Distributed Intelligence Architecture for Smart Grid Control
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Solution Overview
Problem
Centralized utility control systems are inefficient and inflexible, as they rely on low complexity communications and are unable to handle the complexity and dynamic nature of smart grids, leading to challenges in data management, control, and scalability, especially at large scales.
Innovation Solution
A distributed intelligence architecture is implemented, where grid application functions can be dynamically distributed throughout the utility grid, using a combination of 'reverse clouding' and 'forward clouding' to allocate computing resources and applications based on need, allowing for adaptive and efficient grid control operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If centralized control systems are used for utility grids, then system management and control can be simplified, but the system becomes inefficient and inflexible in handling complex and dynamic smart grid operations
Solution Approach 1:
The patent divides the centralized control system into multiple distributed control nodes deployed throughout the utility grid. Each node independently performs control functions for its local region, enabling the system to handle complex and dynamic operations while maintaining manageable complexity through modular architecture
Solution Approach 2:
The patent introduces a new dimensional approach by implementing control functions across multiple spatial dimensions (distributed locations) rather than relying on a single centralized point. This multi-dimensional control architecture enables simultaneous local responsiveness and global coordination
2Device complexity
If centralized control systems are used, then infrastructure requirements can be reduced, but data processing latency increases and scalability is limited
Solution Approach 1:
The patent segments data processing functions across multiple distributed nodes, allowing local data to be processed immediately at the nearest control node rather than being transmitted to a distant centralized system. This reduces data processing latency while maintaining infrastructure efficiency through shared resources
Solution Approach 2:
The patent introduces intermediate control nodes that act as mediators between field devices and the centralized system. These intermediaries perform preliminary data processing and filtering, reducing the time required for data to traverse the entire system while maintaining centralized oversight
3Device complexity
If grid control functions are statically allocated, then system simplicity is maintained, but flexibility and adaptability to changing grid conditions are reduced
Solution Approach 1:
The patent implements dynamic allocation of control functions where the system can automatically adjust which control functions are distributed to which nodes based on real-time grid conditions, node availability, and operational requirements. This maintains relative system simplicity while achieving high flexibility through automated dynamic reconfiguration
Data Source
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AI summary
In one embodiment, a grid application function is hosted at a primary grid device in a utility grid, which may determine whether or not to distribute at least a portion of the grid application function to one or more distributed secondary grid devices in the utility grid. In general, the one or more distributed secondary grid devices will be associated with a subset of the utility grid that is associated with the primary grid device (e.g., a sub-grid). Once a determination has been made, the primary grid device may dynamically distribute the grid application function, or a portion thereof, to the distributed secondary devices according to the determination. In addition, in another embodiment, the grid application function may also be withdrawn, such as from a particular secondary grid device or else from the primary grid device to an originating grid device.