Estimate the Electromechanical States Using Particle Filtering and Smoothing

Conference · Sun Jul 22 00:00:00 EDT 2012

DOI:https://doi.org/10.1109/PESGM.2012.6345440· OSTI ID:1089098

Meng, Da; Zhou, Ning; Lu, Shuai; Lin, Guang

Accurate knowledge of electromechanical states is critical for efficient and reliable control of a power system. This paper proposes a particle filtering approach to estimate the electromechanical states of power systems from Phasor Measurement Unit (PMU) data. Without having to go through laborious linearization procedure, the proposed particle filtering techniques can estimate states of a complex power system, which is often non-linear and has non-Gaussian noise. The proposed method is evaluated using a multi-machine system with both large and small disturbances. Sensitivity studies of the dynamic state estimation performance are also presented to show the robustness of the proposed method. The inherent decoupling properties of particle filtering make it highly scalable and the potential to reduce computational time through parallel implementation is very promising.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1089098
• Report Number(s): PNNL-SA-84381; KJ0401000
• Resource Relation: Conference: IEEE Power and Energy Society General Meeting, July 22-26, 2012, San Diego, California
• Country of Publication: United States
• Language: English

Related Subjects

Auxiliary Particle Filter
Importance Sampling
Non-Gaussian State Space Model
Particle Filtering
Particle Smoothing
Sequential Monte Carlo Methods
State Estimation