A Novel Methodology for Distributed and Online Constrained Nonlinear Estimation with Applications
Grant Data
Project Title
A Novel Methodology for Distributed and Online Constrained Nonlinear Estimation with Applications
Principal Investigator
Professor Chan, Shing Chow
(Principal Investigator (PI))
Co-Investigator(s)
Professor Hou Yunhe
(Co-Investigator)
Duration
42
Start Date
2021-01-01
Amount
704212
Conference Title
A Novel Methodology for Distributed and Online Constrained Nonlinear Estimation with Applications
Keywords
Constrained estimation, distributed online algorithms, large-scale systems, optimal power flow, power system state estimation
Discipline
Signal and Image Processing
Panel
Engineering (E)
HKU Project Code
17211320
Grant Type
General Research Fund (GRF)
Funding Year
2020
Status
On-going
Objectives
1) Develop a novel methodology for robust distributed nonlinear estimation which can support both equality and inequality constraints via the augmented Lagrangian method; 2) Develop a framework for solving the local subproblems involved for streaming data. In particular, we shall develop two approaches, one based on Kalman filtering and the other based on stochastic optimization. 3) Investigate its application to power system state estimation, distributed optimal power flow, distributed optimal power flow, and other related problems such as fault/anomaly detection under various physical constraints.