The expanding and interconnected electricity network poses challenges for National Grid Electricity Transmission (NGET) in monitoring and assessing network resilience. Currently, tracking resilience involves multiple metrics on separate Power BI pages, making it difficult to view overall resilience and hindering timely decision-making during storms or major events. This fragmented approach can lead to suboptimal maintenance and repair decisions. To address these challenges, the proposed project aims to incorporate probabilistic risk analysis to further improve resilience assessments, enhance decision-making accuracy using risk scores, and identify weak areas in the network. Additionally, simplify monitoring through a holistic map view. Ultimately, the project seeks to improve network resilience by streamlining risk identification and establishing minimum resilience levels for substations. FRAME II will be the second phase following the Proof-of-Concept (POC) phase in NIA2_NGET0075 Framework for Risk Analysis and Modelling of Events (FRAME I) .
Benefits
- Facilitates faster decision-making during network events and extreme weather conditions.
- Enables more accurate decision-making by utilising holistic resilience information.
- Supports improved investment justification and asset management decisions.
- Enhances overall network resilience by identifying weak areas and establishing minimum resilience levels for substations.
- Simplifies the identification of network areas at increased risk during storms, particularly due to weak Delayed Auto Reclose (DAR) functionality.
