Zonal Autonomous Grid Control for Decentralized Node Management
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Solution Overview
Problem
The increased complexity of modern power grids due to variable energy sources and bulk power electronic control devices poses challenges in centralized control, particularly in managing and monitoring a large number of node points and circuit configurations.
Innovation Solution
The implementation of zonal autonomous control systems, which divide power grids into transmission and distribution zones, utilizing zonal controllers and intelligent electronic devices for decentralized management and automation, enabling efficient data processing and real-time control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized control is used to manage power grids, then control coordination is improved, but device complexity and difficulty of monitoring increase due to the large number of node points
Solution Approach 1:
The power grid is divided into multiple zones with hierarchical control levels (transmission level, distribution level, and sub-distribution level). Each zone has its own control functions, allowing localized decision-making while maintaining overall system coordination. This segmentation reduces the complexity burden on any single centralized controller and enables parallel processing of control tasks.
2Adaptability or versatility
If the number of controllable node points increases, then adaptability of the power grid improves, but the difficulty of detecting and measuring system state increases
Solution Approach 1:
Different zones and control levels are equipped with specific monitoring and measurement capabilities tailored to their local requirements. Intelligent electronic devices at each node perform local state estimation and monitoring, reducing the burden on centralized monitoring systems. Each zone can independently detect and measure its local state while contributing aggregated information to higher levels.
3Manufacturing precision
If real-time control of numerous node points is implemented, then control precision improves, but communication bandwidth requirements and computational load increase
Solution Approach 1:
Control functions and computational tasks are extracted from the centralized system and distributed to local zone controllers and intelligent electronic devices. Each node performs local state estimation and control calculations independently, extracting only essential aggregated data for transmission to higher levels. This reduces communication bandwidth requirements while maintaining control precision through distributed real-time processing.
Data Source
AI summary
A power grid system comprising an asset management controller associated with one or more of a plurality of zones in a power grid is provided herein. The asset management controller is configured to receive primary asset data for a primary asset associated with a zone of the plurality of zones. The asset management controller is further configured to receive secondary asset data for a secondary asset associated with the zone. The asset management controller is also configured to determine, via a machine learning model, a zonal analytics parameter. In addition, the asset management controller is configured to identify an asset management control action for a control device associated with the zone based on the zonal analytics parameter and communicate a command to a distribution zonal controller associated with the zone based on the asset management control action.