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Optimized scheduling study of user side energy storage in cloud energy storage model
With the new round of power system reform, energy storage, as a part of power system frequency regulation and peaking, is an indispensable part of the reform. Among them, user-side small energy storage devices have the advantages of small size, flexible use and convenient application, but present de...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10620393/ https://www.ncbi.nlm.nih.gov/pubmed/37914746 http://dx.doi.org/10.1038/s41598-023-45673-4 |
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author | Wang, Huidong Yao, Haiyan Zhou, Jizhou Guo, Qiang |
author_facet | Wang, Huidong Yao, Haiyan Zhou, Jizhou Guo, Qiang |
author_sort | Wang, Huidong |
collection | PubMed |
description | With the new round of power system reform, energy storage, as a part of power system frequency regulation and peaking, is an indispensable part of the reform. Among them, user-side small energy storage devices have the advantages of small size, flexible use and convenient application, but present decentralized characteristics in space. Therefore, the optimal allocation of small energy storage resources and the reduction of operating costs are urgent problems to be solved. In this study, the author introduced the concept of cloud energy storage and proposed a system architecture and operational model based on the deployment characteristics of user-side energy storage devices. Additionally, a cluster scheduling matching strategy was designed for small energy storage devices in cloud energy storage mode, utilizing dynamic information of power demand, real-time quotations, and supply at the load side. Subsequently, numerical analysis was conducted to verify that the proposed operational mode and optimal scheduling scheme ensured the maximum absorption of renewable energy, improved the utilization rate of energy storage resources at the user side, and contributed to peak shaving and load leveling in the power grid. The model put forward in this study represents a valuable exploration for new scenarios in energy storage application. |
format | Online Article Text |
id | pubmed-10620393 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106203932023-11-03 Optimized scheduling study of user side energy storage in cloud energy storage model Wang, Huidong Yao, Haiyan Zhou, Jizhou Guo, Qiang Sci Rep Article With the new round of power system reform, energy storage, as a part of power system frequency regulation and peaking, is an indispensable part of the reform. Among them, user-side small energy storage devices have the advantages of small size, flexible use and convenient application, but present decentralized characteristics in space. Therefore, the optimal allocation of small energy storage resources and the reduction of operating costs are urgent problems to be solved. In this study, the author introduced the concept of cloud energy storage and proposed a system architecture and operational model based on the deployment characteristics of user-side energy storage devices. Additionally, a cluster scheduling matching strategy was designed for small energy storage devices in cloud energy storage mode, utilizing dynamic information of power demand, real-time quotations, and supply at the load side. Subsequently, numerical analysis was conducted to verify that the proposed operational mode and optimal scheduling scheme ensured the maximum absorption of renewable energy, improved the utilization rate of energy storage resources at the user side, and contributed to peak shaving and load leveling in the power grid. The model put forward in this study represents a valuable exploration for new scenarios in energy storage application. Nature Publishing Group UK 2023-11-01 /pmc/articles/PMC10620393/ /pubmed/37914746 http://dx.doi.org/10.1038/s41598-023-45673-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wang, Huidong Yao, Haiyan Zhou, Jizhou Guo, Qiang Optimized scheduling study of user side energy storage in cloud energy storage model |
title | Optimized scheduling study of user side energy storage in cloud energy storage model |
title_full | Optimized scheduling study of user side energy storage in cloud energy storage model |
title_fullStr | Optimized scheduling study of user side energy storage in cloud energy storage model |
title_full_unstemmed | Optimized scheduling study of user side energy storage in cloud energy storage model |
title_short | Optimized scheduling study of user side energy storage in cloud energy storage model |
title_sort | optimized scheduling study of user side energy storage in cloud energy storage model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10620393/ https://www.ncbi.nlm.nih.gov/pubmed/37914746 http://dx.doi.org/10.1038/s41598-023-45673-4 |
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