Project Summary
Challenge:
"Black swan" events are low-probability, high-impact events which can have serious repercussions. Currently, for energy networks, these events are addressed as they arise and are not fully considered in strategic decision-making. Major global events over the past few years (COVID, war, economic downturn) have highlighted limitations of this reactive approach: the whole system impacts of, and interactions between, black swan events are not systematically captured. This limits future operational resilience.
Moreover, the climate emergency impacts the GB energy system through increasingly challenging operating conditions (e.g. extreme weather events), while the need for decarbonisation drives system diversification (e.g. different generation types; increased electrification; transitioning from natural gas).
Solution:
A methodology is required to quantify the impact of black swan events, particularly as energy system operation evolves. Novel use of probabilistic modelling will form a key part of the methodology, to account for high levels of uncertainty around such events. This approach builds on emerging thinking in this area from industries where risk management and costing of extreme events is paramount to that industry's success, e.g. insurance, banking. It will also use emerging datasets on infrastructure resilience and weather and climate patterns collated by academia and the Met Office.
Scope:
This project meets the Innovation Challenge of "Improving energy system resilience and robustness", by improving the approach to the identification and analysis of extreme events and their impacts on the GB energy system.
The project output is anticipated to be a decision-making framework, supported by scenario modelling capabilities to allow evaluation of, and build resilience against, future black swan events. This capability would be developed and integrated into business as usual (BAU) activities, including system planning and Future Energy Scenario (FES) work.
Users:
Users of the innovation would be the System Operator and Networks' operational and planning teams, who would use the project outputs to better understand and pre-empt the impact of extreme events on the grid and wider energy system.
Project Team:
NGESO will lead the project, collaborating with:
- Electricity network operators: NGED, SSEN Transmission, SSEN Distribution.
- Gas network operators: NGGT and Cadent Gas.
- Lloyd's of London - insurance costing and risk management experts.
- University of Strathclyde - research partner and expert in electrical systems innovation.
- Met Office - climate data and modelling experts.
- Frazer-Nash Consultancy - probabilistic modelling and systems engineering experts
- Energy Emergencies Executive Committee - management of future power disruption event
Innovation Justification
Existing approach
Current approaches to system resilience and security of supply need to evolve from models established when the bulk energy system was constructed around 50 years ago. Previously, extreme events did not have as significant impact as the system was supplied more locally, was less interconnected, and energy was not as vital to the everyday functioning of the economy. Now, even short-term power outages can cause serious problems for the systems that the economy relies upon. With a globalised supply chain, the GB energy system is more vulnerable to worldwide events, while the climate crisis regularly provides new challenges.
The current reactive approach to extreme events can result in slower responses, lower system availability and increased costs for network operators. Recent extreme events, such as the pandemic and global economic downturn, have highlighted the need for a refreshed approach.
Novel solution:
The nature of black swan events means they are difficult to quantify, with little data available to validate results. It is therefore proposed to investigate the latest thinking on black swan events from sectors at the forefront of risk evaluation (e.g. insurance, banking) and determine how this knowledge can be adapted and applied to the energy system. Building on this, probabilistic modelling tools will be developed to test various scenarios and predict their impact on the whole energy system.
The modelling results will allow optimisation of responses to extreme events and minimise the impact and cost to energy system stakeholders. Additionally, the results will feed into planning activities, such as FES, ensuring the benefits of the refreshed approach also feed into long-term system reliability.
SIF suitability:
The project is a novel approach that cannot be resourced via existing business processes, as it must be developed and tested separately to avoid impact on the current security of supply. The project brings together partners with significant breadth and depth of expertise across the energy, insurance, and academic research sectors; offering a diverse range of thoughts which will be pivotal in pioneering innovations.
The SIF process offers the best model for development, comprising:
- a Discovery Phase to investigate other sectors' risk approaches and determine their applicability to the energy sector.
- pending a feasible approach, a subsequent Alpha Phase to develop the initial models and consider requirements for integration into existing processes.
- a Beta Phase to develop and test a complete model, alongside a detailed plan for BAU integration.
Project Benefits
We will develop the methodology for calculating project benefits as part of the Discovery Phase. We would expect a rough order of magnitude (ROM) benefit calculation to be carried out as part of the Alpha Phase, with a more detailed analysis taking place in the Beta Phase. For the solution to be adopted as BAU, it will have to undergo independent scrutiny by Ofgem to demonstrate that it offers significant benefits in comparison with existing methodologies. This would be taken into consideration when planning the later stages of the project.
The following gives an initial indication of how we expect to be able to demonstrate project benefits:
Financial: savings in network restoration costs, demonstrated by retrospectively examining system performance in previous black swan events, such as Storm Arwen, and outlining how our proposed model would have improved the response.
Environmental: we will consider the existing response to extreme events compared with the response recommended by our model, and will calculate the resulting carbon benefit using established methodologies for assessing CO2 savings.
New to Market: the benefits of new services that could be developed to improve system resilience can be assessed by reference to the benefits provided to the system by past developments in other innovative areas, such as flexibility services.
Revenues -- Creation of new revenue streams: the potential income streams from leveraging the project's IP (e.g. licensing) will be considered.
For benefits to be fully realised, it is vital that project learning is shared as widely as possible, so that all stakeholders have opportunities to use outputs and provide feedback. This is partly achieved by having a diverse team in the initial stages, but will be enhanced by considering additional project partners for in future (e.g. water companies, transport providers) and by disseminating findings via relevant forums, such as the Energy Emergencies Executive Committee (E3C) and the Electricity and Gas Networks Forum.
