Cooperative State Estimation for Interconnected Electrical Grids
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Solution Overview
Problem
Traditional state estimation in electrical grids becomes increasingly complex and error-prone as grids interconnect, with challenges in maintaining synchronized models and accurate measurements across multiple operators, leading to higher operational costs and insecure operating conditions.
Innovation Solution
A system and method for cooperative electrical grids that share up-to-date state estimator solution information between grids, incorporating both local and remote state estimator results and grid models to maintain accurate and synchronized state estimation, reducing reliance on stale shared models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If each grid operator performs state estimation independently using their own models and measurements, then each operator can maintain control over their portion of the grid, but model synchronization becomes difficult and estimation accuracy deteriorates at interconnection points
Solution Approach 1:
The system divides the interconnected grid into multiple independent estimation zones, each operated by different grid operators. Each operator maintains their own state estimator for their portion of the grid, allowing operational autonomy while the system coordinates these segmented estimators to improve overall accuracy at interconnection points.
Solution Approach 2:
A coordination mechanism acts as an intermediary between independent state estimators, facilitating information exchange and model synchronization. This intermediary enables operators to maintain autonomy while achieving synchronized estimates through shared measurement data and coordinated algorithms.
2Measurement precision
If grid operators share detailed models and measurements for comprehensive state estimation, then estimation accuracy improves, but system complexity and synchronization requirements increase significantly
Solution Approach 1:
The system extracts only the essential synchronization elements (boundary conditions, interconnection measurements, and coordination algorithms) from the complete state estimation problem. Operators share minimal necessary data at interconnection points rather than exchanging entire models, reducing complexity while maintaining accuracy where it matters most.
Solution Approach 2:
Each grid operator maintains high-quality, detailed models for their own portion of the grid while using coordinated estimates from neighboring operators for adjacent portions. This local quality approach ensures accuracy is optimized where each operator has direct control while reducing the burden of maintaining comprehensive models everywhere.
3Measurement precision
If operators maintain high-quality models for their own grid portions, then local estimation accuracy improves, but models for other portions become stale and less reliable
Solution Approach 1:
The system implements feedback mechanisms where state estimation results from one operator's estimator are fed back as inputs to neighboring operators' estimators. This feedback loop ensures that each operator benefits from the most recent state information available from connected grids, preventing model staleness while maintaining local estimation quality.
Data Source
AI summary
Aspects of state estimation for cooperative electrical grids are disclosed. State estimation of a local electrical grid can be based on a local grid model and local electrical grid information. The local state estimation can reflect interactions and interconnections with other electrical grids by determining state estimation solution information based on the local grid model, local electrical grid information, and remote state estimator solution information associated with the other electrical grid. As such, a local state estimator can be configured to receive and employ remote state estimator solution information. This can be in addition to the more conventional technique or receiving a remote grid model and remote electrical grid information to estimate the conditions of the remote electrical grid. Further, state estimation solution information can be incremental to further reduce the amount of information to be transferred and the time needed to accomplish transmission of the information.