Time-Based Sustainability Action Plan Simulation for Enterprise Operations
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Solution Overview
Problem
Challenges exist in tracking and improving sustainability parameters across hydrocarbon enterprise operations, including energy, carbon, and waste management, while achieving net zero carbon emissions and optimizing resource use.
Innovation Solution
An enterprise system with sensors and a sustainability platform system that measures operational parameters, generates sustainability models, and simulates action plans to adjust operations for improved sustainability, using data from various sources to continuously update and validate the effectiveness of these plans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive sustainability tracking is implemented across hydrocarbon enterprise operations, then sustainability parameter monitoring capability is improved, but system complexity and computational costs increase
Solution Approach 1:
The sustainability platform segments the hydrocarbon enterprise operations into distinct operational units (upstream, midstream, downstream) and tracks sustainability parameters for each segment separately. This allows comprehensive monitoring without requiring a monolithic complex system, as each segment can be managed and processed independently through modular computational approaches.
Solution Approach 2:
The sustainability platform acts as an intermediary system that sits between operational devices and decision-making processes. It collects data from various sensors and devices across the enterprise, processes this information through standardized protocols, and provides actionable insights without requiring direct integration with every operational component, thereby reducing overall system complexity.
2Reliability
If real-time sustainability simulation and validation is performed, then decision accuracy is improved, but computational processing time increases
Solution Approach 1:
The system performs preliminary simulations and validations of sustainability action plans before full implementation. By pre-evaluating potential actions through computational models and sensitivity analyses, the system identifies high-probability successful interventions in advance, reducing the need for extensive real-time computational validation during actual decision-making processes.
Solution Approach 2:
The sustainability platform implements partial simulation and validation for all action plans, focusing computational resources on critical sustainability parameters and high-impact interventions. Rather than performing exhaustive validation on every possible parameter, the system identifies and validates only the most significant factors, achieving sufficient decision accuracy with reduced computational time.
3Measurement precision
If multiple data sources are integrated for sustainability modeling, then model accuracy is improved, but data integration complexity increases
Solution Approach 1:
The sustainability platform employs universal data integration protocols and standardized interfaces that can accommodate multiple data sources (sensor data, operational data, external sustainability data) through a common framework. This multi-functional approach allows the system to integrate diverse data types without requiring separate integration mechanisms for each source, reducing overall integration complexity while maintaining model accuracy.
4Productivity
If continuous sustainability action plan updates are implemented, then sustainability goal achievement is improved, but operational disruption increases
Solution Approach 1:
The sustainability platform implements continuous feedback loops that monitor sustainability parameter performance and automatically trigger action plan updates only when performance deviations exceed predefined thresholds. This feedback-driven approach ensures continuous improvement toward sustainability goals while minimizing unnecessary operational disruptions by updating plans only when actually needed based on real performance data.
Data Source
AI summary
An enterprise system may include one or more devices with sensors that measure operational parameters of the devices. The enterprise system may also include a sustainability platform system that obtains a sustainability model representative of a state of operations of the enterprise based on the measured operational parameters and receives sustainability target data that includes one or more threshold limits, one or more ranges, or both for one or more sustainability parameters. The sustainability platform system may also obtain one or more action plans for adjusting respective operations of the devices based on the sustainability model and the sustainability target data, simulate a performance of the action plans over a period of time relative to the sustainability parameters, and determine whether the simulated performance of the action plans is effective.