Data-Driven Low-Rank Tensor Approximation for Fast Grid Integration of Commercial EV Charging Stations Considering Demand Uncertainties-Reference-Cited by-同舟云学术

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Data-Driven Low-Rank Tensor Approximation for Fast Grid Integration of Commercial EV Charging Stations Considering Demand Uncertainties

Published:2023-01 Issue:1 Volume:14 Page:517-529
ISSN:1949-3053
Container-title:IEEE Transactions on Smart Grid
language:
Short-container-title:IEEE Trans. Smart Grid

Author:

Jiang Yazhou¹^ORCID,Ortmeyer Thomas H.¹,Fan Miao²^ORCID,Ai Xiaomeng³^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, Clarkson University, Potsdam, NY, USA

2. Digital Grid Business Unit, Siemens Industry Inc., Schenectady, NY, USA

3. School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/5165411/9997165/09830763.pdf?arnumber=9830763

Reference35 articles.

1. A Polynomial Chaos-based Approach to Quantify Uncertainties of Correlated Renewable Energy Sources in Voltage Regulation

2. Joined Probabilistic Load Flow and Sensitivity Analysis of Distribution Networks Based on Polynomial Chaos Method

3. Basis-Adaptive Sparse Polynomial Chaos Expansion for Probabilistic Power Flow

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1. Probabilistic Frequency Stability Analysis Considering Dynamics of Wind Power Generation With Different Control Strategies;IEEE Transactions on Power Systems;2024-09

2. AC False Data Injection Attack Based on Robust Tensor Principle Component Analysis;IEEE Transactions on Industrial Informatics;2024-08

3. Hierarchical framework for demand prediction and iterative optimization of EV charging network infrastructure under uncertainty with cost and quality-of-service consideration;Expert Systems with Applications;2024-03

4. Data-Driven Fast Uncertainty Assessment of Distribution Systems With Correlated EV Charging Demand and Renewable Generation;IEEE Transactions on Sustainable Energy;2023-07

5. Analytical Probabilistic Power Flow and Global Sensitivity Analysis of Distribution Systems Based on Gaussian Mixture Model of Input-Output Variables;IEEE Transactions on Power Systems;2023

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