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Nanpeng Yu

Assistant Professor

University of California, Riverside

United States

Research Interests

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About

Dr. Nanpeng Yu is an Assistant Professor at the University of California Riverside, USA. His research focuses on transportation electrification, power systems, and smart grid technologies, as evidenced by his recent articles on dynamic wireless charging for heavy-duty trucks, efficient scheduling of truck routing and charging, and advancements in power system monitoring and control. Dr. Yu's work aims to enhance the integration of renewable energy sources and optimize energy management in transportation systems.

Articles (33)

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Collaborators (7)

Lin Zhu

Senior Technical Leader

Electric Power Research Institute

UNITED STATES

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Md Zahidul Islam

Assistant Professor

Southern Illinois University Carbondale

UNITED STATES

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Mikhail A. Bragin

University of California, Riverside

UNITED STATES

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Oliver Gao

Cornell University

UNITED STATES

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Youmin Zhang

Professor

Concordia University

CANADA

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Junbo Zhao

Todd M. Cook and Elizabeth Donohoe Cook Associate Professor

Dartmouth College

UNITED STATES

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Ning Lu

Professor

North Carolina State University

UNITED STATES

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Nanpeng Yu

Research Interests

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About

Articles (33)

Unified Fourier Graph-Based Spatiotemporal Learning and Corrected NWP for Multi-Site Ultra-Short Term Photovoltaic Power Forecasting

Generating Synthetic Net Load Data for Residential Customers With Physics-Informed Diffusion Models

AccSPS Learning Rate: Accelerated Convergence Through Decision-Adjusted Levels for Stochastic Polyak Stepsize

TERRAN: A Transformer-Based Electric Vehicle Routing Agent for Real-Time Adaptive Navigation

Data-driven control, optimization, and decision-making in active power distribution networks

A Cyber–Physical Security Assessment Model for Distribution Grid With High Penetration of Electric Vehicle Charging Infrastructure

Stochastic long-term joint decarbonization planning for power systems and data centers: A case study in PJM

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

PV power forecasting method using a dynamic spatio-temporal attention graph convolutional network with error correction

Solve Large-Scale Unit Commitment Problems by Physics-Informed Graph Learning

Carbon-Aware Charging Strategies for Electric Vehicle Battery Swapping Stations

Enhancing Black-Box Adversarial Attacks on Power System Event Classifiers via Transferability

Carbon-Aware Optimal Power Flow with Data-Driven Carbon Emission Tracing

Physics-Informed Graph Neural Networks for Collaborative Dynamic Reconfiguration and Voltage Regulation in Unbalanced Distribution Systems

Impact of flexible and bidirectional charging in medium- and heavy-duty trucks on California’s decarbonization pathway

Optimizing deep decarbonization pathways in California with power system planning using surrogate level-based Lagrangian relaxation

Graph Learning-Based Power System Health Assessment Model

Physical Intrusion Attack Detection in Fieldbus Network With Passive Fail-Safe Biasing

Toward efficient transportation electrification of heavy-duty trucks: Joint scheduling of truck routing and charging

pmuBAGE: The Benchmarking Assortment of Generated PMU Data for Power System Events

Joint planning of dynamic wireless charging lanes and power delivery infrastructure for heavy-duty drayage trucks

Joint planning of charging stations and power systems for heavy-duty drayage trucks

Deep reinforcement learning-based two-timescale Volt-VAR control with degradation-aware smart inverters in power distribution systems

Missing Value Replacement for PMU Data via Deep Learning Model With Magnitude Trend Decoupling

Robust learning-based real-time load estimation using sparsely deployed smart meters with high reporting rates

Behind-the-Meter Resources: Data-driven modeling, monitoring, and control

Bidding strategy for wireless charging roads with energy storage in real-time electricity markets

Decarbonizing regional multi-model transportation system with shared electric charging hubs

PowerMorph: QoS-Aware Server Power Reshaping for Data Center Regulation Service

Online Voltage Event Detection Using Synchrophasor Data With Structured Sparsity-Inducing Norms

Learning to Operate an Electric Vehicle Charging Station Considering Vehicle-Grid Integration

Efficient Operations of Micro-Grids with Meshed Topology and Under Uncertainty through Exact Satisfaction of AC-PF, Droop Control and Tap-Changer Constraints

Model-augmented safe reinforcement learning for Volt-VAR control in power distribution networks

Collaborators (7)

Lin Zhu

Md Zahidul Islam

Mikhail A. Bragin

Oliver Gao

Youmin Zhang

Junbo Zhao

Ning Lu

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