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

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.