most citedAdversarial Purification for Data-Driven Power System Event Classifiers with Diffusion Models

1 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG20241 cited

Generating Synthetic Net Load Data with Physics-informed Diffusion Model

Shaorong Zhang, Yuanbin Cheng, Nanpeng Yu

This paper presents a novel physics-informed diffusion model for generating synthetic net load data, addressing the challenges of data scarcity and privacy concerns. The proposed f…

math.OC2024

Joint Planning of Charging Stations and Power Systems for Heavy-Duty Drayage Trucks

Zuzhao Ye, Nanpeng Yu, Ran Wei

As global concerns about climate change intensify, the transition towards zero-emission freight is becoming increasingly vital. Drayage is an important segment of the freight syste…

eess.SY2024

Impact of Flexible and Bidirectional Charging in Medium- and Heavy-Duty Trucks on California's Decarbonization Pathway

Osten Anderson, Wanshi Hong, Bin Wang +1

California has committed to ambitious decarbonization targets across multiple sectors, including decarbonizing the electrical grid by 2045. In addition, the medium- and heavy-duty…

eess.SY20241 cited

On the Selection of Intermediate Length Representative Periods for Capacity Expansion

Osten Anderson, Nanpeng Yu, Konstantinos Oikonomou +1

As the decarbonization of power systems accelerates, there has been increasing interest in capacity expansion models for their role in guiding this transition. Representative perio…

eess.SY20231 cited

Adversarial Purification for Data-Driven Power System Event Classifiers with Diffusion Models

Yuanbin Cheng, Koji Yamashita, Jim Follum +1

The global deployment of the phasor measurement units (PMUs) enables real-time monitoring of the power system, which has stimulated considerable research into machine learning-base…