Day-Ahead Distributionally Robust Optimization-Based Scheduling for Distribution Systems with Electric Vehicles-Reference-Cited by-同舟云学术

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Day-Ahead Distributionally Robust Optimization-Based Scheduling for Distribution Systems with Electric Vehicles

Published:2022 Issue: Volume: Page:1-1
ISSN:1949-3053
Container-title:IEEE Transactions on Smart Grid
language:
Short-container-title:IEEE Trans. Smart Grid

Author:

Shi Xiaoying¹,Xu Yinliang¹^ORCID,Guo Qinglai²^ORCID,Sun Hongbin²^ORCID,Zhang Xian³^ORCID

Affiliation:

1. Tsinghua Shenzhen International Graduate School, Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, P. R. China

2. Department of Electrical Engineering, State Key Laboratory of Power Systems, Tsinghua University, Beijing, P. R. China

3. School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, China

Funder

National Natural Science Foundation of China

Shenzhen Science and Technology Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/5165411/5446437/09955377.pdf?arnumber=9955377

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Bayesian Nonparametric Two-Stage Distributionally Robust Unit Commitment Optimization: From Global Multimodality to Local Trimming-Wasserstein Ambiguity;IEEE Transactions on Power Systems;2024-09

2. Assessment of the Renewable Energy Accommodation Capability of the Power Distribution Systems;2024 IEEE 7th International Electrical and Energy Conference (CIEEC);2024-05-10

3. Combined Peak Load Scheduling for Power Dispatching with Price Demand Response;2024 IEEE 7th International Electrical and Energy Conference (CIEEC);2024-05-10

4. Bilevel optimal coordination of active distribution network and charging stations considering EV drivers' willingness;Applied Energy;2024-04

5. Joint chance-constrained program based electric vehicles optimal dispatching strategy considering drivers' response uncertainty;Applied Energy;2024-02

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