‘Government now needs to think seriously about whether new subsidies, or even market changes such as pricing electricity differently during off-peak periods, are needed to enable communities to move towards net zero.’
You can read the full research paper in the Journal of Applied Energy.
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