Z
Zhenyu Huang
Researcher at Pacific Northwest National Laboratory
Publications - 219
Citations - 6729
Zhenyu Huang is an academic researcher from Pacific Northwest National Laboratory. The author has contributed to research in topics: Electric power system & Kalman filter. The author has an hindex of 40, co-authored 200 publications receiving 5368 citations. Previous affiliations of Zhenyu Huang include State University of Campinas & University of Alberta.
Papers
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Journal ArticleDOI
Power System Dynamic State Estimation: Motivations, Definitions, Methodologies, and Future Work
Junbo Zhao,Antonio Gomez-Exposito,Marcos Netto,Lamine Mili,Ali Abur,Vladimir Terzija,Innocent Kamwa,Bikash C. Pal,Abhinav Kumar Singh,Junjian Qi,Zhenyu Huang,A. P. Sakis Meliopoulos +11 more
TL;DR: A unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, trackingstate estimation, and static state estimation and provide future research needs and directions for the power engineering community.
Journal ArticleDOI
Comparative analysis between ROCOF and vector surge relays for distributed generation applications
TL;DR: In this paper, a comprehensive comparative analysis between rate-of-change-offrequency (ROCOF) and vector-surge (VS) relays for distributed generation islanding detection is presented.
Journal ArticleDOI
Incorporating Uncertainty of Wind Power Generation Forecast Into Power System Operation, Dispatch, and Unit Commitment Procedures
TL;DR: An approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed in this paper, which includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level.
Proceedings ArticleDOI
Adaptive adjustment of noise covariance in Kalman filter for dynamic state estimation
TL;DR: In this article, an adaptive filtering approach is proposed to estimate the covariance matrix of process noise (Q) and measurement noise (R) based on innovation and residual to improve the dynamic state estimation accuracy of the extended Kalman filter.
Journal ArticleDOI
Dynamic State Estimation of a Synchronous Machine Using PMU Data: A Comparative Study
TL;DR: This paper compares the performance of four Bayesian-based filtering approaches in estimating dynamic states of a synchronous machine using phasor measurement unit data and makes some recommendations for the proper use of the methods.