Long Zhao

Assistant Professor

South Dakota Mines

United States

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About

Long Zhao is an Assistant Professor at South Dakota Mines in the United States. His research focuses on electrical systems and sustainability, notably in areas such as electricity consumption patterns, wildfire smoke impacts on photovoltaic systems, and demand analysis for electric vehicle charging stations. His recent articles reflect a commitment to data-driven methodologies and modeling to enhance energy system efficiency and resilience.

Articles (14)

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2025

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2024

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2024

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2024

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2024

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2024

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2024

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2023

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2023

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2023

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2021

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2020

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Assistant Professor

University of Miami

UNITED STATES

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Long Zhao

Research Interests

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About

Articles (14)

Clustering electricity consumption patterns using functional data analysis

Integrated Energy Management Scheme Considering Transportation Flexibility for Highway Service Zones

The Indexing Development for Assessing Impact of Wildfire Smoke on Photovoltaic System Performance

Data-Driven Classification for Residential Coincident Peak Demand Contributors Using Actual Power, Sociological, and Meteorological Data

Optimal Reconfiguration of Power Distribution Grids to Maintain Line Thermal Efficiency During Progressive Wildfires

Predictive Analysis of Wildfire Smoke-Induced Wiggle Effect on Low-Inertia Trending Power Grids

Data-Driven Analysis of a NEVI-Compliant EV Charging Station in the Northern Region of the U.S.

Data-Driven-Based Analysis and Modeling for The Impact of Wildfire Smoke on PV Systems

Demand and Sustainability Analysis for A Level-3 Charging Station on the U.S. Highway Based on Actual Smart Meter Data

Distributed Auto-Clustering for Residential Load Profiling Using AMI Data from The U.S. High Plains

Impact of Societal Events on Frequency Stability Considering LED TVs in Low Inertia Trending Power Systems

High-Speed Arcing Fault Detection: Using the Light Spectrum

Optimized Frequency Scanning of Nonlinear Devices Applied to Subsynchronous Resonance Screening

The Design of a Remote Online Holistic Monitoring System for a Wind Turbine

Collaborators (5)

Wei-Jen Lee

Payman Dehghanian

Soundar Kumara

Kangwon Seo

Cheng-Bang Chen

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