Feedstock Blending Control for Corrosion-Limited Biofuel Processing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing petroleum processing plants face challenges in accommodating high concentrations of biogenic feedstocks, such as biocrude, due to corrosion and compatibility issues with existing infrastructure designed for petroleum processing, necessitating active monitoring and adjustment of process parameters to optimize product output and asset lifetime.
Innovation Solution
A controlled feedstock blending apparatus and method that utilizes sensors to monitor pipe corrosion and viscosity, a main controller to adjust blending parameters, and an AI system to optimize feedstock blending, ensuring compatibility and efficiency in processing diverse feedstocks including biogenic materials.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high concentrations of biogenic feedstocks are processed, then product output and biofuel content are improved, but corrosion and compatibility issues with existing infrastructure worsen
Solution Approach 1:
The system dynamically adjusts blending parameters (biofuel concentration ratios, flow rates, temperature) based on real-time sensor feedback about corrosion conditions. When corrosion sensors detect elevated levels, the controller automatically modifies the blend composition to reduce corrosivity while maintaining acceptable productivity levels.
Solution Approach 2:
Corrosion sensors continuously monitor the processing infrastructure and provide real-time feedback to the controller. This feedback loop enables the system to detect corrosion trends and adjust operational parameters proactively, preventing severe corrosion damage while optimizing biofuel blend production.
2Productivity
If high concentrations of biogenic feedstocks are processed, then product output and biofuel content are improved, but asset lifetime deteriorates
Solution Approach 1:
The controller dynamically modifies processing parameters including feedstock blend composition, flow rates, and temperature based on real-time asset condition monitoring. When sensors indicate deteriorating asset health, the system adjusts parameters to reduce stress on infrastructure, thereby extending asset lifetime while maintaining optimized productivity.
Solution Approach 2:
The system performs preliminary adjustments to blending parameters based on predicted corrosion risks and asset condition trends. By proactively modifying the blend composition before severe corrosion occurs, the system prevents asset degradation and extends infrastructure lifetime while maximizing biofuel production.
3Object-affected harmful factors
If sulfur content is reduced to meet maximum sulfur content requirements, then compatibility with processing infrastructure is improved, but product quality may be affected
Solution Approach 1:
The system dynamically adjusts multiple parameters simultaneously including sulfur content, blend composition, and processing temperature to achieve the optimal balance. By coordinating changes across multiple parameters, the system reduces sulfur content to meet compatibility requirements while compensating for any potential product quality impacts through adjusted blending ratios and processing conditions.
Data Source
AI summary
A method for controlling a feedstock blend is described, comprising the steps of: measuring a corrosion of a pipe in a fuel processing facility with a sensor; setting a maximum sulfur content in the feedstock blend based on the corrosion; measuring a build-up of material in the pipe with the sensor; establishing a maximum viscosity of the feedstock blend based on output of the sensor; blending, to form the feedstock blend, a first feedstock and a second feedstock to fulfill both the maximum sulfur content and the maximum viscosity; and passing the feedstock blend through the first pipe.