QGS State Estimation

Nonlinear PMU-only and Hybrid (SCADA/PMU) State Estimation

State Estimation provides the foundation for control center operations such as monitoring, analysis, optimization, and control functions. The conventional method, Weighted-Least Squares (WLS), has been used for over half a century with little change. However, with state estimation now needed in distribution networks or using PMU data where measurement availability is limited, there is a need for alternative state estimation methods.

BSI QGS State Estimation provides reliability through backup or the enhancement of control center state estimation. QGS stands for Quasi-Gradient Systems, which takes a dynamic approach to solving the non-linear state estimation problem, accommodating scenarios where measurement redundancy is limited. This application can operate as stand-alone or when integrated with the Energy Management System (EMS) or Advanced Distribution Management Systems (ADMS).

Use Case

The QGS State Estimation can enhance conventional state estimators or serve as a backup to state estimators when they diverge.

QGS State Estimation can be used for:

  • PMU-only non-linear State Estimation
  • Hybrid State Estimation (combine PMU, SCADA, and other inputs)
  • Enhancing SCADA State Estimation

Key Functions

  • Great convergence property for power systems with limited measurements
  • Robustness against a set of measurements with a large quantity of current magnitudes for medium and low-voltage distribution systems
  • Flexible formulation with residual constraints for every measurement
  • Easily incorporate PMU measurements, which may not provide full system observability between two refreshed SCADA data.
  • Easy integration of existing SE solvers and greatly improved SE results