4 papers
Adaptive Regulated Sparsity Promoting Approach for Data-Driven Modeling and Control of Grid-Connected Solar Photovoltaic Generation
Zhongtian Zhang, Javad Khazaei, Rick S. Blum
This paper aims to introduce a new statistical learning technique based on sparsity promoting for data-driven modeling and control of solar photovoltaic (PV) systems. Compared with…
Data-Driven Dynamic State Estimation of Photovoltaic Systems via Sparse Regression Unscented Kalman Filter
Elham Jamalinia, Zhongtian Zhang, Javad Khazaei +1
Dynamic state estimation (DSE) is vital in modern power systems with numerous inverter-based distributed energy resources including solar and wind, ensuring real-time accuracy for…
Vulnerability of Building Energy Management against Targeted False Data Injection Attacks:Model Predictive Control vs. Proportional Integral
Xiaoyu Ge, Kamelia Norouzi, Faegheh Moazeni +4
Cybersecurity in building energy management is crucial for protecting infrastructure, ensuring data integrity, and preventing unauthorized access or manipulation. This paper invest…
Communication-Efficient {Federated} Learning Using Censored Heavy Ball Descent
Yicheng Chen, Rick S. Blum, Brian M. Sadler
Distributed machine learning enables scalability and computational offloading, but requires significant levels of communication. Consequently, communication efficiency in distribut…