A Computationally Efficient State Estimation Algorithm for the Supervision of Low Voltage Grids

The presence of an accurate and efficient system state estimator is a precondition for supervision and closed-loop-control of low voltage grids. Such an estimator has to perform in consecutive periods of minutes. Between two periods in most cases, only the measurement values will change, but sometimes also the measurement model. This paper gives suggestions on how to improve the computationally efficiency of state estimation algorithms that have to perform in such an environment. The efficiency improvements are achieved by the application of advanced matrix inversion methods. Further the use of a linear measurement model and the application of the standard augmented matrix approach for solving the state estimation formula is suggested. However, these improvements can also be applied to other measurement models and estimation methods. The efficiency of the improvements is benchmarked against standard methods for different real grid operation cases. In particular, cases when new measurements are added or measurement values get lost are considered. The final result of the paper is an adjustable, robust and efficient algorithm for low voltage state estimation, presented in a way to support manufacturers and operators to implement and maintain it. The paper is a contribution in the field of static state estimation and short-term operation in distribution systems, in particular, low voltage grids.