Grid Side Distributed Energy Storage Cloud Group End Region Hierarchical Time-Sharing Configuration Algorithm Based on Multi-Scale and Multi Feature Convolution Neural Network-Reference-Cited by-同舟云学术

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Grid Side Distributed Energy Storage Cloud Group End Region Hierarchical Time-Sharing Configuration Algorithm Based on Multi-Scale and Multi Feature Convolution Neural Network

Published:2023 Issue:5 Volume:120 Page:1253-1269
ISSN:0199-8595
Container-title:Energy Engineering
language:en
Short-container-title:

Author:

Long Wen,Zhu Bin,Li Huaizheng,Zhu Yan,Chen Zhiqiang,Cheng Gang

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

Energy Engineering and Power Technology,Building and Construction,Renewable Energy, Sustainability and the Environment

Link

https://www.techscience.com/energy/v120n5/51729/pdf

Reference17 articles.

1. Design, construction, and testing of a desktop superconducting series reactor toward the grid installation of a prototype unit;Khan;IEEE Transactions on Applied Superconductivity,2020

2. Transient stability improvement of wave energy conversion systems connected to power grid using anti-windup-coot optimization strategy;Mahdy;Energy,2022

3. Bounding regression errors in data-driven power grid steady-state models;Liu;IEEE Transactions on Power Systems,2021

4. The rise in investors’ awareness of climate risks after the paris agreement and the clean energy-oil-technology prices nexus;Fahmy;Energy Economics,2022

5. Assessing trade-offs among electrification and grid decarbonization in a clean energy transition: Application to New York State;Conlon;Energy,2022

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