An IGDT-Based Day-Ahead Co-Optimization of Energy and Reserve in a VPP Considering Multiple Uncertainties-Reference-Cited by-同舟云学术

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An IGDT-Based Day-Ahead Co-Optimization of Energy and Reserve in a VPP Considering Multiple Uncertainties

Published:2022-05 Issue:3 Volume:58 Page:4037-4049
ISSN:0093-9994
Container-title:IEEE Transactions on Industry Applications
language:
Short-container-title:IEEE Trans. on Ind. Applicat.

Author:

Yan Xingyu¹^ORCID,Gao Ciwei¹^ORCID,Song Meng¹^ORCID,Chen Tao¹^ORCID,Ding Jianyong¹,Guo Mingxing²,Wang Xiaohui²,Abbes Dhaker³^ORCID

Affiliation:

1. Department of Electrical Engineering, Southeast University, Nanjing, China

2. Economic and Technical Research Institute, Shanghai Municipal Electric Power Company, Shanghai, China

3. Department of Energies and Smart Systems, HEI, Junia Grande Ecole d'Ingénieurs, Lille, France

Funder

National Natural Science Foundation of China

Fund of Shanghai Science and Technology Development

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/28/9778222/09716873.pdf?arnumber=9716873

Reference31 articles.

1. Convex Relaxation of Optimal Power Flow—Part I: Formulations and Equivalence

2. A two-stage robust reactive power optimization considering uncertain wind power integration in active distribution networks;ding;IEEE Trans Sustain Energy,2015

3. Optimal demand response strategy of commercial building‐based virtual power plant using reinforcement learning

4. Day-Ahead Self-Scheduling of a Virtual Power Plant in Energy and Reserve Electricity Markets Under Uncertainty

5. Wind and Solar Power Integration in Electricity Markets and Distribution Networks Through Service-Centric Virtual Power Plants

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