Dual Carbon Control System for Life Cycle Optimization
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Solution Overview
Problem
Existing approaches to carbon reduction in the dual carbon context fail to consider the entire life cycle comprehensively, leading to inefficiencies and high costs due to inadequate management and lack of effective measures for technological development and cost fluctuations.
Innovation Solution
A control method and apparatus that optimize carbon reduction measures across multiple dimensions in time using optimization algorithms, such as deep learning or ant colony optimization, to align with carbon reduction requirement curves, incorporating factors like technological maturity, economic efficiency, and resource endowment, allowing for real-time monitoring and modification to achieve collaborative optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing carbon reduction approaches are used, then implementation is simple, but carbon reduction efficiency is low and costs are high
Solution Approach 1:
The patent segments the carbon reduction process into multiple dimensions including time dimensions (different stages of carbon reduction), spatial dimensions (different departments and business units), and measure dimensions (different types of carbon reduction measures). This segmentation enables comprehensive optimization across all dimensions while maintaining manageable complexity through modular analysis and optimization.
Solution Approach 2:
The patent implements dynamic optimization by continuously monitoring carbon reduction progress, technological developments, and cost fluctuations. The system dynamically adjusts carbon reduction measures and resource allocation based on real-time data, enabling the system to adapt to changing conditions and achieve optimal carbon reduction efficiency throughout the entire life cycle.
2Measurement precision
If comprehensive life cycle management is implemented, then carbon reduction precision is improved, but management complexity increases
Solution Approach 1:
The patent creates a universal digital intelligence system that performs multiple functions including carbon reduction planning, execution monitoring, performance evaluation, and dynamic optimization. This multi-functional platform manages the entire life cycle of carbon reduction measures through a single integrated system, improving precision while avoiding the complexity of multiple separate management systems.
Solution Approach 2:
The patent implements comprehensive feedback mechanisms that continuously monitor carbon reduction progress across all dimensions and provide real-time information to the optimization system. This feedback loop enables precise measurement of carbon reduction effectiveness and allows for continuous refinement of measures, achieving high precision through systematic feedback rather than complex manual management.
3Reliability
If traditional carbon reduction measures are used, then implementation cost is low initially, but operational risks increase due to lack of measures for technological development and cost fluctuation
Solution Approach 1:
The patent applies preliminary action by proactively identifying and preparing carbon reduction measures for future technological developments and cost fluctuations. The system forecasts potential changes in technology and costs, and pre-plans appropriate responses, thereby reducing operational risks before they materialize while maintaining reasonable system complexity through structured forecasting frameworks.
4Productivity
If carbon reduction measures are optimized across entire life cycle, then costs are reduced and efficiency is improved, but requires complex multi-dimensional optimization
Solution Approach 1:
The patent introduces multiple dimensions for carbon reduction optimization including time dimensions (different stages), organizational dimensions (different departments), and measure dimensions (different types of measures). By organizing the optimization problem across these dimensions, the system achieves comprehensive optimization while managing complexity through dimensional structuring rather than unstructured complex algorithms.
Data Source
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AI summary
A control method and apparatus for dual carbon, an electronic device, a storage medium, and a program product are provided. An entire life cycle of the dual carbon is divided into at least two dimensions in time based on a duration of the dual carbon. The control method includes: acquiring, for each of the dimensions, a carbon reduction measure, where the carbon reduction measure includes at least one item of carbon reduction measure information; acquiring a carbon reduction requirement curve, where the carbon reduction requirement curve is a carbon reduction result curve including all the dimensions, and a horizontal axis of the curve represents time; and optimizing the carbon reduction measure aiming at the carbon reduction requirement curve, using an optimization algorithm and based on the carbon reduction measure information, to obtain a modification result. Therefore, costs in carbon reduction are reduced and efficiency for carbon reduction is improved, achieving multi-dimensional optimization throughout the entire life cycle for the dual carbon.