Cascade LNG Refrigeration Load Control for Maximum Throughput
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Solution Overview
Problem
The operation of liquefied natural gas (LNG) facilities is challenging due to numerous process variables, changing ambient conditions, and shifts in feed gas composition, leading to sub-optimal operation and monetary losses as human operators struggle to manage the complex systems effectively.
Innovation Solution
An apparatus and method utilizing a processor and memory to adjust manipulated variables in a cascade LNG facility, optimizing refrigeration system loads and processing rates through models that maintain controlled variables within defined limits, employing linear or quadratic economic optimization to maximize LNG and natural gas liquids production.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If human operators manually adjust operating variables, then the facility can be controlled, but the operation remains sub-optimal due to operator limitations
Solution Approach 1:
The control system performs self-optimization by automatically monitoring process variables, evaluating multiple operating scenarios, and adjusting manipulated variables without human intervention. The system serves itself by making real-time decisions to maximize production while maintaining safe operating conditions, eliminating the need for operators to manually optimize each parameter.
Solution Approach 2:
The patent replaces human operator decision-making with an automated computer-based control system that uses algorithms, process models, and optimization techniques. This substitution transforms manual mechanical adjustment into automated intelligent control, enabling the system to process multiple variables simultaneously and make optimal decisions faster than human operators.
2Measurement precision
If the number of process variables monitored is increased to improve control accuracy, then operating precision improves, but operator workload increases
Solution Approach 1:
The patent extracts the complex task of monitoring and coordinating numerous process variables from human operators and transfers it to the automated control system. The computer-based system selectively monitors relevant process variables, process constraints, and operating conditions, separating essential control functions from unnecessary complexity and focusing computational resources on critical parameters.
3Productivity
If the facility operates at maximum capacity, then production increases, but the risk of exceeding safe operating limits increases
Solution Approach 1:
The control system performs preliminary evaluation of multiple operating scenarios and predicts future process states before making adjustments. By using process models to simulate potential outcomes and identify optimal operating points in advance, the system proactively prevents violations of safe operating limits while maximizing production, rather than reacting after problems occur.
Solution Approach 2:
The patent implements dynamic optimization that continuously adapts operating parameters based on real-time process conditions, feed gas composition changes, and environmental factors. The system dynamically adjusts manipulated variables to maintain operation at the boundary of safe limits, allowing maximum production when conditions permit while automatically retreating to safer operating points when constraints are approached.
Data Source
AI summary
At least one model is associated with one or more manipulated variables and one or more controlled variables, which are associated with a cascade liquefied natural gas facility. Adjustments to the one or more manipulated variables are made using the at least one model to maintain the one or more controlled variables within defined limits. For example, a controlled variable may identify an overall load placed on multiple refrigeration systems in the facility. The one or more manipulated variables may be adjusted to increase the overall load placed on the refrigeration systems. The overall load can be determined by identifying a maximum of: a projected feed gas rate to operate a propane refrigeration system at maximum load, a projected feed gas rate to operate an ethylene or ethane refrigeration system at maximum load, and a projected feed gas rate to operate a methane refrigeration system at maximum load.