Advancing Dynamic State Estimation for the Next-Generation EMS: Structure, Algorithms and Experiences
* 21PESGM0070, EMS2.0”A Multi-Scale State Estimator: S. WANG, Pacific Northwest National Lab * 21PESGM0071, From Dynamic State Tracking Data to AI-inspired Dispatcher Aids in Post-Disturbance Conditions: I. KAMWA, Hydro Quebec * 21PESGM0072, Challenges and Solutions of State Estimation for Future EMS Applications: GE Experiences: G. ZHENG, GE * 21PESGM0073, Dynamic State Estimation for Integrated Energy Systems: H. SUN, Tsinghua University * 21PESGM0074, On Advanced State Estimators for System Integrity Protection Schemes: V. TERZIJA, Skolkovo Institute of Science and Technology (Skoltech)
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Members: $5.00PES
IEEE Members: $10.00
Non-members: $20.00
28 Jul 2021
Due to the increasing penetration of variable generation, demand response, new power market structures and unexpected events, the behavior of modern power systems is becoming more stochastic and dynamic. It is critically important to understand the current dynamic states and predict their near-future trajectories to enhance system resilience and reliability so that power system operators can take both preventive and corrective actions to mitigate the impact. The existing Energy Management System (EMS) relies heavily on static state estimation (SSE) to gain situational awareness of the power system, which may not be adequate for a more dynamic and complicated power system. This panel will bring practitioners, vendors, and researchers together to discuss the advancements of dynamic state estimation for the next-generation EMS, including its structure, algorithms, and prior experiences.
Chairs:
Zhenyu (Henry) Huang, Pacific Northwest National Laboratory, Junbo Zhao, Mississippi State University
Sponsor Committees:
(PSOPE) Bulk Power System Operations Subcommittee