Monitoring of distribution systems plays an important role in the enhancement of today's distribution systems for future requirements. Tasks of distribution system operation are becoming more active and the demand for network observability increases. In this paper two innovative methods for quasi-dynamic distribution system state estimation, the Extended Kalman Filter and the Particle Filter approach, are evaluated regarding their usability for distribution system operation. Both have been applied to the medium voltage CIGRE benchmark network and are investigated for different situations of measurement configurations and pseudo-measurement modelling.

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This paper presents the final result of a joint EU and Russian project called ICOEUR (Intelligent Coordination of Operation and Emergency Control of EU and Russian Power Grids). The presented results are about the extension and interconnection of large scale power systems from the perspective of monitoring and control. In this paper the authors identify algorithms and monitoring technologies for the identification of full system states and dynamic behavior of system. The algorithms are validated with realistic models from the European and Russian power system. The results lead to a coordination platform which applies Distributed and Dynamic State Estimation in order to manage cross border flows.

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