Digital Twin Control for Synthetic Fuel Process Optimisation
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Solution Overview
Problem
Existing synthetic fuel generation plants require significant human input for efficient operation and continuous adjustment to maintain high-quality and quantity of fuel production, lacking automation for optimal control.
Innovation Solution
A control system utilizing a digital twin and machine learning model to predict future states and optimize fuel generation processes, enabling automated and continuous monitoring to achieve high-quality and quantity of fuel production with minimal human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If extensive human input is used to operate the plant, then fuel quality and quantity can be maintained, but automation level and operational efficiency deteriorate
Solution Approach 1:
The control system performs self-optimization by automatically adjusting plant parameters based on real-time data from sensors and the digital twin model, eliminating the need for continuous human intervention while maintaining optimal fuel production
Solution Approach 2:
The system implements closed-loop feedback by continuously monitoring plant state through sensors, comparing actual performance against predicted performance from the digital twin, and automatically adjusting parameters to maintain optimal operation
2Productivity
If continuous adjustment is performed to maintain fuel quality, then fuel production efficiency improves, but energy consumption and operational complexity increase
Solution Approach 1:
The digital twin model predicts future plant states and optimal parameter adjustments before they are needed, allowing the system to proactively optimize fuel production rather than reactively responding to deviations, thereby reducing unnecessary energy-consuming adjustments
Data Source
AI summary
A control system for optimising a fuel generation process performed by a synthetic fuel generation plant. The system comprises an interface unit configured to be communicably coupled to the synthetic fuel generation plant; a digital twin representative of the synthetic fuel generation plant; and an optimisation unit in communication with the interface unit and the digital twin The optimisation unit is configured to perform an optimisation process to determine, from an initial state of the synthetic fuel generation plant, an updated state of the fuel generation plant using the digital twin.