Detection of measurements errors with a distribution network state estimation function

Existing electricity distribution management systems (DMS) have been designed using operational and algorithmic procedures that are highly centralised. As more of the distribution network becomes active, accurately estimating the state of the system becomes essential and therefore DMS must include functions to achieve the required near to real-time state estimation. Distribution State Estimation using sensors data and load models as input data can help improve the network observability required by Advanced Distribution Automation function. One of the important objectives of state estimation algorithms is also to be able to detect erroneous measurement data. This information is firstly used in order to reject this data as inputs of the estimation process but also to help identify faulty sensors for scheduling their repair or their replacement. This paper presents different techniques which can be applied to distribution state estimation to detect and identify faulty sensors.