Assessment of State Estimation Methods for Power Systems with Uncertain Parameters

In the power system state estimation, it is usually supposed that process and measurement models and grid parameters are completely and accurately known. Unfortunately, in real scenarios, this does not hold true. For instance, grid parameters may be uncertain for various reasons (lack of documentation, parameter variation due to weather conditions, heating, etc.). In these cases, state estimation techniques that take into account the parameters uncertainty can be used. A potential solution is to identify the parameters in a first step, and then estimate the state in a second step. In view of the deployment into real power systems, these methods have to be capable of being executed in real-time. The purpose of this paper is to assess the performance of such approaches with respect to estimation accuracy.