Strategic Innovation Fund

Climate Resilience Decision Optimiser (CREDO+)

Project Data

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End date:





CReDo+ is a novel enhancement of the original Climate Resilience Demonstrator (CReDo) climate change adaptation decision support tool, with a primary focus of extending to the emerging risk of extreme heat.

CReDo+ will scale up across the energy sector and develop a user-friendly platform for asset experts to quantify their combined tacit knowledge of risk under extreme weather conditions into new statistical models. By connecting these asset impact models across the network, CReDo+ will capture a system level view of cascading risk, enhancing the ability of network operators and wider connected asset owners to build systemic climate resilience and robustness.

What is the project about?

Climate change is expected to increase the frequency of severe weather events. The Committee on Climate Change reported that “Connectedness of infrastructure systems means that climate and weather-related impacts in one system can cause large and cascading failures in connected systems” and that “many organisations are struggling to fully assess risks from infrastructure interdependencies”, which is echoed by the National Infrastructure Commission. Energy networks are at the heart of critical infrastructure, interdependencies, and cascading risks. 

Reliable asset models that capture the impact and risk of different weather events are critical. However, typical data-driven (machine learning) approaches are limited by sparse historic failure data of rare weather events and a lack of digitisation across industries. Innovation is required to scale across different weather scenarios, use cases and networks. 

How we’re doing it

The goal of Alpha Phase was to develop a small-scale prototype that is usable for the purposes of demonstrating CReDo+’s overall concept. The project is being delivered collaboratively between partner organisations UK Power Networks, Connected Places Catapult (CPC), the Science and Technology Facilities Council Laboratories (STFC), Computational Modelling Cambridge Limited (CMCL), and National Grid Electricity System Operator Limited (NG ESO). The prototype was a viable demonstration of the key functionality of the tool and the development of the extreme heat use case in CReDo. The project included the following components: 

  • UK Power Networks engagement and data
  • CReDo asset and system modelling
  • Digital Elicitation Tool (small scale prototype).
  • CReDo extreme heat prototype
  • Business and cost benefit analysis
  • Engagement and Dissemination

The Alpha Phase of the project ran in parallel to CReDo’s successful sister bid, the Ofwat Breakthrough Challenge Catalyst 3 “CReDo – Extreme Heat Scenario”. The Ofwat-funded project will continue until June 2024 and will focus on developing the extreme heat use case from a water sector perspective. Both projects were designed without interdependencies, however, there have been significant synergies and learnings to exploit between the two; this has led to more efficient developments in both projects and more robust, higher quality outputs across each project. 

What makes it innovative

CReDo+ is a novel solution as it will 

  1. Address data gaps in understanding asset behaviour by creating new probabilistic failure models for extreme heat. 
  2. Increase the granularity of data available to DNOs for their assets and identify interdependencies with other utilities’ assets to inform cross-sector resilience approaches.  
  3. Incorporate economic and societal cost data to quantify the implications of failure, such as costs of recovery, repair, impact on supply, to support the investment case for building whole system resilience.  
  4. Extensible to other assets and risks.  
  5. Implement the risk models in the CReDo technology to provide a new understanding of predictability, robustness, and quantification of uncertainties at a whole system level. 
  6. Prototype a user-friendly digital elicitation tool to create asset impact risk models 

What we’re learning

We learnt:

  • The strategic focus of UKPN and other DNOs in relation to climate adaptation focusing on operational impacts. 
  • Lack of data to inform asset behaviour models without expert intervention, meaning that the BAU approach to forecasting faults on the network cannot anticipate impacts of extreme heat leading to gaps in investment planning. 
  • Applicability of available extreme heat climate data for Alpha prototyping, and UK capability to generate new data for Beta deployment.   
  • Approach to integrate the CReDo+ tool with CReDo technology, and as a digital resource in the DNO landscape.  
  • Modelling principles for extreme heat and differences versus prior work on flooding. 
  • Digital elicitation tool wireframe and requirements for a graphical interface for model building and distributing online questionnaires, informing the project roadmap.
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