Jie Zhang

Orcid: 0000-0001-7478-5670

Affiliations:
  • University of Texas at Dallas, Department of Mechanical Engineering, Dallas, TX, USA
  • National Renewable Energy Laboratory, Golden, CO, USA


According to our database1, Jie Zhang authored at least 29 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Online presence:

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Bibliography

2024
Black Start of Coastline Power Networks From Grid-Forming Ship-to-Grid Services.
IEEE Trans. Smart Grid, 2024

2023
Spectral Graph Clustering for Intentional Islanding Operations in Resilient Hybrid Energy Systems.
IEEE Trans. Ind. Informatics, April, 2023

2022
Short-term load forecasting data with hierarchical advanced metering infrastructure and weather features.
Dataset, May, 2022

An Occupancy-Informed Customized Price Design for Consumers: A Stackelberg Game Approach.
IEEE Trans. Smart Grid, 2022

Hierarchical Microenergy Hub Sizing and Placement in Integrated Electricity and Natural Gas Distribution Systems.
IEEE Syst. J., 2022

2021
A Community Sharing Market With PV and Energy Storage: An Adaptive Bidding-Based Double-Side Auction Mechanism.
IEEE Trans. Smart Grid, 2021

Deep Learning-Based Real-Time Switching of Hybrid AC/DC Transmission Networks.
IEEE Trans. Smart Grid, 2021

Stochastic Modeling and Integration of Plug-In Hybrid Electric Vehicles in Reconfigurable Microgrids With Deep Learning-Based Forecasting.
IEEE Trans. Intell. Transp. Syst., 2021

Defect Prediction of Relay Protection Systems Based on LSSVM-BNDT.
IEEE Trans. Ind. Informatics, 2021

Resilient Distribution Networks Considering Mobile Marine Microgrids: A Synergistic Network Approach.
IEEE Trans. Ind. Informatics, 2021

Blockchain-Based Stochastic Energy Management of Interconnected Microgrids Considering Incentive Price.
IEEE Trans. Control. Netw. Syst., 2021

2020
Reinforced Deterministic and Probabilistic Load Forecasting via $Q$ -Learning Dynamic Model Selection.
IEEE Trans. Smart Grid, 2020

Deep Learning-Based Real-Time Building Occupancy Detection Using AMI Data.
IEEE Trans. Smart Grid, 2020

Sensitivity Analysis of Renewable Energy Integration on Stochastic Energy Management of Automated Reconfigurable Hybrid AC-DC Microgrid Considering DLR Security Constraint.
IEEE Trans. Ind. Informatics, 2020

Factoring Behind-the-Meter Solar into Load Forecasting: Case Studies under Extreme Weather.
Proceedings of the IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2020

A Copula Enhanced Convolution for Uncertainty Aggregation.
Proceedings of the IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2020

SolarNet: A Deep Convolutional Neural Network for Solar Forecasting via Sky Images.
Proceedings of the IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2020

Deep Learning-based Real-time Switching of Reconfigurable Microgrids.
Proceedings of the IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2020

2019
A Data-Driven Methodology for Probabilistic Wind Power Ramp Forecasting.
IEEE Trans. Smart Grid, 2019

A Copula-Based Conditional Probabilistic Forecast Model for Wind Power Ramps.
IEEE Trans. Smart Grid, 2019

Analyze the Break-even Cost of Lithium-ion Battery under Time-of-use Pricing Tariffs.
Proceedings of the IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2019

Reinforcement Learning based Dynamic Model Selection for Short-Term Load Forecasting.
Proceedings of the IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2019

Assessing the Resilience of the Texas Power Grid Network.
Proceedings of the IEEE Data Science Workshop, 2019

2018
A Methodology for Quantifying Reliability Benefits From Improved Solar Power Forecasting in Multi-Timescale Power System Operations.
IEEE Trans. Smart Grid, 2018

An Unsupervised Clustering-Based Short-Term Solar Forecasting Methodology Using Multi-Model Machine Learning Blending.
CoRR, 2018

Hourly-Similarity Based Solar Forecasting Using Multi-Model Machine Learning Blending.
CoRR, 2018

2017
CompSim: Cross sectional modeling of geometrical complex and inhomogeneous slender structures.
SoftwareX, 2017

Characterizing Time Series Data Diversity for Wind Forecasting.
Proceedings of the Fourth IEEE/ACM International Conference on Big Data Computing, 2017

2015
Machine learning based multi-physical-model blending for enhancing renewable energy forecast - improvement via situation dependent error correction.
Proceedings of the 14th European Control Conference, 2015


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