Adaptive Power Grid Operation Loops for Autonomous Fault Response
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Solution Overview
Problem
Geographically distributed complex device networks, such as power grids, are susceptible to service interruptions due to external factors like weather and sabotage, and internal factors like device aging and malfunction, making it difficult to identify and rectify issues in a timely manner.
Innovation Solution
An adaptive power grid management system utilizing a network device database, a network adapter, and a processor configured to train a context model with machine learning, determine a formation plan, and execute scout applications on devices to adaptively manage the grid, forming self-acting operating cells that can operate autonomously and merge to achieve objectives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional centralized management is used for power grids, then system control is simplified, but response time to faults and service interruptions increases
Solution Approach 1:
The power grid is divided into multiple autonomous operating cells that can independently detect, decide, and act on local conditions. Each cell operates semi-autonomously, eliminating the need for centralized approval delays and enabling immediate local response to faults and changes.
Solution Approach 2:
The system dynamically forms and reconfigures operating cells based on real-time grid conditions, fault locations, and resource availability. This dynamic reconfiguration allows the system to adapt its structure to optimize response times for different scenarios rather than relying on a fixed hierarchical structure.
2Measurement precision
If more monitoring and control devices are added to improve detection capability, then measurement precision improves, but device complexity increases
Solution Approach 1:
Existing grid devices are equipped with multi-functional capabilities to perform monitoring, control, and communication functions. Rather than adding dedicated monitoring devices, the system enables existing equipment to serve multiple purposes, improving detection precision without proportionally increasing component count.
Solution Approach 2:
Operating cells utilize their own local resources and capabilities for self-diagnosis and self-monitoring. Each cell can detect its own status and faults without requiring external monitoring infrastructure, reducing the need for additional dedicated monitoring devices across the grid.
3Productivity
If manual intervention is increased for grid management, then control precision improves, but productivity decreases
Solution Approach 1:
Operating cells are designed to autonomously detect faults, make decisions, and execute corrective actions without human intervention. This self-service capability handles routine operations and fault responses automatically, significantly improving grid management productivity while maintaining appropriate manual override capabilities for exceptional situations.
Solution Approach 2:
The system implements continuous feedback loops where operating cells monitor their own performance and grid conditions, automatically adjusting operations based on real-time data. This closed-loop control maintains operational precision by using sensor feedback to verify actions and detect anomalies, reducing the need for manual verification while preserving ease of operation through automated decision-making.
Data Source
AI summary
A system for adaptive power grid management includes a formation construct module configured to receive a formation plan and a logistics list comprising a plurality of assets for executing an operation loop in the formation plan, retrieve a matching schema based on comparing the tasks of the operation loop and the logistics list with the plurality of meta objects in the historical meta object database, construct meta objects for plurality of assets based on the matching schema and the formation plan, and cause the plurality of the network of devices to execute the formation plan based on meta objects assigned to the plurality of assets of the network of devices.