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Gas Distribution
Project Details
Documents
Ideas for future projects?
Mar 2018
Gas Distribution
Universal Temperature Controller using Artificial Intelligence
Reference:
NIA_SGN0120
Status:
Complete
Start Date:
Mar 2018
End Date:
Mar 2019
Funding Licencee(s):
SGN
Contact:
Keith Ellison, Innovation Project Manager
Click here to send a question to the contact.
Funding Mechanism
Network Innovation Allowance
Research Area:
GD - Reliability and maintenance
Core Technology(ies):
Maintenance & Inspection
Estimated Expenditure:
£57,700.00
Introduction:
This project aims to assess the potential application of a universal controller based on Artifical Intelligence (AI) to act as an intermediary between a traditional station exit temperature signal and an installed preheat asset.
Objectives:
This project will include:
Teaching the AI controller:
Select a sample of 3 sites with different operating characteristics.
Use data mining techniques to identify process bottlenecks, energy saving opportunities and process variability issues.
Train the AI to assess performance with the minimum number of inputs for maximum potential application (Inlet Pressure, Outlet Pressure, Station Outlet Temperature, Historic Weather).
Development of a virtual system expert to advise on “optimal operation” to help guide process performance from past operating data.
Optimise computation for data efficiency.
Assess reliability and robustness for suitability on critical infrastructure.
Hardware Specification:
Determine computation requirement (Central Processing Unit (CPU)/ Graphic Processing Unit (GPU).
Develop physical specifications (considering any restrictions).
Input / Output specifications and protocols.
Review SGN specific requirements / Applicable standards.
Determine power requirements.
Review connectivity (Global System for Mobile Communications (GSM)/ Wi-Fi etc.).
Determine appropriate security & cyber-security protocols.
Remote update and control.
Implementation:
Development of a project implementation roadmap for site integration.