1 code implementation • IEEE Sensors Journal 2022 • Rui Wu, Scott D. Hamshaw, Lei Yang, Dustin W. Kincaid, Randall Etheridge, Amir Ghasemkhani
Imputation of missing sensor-collected data is often an important step prior to machine learning and statistical data analysis.
no code implementations • 19 Oct 2021 • Yunchuan Liu, Lei Yang, Amir Ghasemkhani, Hanif Livani, Virgilio A. Centeno, Pin-Yu Chen, Junshan Zhang
Specifically, the data preprocessing step addresses the data quality issues of PMU measurements (e. g., bad data and missing data); in the fine-grained event data extraction step, a model-free event detection method is developed to accurately localize the events from the inaccurate event timestamps in the event logs; and the feature engineering step constructs the event features based on the patterns of different event types, in order to improve the performance and the interpretability of the event classifiers.
no code implementations • 25 Aug 2020 • Iman Niazazari, Hanif Livani, Amir Ghasemkhani, Yunchuan Liu, Lei Yang
This paper presents a machine learning method for event cause analysis to enhance situational awareness in distribution networks.
no code implementations • 24 Aug 2020 • Iman Niazazari, Amir Ghasemkhani, Yunchuan Liu, Shuchismita Biswas, Hanif Livani, Lei Yang, Virgilio Centeno
This paper presents a wide-area event classification in transmission power grids.
no code implementations • 2 May 2019 • Mohammad Jafari, Vahid Sarfi, Amir Ghasemkhani, Hanif Livani, Lei Yang, Hao Xu
In this paper, a biologically-inspired adaptive intelligent secondary controller is developed for microgrids to tackle system dynamics uncertainties, faults, and/or disturbances.