Deep neural networks have revolutionized many machine learning tasks in power systems,
ranging from pattern recognition to signal processing. The data in these tasks are typically …

The Industrial Internet of Things (IIoT) plays an important role in digital transformation of
traditional industries toward Industry 4.0. By connecting sensors, instruments, and other …

This paper proposes a robust diagnosis method of photovoltaic (PV) array faults considering
label errors in training data. First, the online data of PV systems, including the sequences of …

Solar array management and photovoltaic (PV) fault detection is critical for optimal and
robust performance of solar plants. PV faults cause substantial power reduction along with …

This paper presents a novel fault detection and identification method for low-voltage direct
current (DC) microgrid with meshed configuration. The proposed method is based on graph …

Significant increases in cyberattacks worldwide have threatened the security of
organizations, businesses, and individuals. Cyberattacks exploit vulnerabilities in software …

A Physics-Informed Dynamic Graph Neural Network (PIDGeuN) is presented to accurately,
efficiently and robustly predict the nonlinear transient dynamics of microgrids in the …

Smart energy meters allow individual residential, commercial, and industrial energy load
usage to be monitored continuously with high granularity. Accurate short-term energy …

This paper accompanies the keynote speech at IISA2020 and describes federally funded
workforce development research grants and supplements in the area of sensors and …

The international research experiences for students (IRES) program addresses
multidisciplinary research at the overlap of sustainability, power systems, and signal …