Hierarchical Grid Edge Control for Coordinated Power Flow
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Solution Overview
Problem
Grid edge devices lack integration with higher-level grid operations, leading to inefficient and localized responses to disturbances and events, which can affect broader portions of the electric grid, necessitating intelligent and holistic control strategies.
Innovation Solution
An electric grid operation system with a central controller layer that monitors and controls grid conditions, and an intermediate controller layer with hubs that adjust local operations of grid edge devices based on sensor data and expected grid-wide operations, enabling coordinated autonomous operation and improved data analytics for predictive management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If grid edge devices perform localized actions in response to grid events, then response speed is improved, but grid-wide coordination and efficiency deteriorate
Solution Approach 1:
The control system is segmented into multiple hierarchical levels: local control at grid edge devices, regional control at distribution automation systems, and central control at the utility level. Each level operates autonomously within its scope while receiving coordination from higher levels, enabling both fast local response and efficient grid-wide coordination.
Solution Approach 2:
Distribution automation systems act as intermediary layers between central utility control and grid edge devices. These intermediaries translate central control strategies into localized actions and aggregate local sensor data into meaningful regional information, enabling coordinated operation without requiring direct central control of every device.
2Device complexity
If grid edge devices operate autonomously without higher-level integration, then device simplicity is improved, but overall grid resilience deteriorates
Solution Approach 1:
The system divides control functions across multiple autonomous agents at different hierarchical levels. Grid edge devices maintain simple local control logic, while distribution automation systems and central utility systems provide layered coordination, achieving grid resilience without requiring complex intelligence in individual devices.
Solution Approach 2:
Each control layer operates autonomously using locally available information and sensor data. Grid edge devices self-adjust based on local conditions, distribution automation systems self-coordinate regional operations, and the central system self-optimizes overall grid performance, with each layer serving itself rather than requiring constant external control.
3Measurement precision
If comprehensive sensor data is collected from all grid edge devices, then data accuracy is improved, but computational complexity deteriorates
Solution Approach 1:
Data collection and processing are segmented across hierarchical levels. Local devices collect and pre-process sensor data, distribution automation systems aggregate and analyze regional data patterns, and the central system performs high-level optimization. This segmentation maintains data accuracy while distributing computational complexity across multiple systems with appropriate processing capabilities.
Solution Approach 2:
The system extracts and processes only the most relevant features and patterns from comprehensive sensor data at each hierarchical level, rather than transmitting and processing all raw data centrally. Distribution automation systems extract regional patterns and anomalies, sending only essential information to the central system, thereby maintaining analytical accuracy while reducing computational burden.
Data Source
AI summary
This disclosure describes a system and method for a central controller layer to monitor conditions and control operations of an electric grid. The central controller layer communicates with an intermediate controller layer that includes hubs to monitor operations of grid edge devices connected to different regions of the electric grid. The central controller layer obtains, from each hub, sensor data corresponding to measurements performed by the grid edge devices. The central controller layer determines, based on the sensor data and expected grid-wide operations, control strategies with expected electrical operating conditions for the respective region, and provides a respective control strategy to each hub. In response to receiving the respective control strategy for the hub, each hub generates operational parameters for at least one grid edge device that cause a grid edge device to adjust its operation based on the expected amount of power flow for the hub.