4.7 Article

Roles of Dynamic State Estimation in Power System Modeling, Monitoring and Operation

Journal

IEEE TRANSACTIONS ON POWER SYSTEMS
Volume 36, Issue 3, Pages 2462-2472

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2020.3028047

Keywords

Electronic mail; Observability; Power system dynamics; State estimation; Kalman filters; Phasor measurement units; Energy management; Dynamic state estimation; kalman filtering; converter interfaced generation; low inertia; monitoring; parameter estimation; power system stability; static state estimation; synchronous machines; synchrophasor measurements

Funding

  1. US Department of Energy under Advanced Grid Modernization Program

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Power system dynamic state estimation (DSE) plays an important role in enhancing the operational robustness and resilience of power systems. The advantages of DSE compared to static state estimation are discussed with examples demonstrating its benefits in improving the reliability and resiliency of power systems through time critical applications.
Power system dynamic state estimation (DSE) remains an active research area. This is driven by the absence of accurate models, the increasing availability of fast-sampled, time-synchronized measurements, and the advances in the capability, scalability, and affordability of computing and communications. This paper discusses the advantages of DSE as compared to static state estimation, and the implementation differences between the two, including the measurement configuration, modeling framework and support software features. The important roles of DSE are discussed from modeling, monitoring and operation aspects for today's synchronous machine dominated systems and the future power electronics-interfaced generation systems. Several examples are presented to demonstrate the benefits of DSE on enhancing the operational robustness and resilience of 21st century power system through time critical applications. Future research directions are identified and discussed, paving the way for developing the next generation of energy management systems and novel system monitoring, control and protection tools to achieve better reliability and resiliency.

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