Processing Plant Asset Optimization for Carbon Emissions and Impact
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Solution Overview
Problem
Current methods for reducing carbon emissions in processing plants, such as chemical processing and oil refineries, are inefficient and costly, as they struggle to determine optimal transformation actions across multiple assets to achieve carbon emission goals while minimizing impact values.
Innovation Solution
A computer-implemented method using a multi-optimization model to identify carbon output and impact values for each asset, generating an optimized set of transformation actions that include scheduling asset modifications, energy source conversions, and carbon credit offsets, which are executed in real-time or near real-time to minimize cumulative carbon output and impact values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-generated harmful factors
If current methods are used to reduce carbon emissions in processing plants, then carbon emissions can be reduced, but the costs and operational complexity increase significantly
Solution Approach 1:
The system segments the processing plant into multiple discrete assets (e.g., furnaces, boilers, turbines) and evaluates each asset's carbon output and impact values independently. This segmentation allows for targeted transformation actions on specific assets rather than plant-wide changes, reducing operational complexity while effectively reducing overall carbon emissions.
Solution Approach 2:
The system changes parameters by calculating and comparing carbon output values and impact values for different transformation actions. By optimizing based on these parameter changes, the system identifies the most efficient actions that reduce carbon emissions without proportionally increasing costs or operational complexity.
2Object-generated harmful factors
If multiple transformation actions are implemented across multiple assets, then carbon emission goals can be achieved, but determining the optimal actions becomes computationally complex
Solution Approach 1:
The system performs preliminary calculations of carbon output values and impact values for each asset before implementing transformation actions. This preliminary assessment allows for pre-planning and optimization of the transformation sequence, reducing the computational complexity of determining optimal actions while ensuring carbon emission goals are met.
3Object-generated harmful factors
If asset modifications and energy source conversions are implemented, then carbon output is reduced, but operational disruption and costs increase
Solution Approach 1:
The system dynamically schedules transformation actions based on plant operational conditions, asset criticality, and carbon reduction priorities. By making the transformation schedule dynamic rather than static, the system can optimize for minimal operational disruption while still achieving carbon output reduction goals through strategically timed modifications and conversions.
Data Source
AI summary
A computer-implemented method for optimizing carbon emissions associated with an operation of a processing plant is provided. The processing plant includes a plurality of assets and the computer-implemented method includes identifying a carbon output value associated with operating each asset of the plurality of assets of the processing plant and identifying an impact value associated with each asset of the plurality of assets. The method also includes generating an optimized set of transformation actions corresponding to the plurality of assets utilizing a multi-optimization model. The multi-optimization model is based at least in part on the carbon output value and the impact value.