Real-Time State Estimation for Large-Scale Power Systems

An efficient and simple hierarchical state estimation method, suitable for real-time monitoring of large-scale power systems is investigated in detail. This method exhibits inherent parallelism; it treats all sub-systems of the large system and all tielines coupling these sub-systems separately and independently. Thus, it is very flexible, allowing fast state estimation and bad data processing, the latter being achieved by a specially designed algorithm. Suitability of the method and the algorithm are examined using two 220 kV networks. Several comparisons with the classical, centralised state estimation method are used to illustrate practicality of the hierarchical method.