Measurement verification for power systems with battery energy storage integration

In the electric power system, the validity and completeness of data are traditionally provided by the state estimator, which processes raw measurements to filter the noise and gross errors. Gross errors can be detected and eliminated in the step of bad data detection provided there is enough redundancy in the measurements. With the introduction of renewable energy sources, many new components, including energy storage systems, are integrated into the system potentially resulting in a low measurement redundancy. In this context, conventional bad data detection methods may fail to detect gross errors especially when generation provided by stochastic and intermittent sources (wind and solar) is hard to predict. The situation becomes especially acute in cases of low information redundancy (e.g. distribution networks) when some of these recent components are not accompanied by measurement units. In this paper, a new bad data detection method is proposed, which is based on the battery control strategy analysis. The proposed method can be used to handle any energy storage system (ESS) control methodology.