Northeastern University Background
When solving the power system state estimation problem for very large interconnected systems, certain zones can experience convergence issues for various reasons such as bad data, loss of measurements, topology errors, etc. In such cases, a solution may not be reached by the integrated system state estimator. The purpose of this technology is to develop an alternative approach that will automatically detect issues associated with the affected subsystem and isolate its solution from the rest of the system solution. This way, it will be possible to provide a state estimation solution for the largest possible part of the system even when there are one or more unobservable or unsolvable zones.
The developed algorithm is based on the multi-area two-level state estimator (2LvSE), which involves a two-stage solution where the first stage obtains individual area solutions, followed by a coordination stage where these solutions are combined and synchronized by a central processor.
The purpose of the second stage is to synchronize individual area reference angles to detect and remove any errors that were missed by individual area solvers.
The efficient implementation of this approach involves some challenges related to strategic partitioning while maintaining area observability. These challenges are addressed by an approach that partitions the system into areas and avoids area-boundary observability issues and accomplishes this by a computationally efficient implementation of the method even for very large scale power grids.
Will provide a solution for a large portion of the system even when the conventional estimators fully diverge
Allows detection and identification of permanent errors and isolation of the impacted zone. Permanent topology errors can thus be detected and corrected
It lends itself to parallel processing, making it a scalable approach for very large scale problems
It can be used as a back-up network application in control centers
It can be used by utilities to avoid loss of observability for the entire system for lengthy periods when there are errors in one or more of its many zones
It can be used as a tool to detect, identify and correct topology errors which cause state estimators to diverge