Distributed Quasi-Dynamic State Estimation Incorporating Distributed Energy Resources

Deployment of distributed energy resources (DERs) introduces more dynamics to the distribution system, and brings system operators more challenges in monitoring and controlling the distribution system. These challenges can be addressed by developing methods for real time extraction of the operating state and model of the system, that is advanced state estimators for distribution systems with high penetration of DERs. This paper presents an object-oriented Distributed Quasi-Dynamic State Estimator (DQDSE) that employs three-phase detailed models and enables data from sensors to be streamed and used by the DQDSE. Based on three-phase detailed quasi-dynamic models that track slow dynamics (e.g., controls of power electronics, electromechanical transients of motors, etc.), DQDSE forms network measurement model by using network-wise measurements, performs quasi-dynamic state estimation, and provides the best estimate of the distribution system states. The proposed DQDSE has the following advantages: (1) detailed modeling approach ensures accurate results even when accommodating unbalanced and asymmetric systems; (2) the measurement set of DQDSE contains measurements from sensors as well as other measurement types to increase redundancy; (3) the distributed architecture of DQDSE enables fast data processing. The paper presents the method via an illustrative example that substantiates the effectiveness of DQDSE.