IDENTIFYING CRITICAL UNCERTAINTIES IN POWER SYSTEMS (ICUPS)

It is very important that the electrical power grid is secure and reliable. Almost all aspects of our lives are dependent on electricity, from basic needs like heating and lighting to medical technology and vast city infrastructure and transportation systems. Just one day of blackout would cost the UK billions of pounds in lost revenue from businesses that are unable to operate - and the impact on society would be enormous. It is also very important that we begin, as a nation, to generate more electricity from low-carbon, renewable technologies such as solar and wind power. This is essential to ensure that we slow the effects of climate change and develop energy resources which will last for future generations.

Renewable energy sources are unpredictable - we just don't know exactly how much electricity we can generate from the wind turbines or solar panels day-to-day. We can make predictions but they are uncertain predictions - we can't make guarantees. Unfortunately this doesn't help when it comes to making sure our electricity supply is secure and reliable. Electrical demand has to be balanced with electrical generation at every instant. We presently don't have the technology to store electricity on a large scale (we can't build batteries that could power the whole country), and the unpredictability of large numbers of wind farms and solar panels makes it harder and harder to keep the system balanced. Get this balance wrong, and the system could collapse, potentially resulting in a nation-wide blackout. To make matters worse, this is just one source of uncertainty among many others that affect the performance of electricity grids. For example, the wide-scale uptake of electric vehicles will add lots more demand for electricity which can literally move around the network - so not only is there uncertainty over when the vehicle is charged, but also where it is charged.

There is a pressing need to fully understand how uncertainties will impact on the performance of power systems. This begins by building an understanding of which uncertainties are the most important. There are so many potential sources of uncertainty that getting enough data to understand how they all change would be completely impractical. Instead, if we can identify the most important uncertainties - the critical uncertainties that dominate the way the electricity grid behaves - we can focus our future attention on understanding those first, and stopping them from causing any problems.

Identifying these uncertainties is not a simple task and requires new tools and techniques to be developed. These tools not only need to examine all possible consequences of all the possible scenarios (as it is usually unexpected scenarios that cause the most problems), but also need to quantify the importance of different sources of uncertainty in practical terms so power system engineers can be confident in the decisions they are making. This project will develop these tools in the form of new software algorithms which will be thoroughly tested to find their strengths and limitations.

This work will provide the foundation for future research on uncertainty in electrical power grids, helping to identify and solve critical issues to improve the security and reliability of the electricity supply.

The principle impact of this project will be the changed behaviour within utilities and operators, enabling them to better understand the impacts of uncertainties on power systems and mitigate for their impacts. This project will liaise closely with interested industrial stakeholders (particularly project partners National Grid) throughout the whole project programme. This partnership will increase the impact of this research in a number of ways. Firstly, the project will be more thoroughly contextualised by practical electrical engineering considerations and can therefore be directly implemented by power systems operators. Secondly, the industrial stakeholders will be directly exposed to the research, highlighting not only its relevance but also the benefits that can be achieved through further development. This close collaboration will allow stakeholders to direct and shape the form of the research outputs to facilitate easy transfer of knowledge and realisation in practical applications. As can be seen from the attached Letter of Support from National Grid, there is a strong interest in this work and its direct application on the UK electricity network. It is anticipated that future development will lead directly to the targeted mitigation of critical system uncertainties to improve system stability. As such, this work has the potential to impact on the general population by helping to deliver reliable electricity.

This impact will be accomplished through the development of novel algorithms to perform sensitivity assessments for power system applications and the thorough testing and benchmarking of these algorithms using a rigorous methodology. This will represent a significant advance compared to current practice in power systems research. This project represents a platform for future uncertainty analysis which can be built upon by further research to ensure power systems operate securely in the future. Furthermore, the statistical tools developed may have potential applications in other fields of complex systems engineering, helping to solve the Engineering Grand Challenges identified by the EPSRC. Within the University of Manchester, the PI will forge new links with departments working on complex systems modelling in other fields in order to help cross-pollination of techniques and spark new ideas for future research directions.

There is clear potential for this project to inform policy decisions on uncertainty modelling with respect to energy networks. There are many open questions currently unanswered by the research community. For example, can high-impact-low-probability events such as blackouts be accurately modelled with high confidence or are alternative approaches required in order to establish practical mitigation solutions? The PI will engage in the uncertainty debate to inform policy processes and will use this research as platform from which to contribute to professional position papers and technical reports - such as those produced by HubNet and IEEE PES working groups and task forces, of which the PI is a member.

The project may generate IP in the form of new algorithms for power system uncertainty analysis. The aim of the project is to make this library of resources available for access to the wider community under appropriate open licenses. The University of Manchester IP office (UMIP) will be consulted with in order to protect and manage this IP whilst ensuring it is widely disseminated and can form a platform for future developments in this research area. This will be completed in close collaboration with UMIP in a manner consistent with EPSRC guidelines.

Due to the size and scope of this First Grant proposal, the methods developed and subsequent impact will be focussed on power system stability, however the wider applications extend far beyond this domain of energy networks research.