Plant Operation Optimization Component for Iterative Tariff Selection
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Solution Overview
Problem
Existing plant operation optimization components are limited in their ability to optimize energy tariffs, lacking the functionality to select or modify tariffs to minimize operational costs, which restricts their ability to adapt to changing energy prices and plant configurations.
Innovation Solution
A computer-implemented method that determines optimal operation setpoints and corresponding costs based on current and candidate tariffs, iteratively modifying tariff variables to meet target cost criteria, allowing for the selection of a new tariff that balances operational costs with existing conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dedicated optimization components are used to determine operation setpoints, then optimization performance is improved, but functionality is limited and cannot extend to tariff selection
Solution Approach 1:
The optimization component is extended to perform multiple functions: it now handles both operation setpoint determination and tariff selection/optimization. The component universally processes different types of inputs (operation parameters and tariff structures) and provides comprehensive optimization outputs, transforming a specialized tool into a multi-functional platform that addresses both operational and contractual optimization needs
2Reliability
If existing optimization components are used without modification, then core functionality is preserved, but tariff optimization capability is lost
Solution Approach 1:
The patent merges tariff optimization capabilities with the existing operation setpoint optimization component. By combining these previously separate functions into a unified system, the solution preserves the proven core optimization functionality while integrating new tariff selection capabilities, allowing both operation and contract optimization to work together synergistically
3Loss of energy
If tariff variables are iteratively modified to meet cost criteria, then operational costs are reduced, but computational complexity increases
Solution Approach 1:
The system dynamically adjusts tariff variables through iterative modification, adapting the optimization approach based on feedback from cost criterion evaluations. This dynamic process allows the system to navigate complex tariff structures and find optimal configurations that reduce operational costs, with the computational complexity managed through structured iteration and feedback mechanisms
Data Source
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AI summary
The invention provides computer-implemented method for a plant operation optimization component, the method determining optimal operation set points and, based on optimal operation setpoints and corresponding operational costs, providing output allowing for selecting a tariff.