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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

The deployment of a green power alternative within an isolated network, powered by renewable energy sources, in the “Three North” region of China can facilitate the substitution of high-energy-consuming industrial loads with green power. However, an inadequate power supply configuration may lead to economic and reliability issues. To address this problem, effective capacity allocation within the green power alternative isolated network is proposed. The capacity allocation process starts with the design of a network structure that aligns with local conditions. Subsequently, a capacity allocation model is developed, considering economic factors, renewable energy utilization efficiency, and system reliability. The gray wolf optimizer is enhanced to establish a capacity allocation method for the green power alternative isolated network. This method is then employed to simulate and assess the performance of the network. The results indicate that the green alternative isolated grid can successfully facilitate green power substitution, satisfying the energy requirements of the loads.

Details

Title
Research on Capacity Configuration for Green Power Substitution in an Isolated Grid Containing Electrolytic Aluminum
Author
You, Min 1 ; Wang, Yunguang 2 ; Wang, Haiyun 1 ; Wusiman, Aisikaer 2 ; Lv, Liangnian 2 

 Engineering Research Center of Education Ministry for Renewable Energy Power Generation and Grid Connection, Xinjiang University, Urumqi 830017, China; [email protected] 
 Goldwind Science & Technology Co., Ltd., Beijing 100176, China; [email protected] (Y.W.); [email protected] (A.W.); [email protected] (L.L.) 
First page
2136
Publication year
2024
Publication date
2024
Publisher
MDPI AG
e-ISSN
19961073
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3053163145
Copyright
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.