Active Cloud Point Controller for Biofuel Refining
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Solution Overview
Problem
Refining systems face challenges in dynamically adjusting the cloud point of biofuels to meet varying operational demands, as existing methods often result in yield reduction and inefficiencies when trying to maintain the fuel above its cloud point.
Innovation Solution
An active cloud point controller system that measures the cloud point of biofuels and adjusts the refining process by outputting control signals to manipulate variables such as isomerization reactor inlet temperature, using models and optimization techniques to maximize fuel yield while maintaining the cloud point at or below the desired setpoint.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the refining system operates without active cloud point control, then the operational simplicity is maintained, but the fuel yield is reduced and production efficiency is lost
Solution Approach 1:
The patent implements a feedback control system where cloud point measurements are continuously obtained and fed back to adjust refining parameters. The controller monitors the actual cloud point and dynamically adjusts process variables to maintain optimal fuel yield while ensuring the cloud point remains at or below the desired setpoint, thereby resolving the contradiction between increased productivity and system complexity.
Solution Approach 2:
The refining system performs self-adjustment through automated control based on cloud point measurements. The system uses optimization techniques to automatically determine and apply parameter adjustments without external intervention, maximizing fuel yield while maintaining cloud point specifications, thus improving productivity without requiring complex external control infrastructure.
2Reliability
If the cloud point is not actively controlled, then the operational simplicity is maintained, but the economic losses increase due to fuel below cloud point
Solution Approach 1:
The system employs continuous cloud point measurement and feedback control to ensure fuel quality reliability. By monitoring the actual cloud point and adjusting refining parameters in real-time, the system guarantees that the produced fuel meets the desired cloud point specifications, eliminating the risk of delivering substandard fuel while maintaining manageable system complexity through automated control.
Solution Approach 2:
The patent replaces manual quality checking and adjustment mechanisms with automated optical or analytical measurement systems coupled with computerized control. This substitution enhances measurement precision and control reliability while actually reducing operational complexity by eliminating manual intervention, thus improving fuel quality reliability without proportionally increasing device complexity.
3Productivity
If manual adjustment methods are used to maintain cloud point, then the system simplicity is maintained, but the yield reduction and inefficiencies occur
Solution Approach 1:
The refining system automatically performs optimization and adjustment based on cloud point measurements and production goals. The controller autonomously determines the optimal operating parameters and implements adjustments without requiring manual intervention, thereby maximizing production efficiency while keeping operational complexity low through self-service automation.
Solution Approach 2:
The system dynamically adjusts refining parameters such as temperature, pressure, and residence time based on real-time cloud point measurements and optimization algorithms. This automated parameter optimization maximizes fuel yield and production efficiency while eliminating the need for complex manual adjustment procedures, thus improving productivity without increasing operational complexity.
Data Source
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AI summary
A method includes receiving (302) a measurement associated with a cloud point of a biofuel being produced in a refining system (100). The method also includes determining (306) how to adjust the refining system based on a desired cloud point (136) of the biofuel and the measurement associated with the cloud point. The method further includes outputting (308) a control signal to adjust the refining system based on the determination. Determining how to adjust the refining system could include determining how to adjust an inlet temperature of a reactor in the refining system. The reactor could represent an isomerization reactor (116), and a heater (114) could heat material entering the isomerization reactor. Determining how to adjust the inlet temperature of the reactor could include determining how to adjust operation of the heater. A model predictive control (MPC) technique could be used to determine how to adjust the inlet temperature of the isomerization reactor.