This project explores the use of Artificial Intelligence to inform improved National Transmission System (NTS) network planning decisions, namely, to optimise the configuration of network assets to ensure sufficient pressure at NTS offtakes. 
The aim is to develop an AI-based software tool that allows analysts at ESO to rapidly assess ‘Static’ day-to-day NTS Offtake scenarios, by bulk-solving more standard cases, allowing the prioritisation of less standard instances, and helping with the rapid assessment of different network configurations for more complex scenarios. As an extension, the project will assess the feasibility of using AI to optimise ‘transient’ scenarios, where inputs are flexible at more granular intervals, and inform longer-term network planning decisions to accommodate hydrogen. 

Benefits

• Expertise targeting: Ability to bulk-solve day-to-day operational scenarios would allow analysts to focus on more complex future gas network planning decisions. 
• Labour and time savings: Reduced day-to-day effort required in manually running static scenarios. It is envisaged that the solution will save multiple hours per analyst per day.  
• Enhanced planning capability: Develop new capability to rapidly assess the feasibility of future NTS methane capability requirements, and reconfiguration of the NTS as the role of hydrogen grows.