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Optimization Strategy of New Energy Distributed Energy Storage Cluster Based on Intelligent Manufacturing

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DOI: 10.23977/autml.2023.040110 | Downloads: 10 | Views: 348

Author(s)

Yantong Zhu 1, Haibo Wang 1, Peng Liu 1, Jiaren He 1

Affiliation(s)

1 National Energy Investment Group Lingwu Power Generation Co., Ltd. Lingwu 751400, China

Corresponding Author

Yantong Zhu

ABSTRACT

With the rapid development and widespread use of new energy, distributed energy storage technology has become an important method to address the fluctuations and instability of new energy. The development of intelligent manufacturing technology provides new ideas and methods for the optimization of new energy distributed energy storage clusters. Therefore, this article aims to explore the optimization strategy of new energy distributed energy storage clusters based on intelligent manufacturing, with a view to providing reference and reference for research and practice in the field of new energy storage. This paper discusses the application of distributed energy storage systems and intelligent manufacturing in the optimization strategy of new energy distributed energy storage clusters, proposes a distributed optimal scheduling technology, and conducts experimental research on the optimization of new energy distributed energy storage systems. The experimental results in this paper show that when the installed capacity ratio is 70%, the distributed energy storage system achieves the goals of the highest energy utilization rate, the lowest carbon emission rate, and the lowest total annual cost, and achieves dual improvements in economic and environmental benefits.

KEYWORDS

Energy Storage Cluster, Intelligent Manufacturing, New Energy Distribution, Optimization Strategy, Optimization Scheduling

CITE THIS PAPER

Yantong Zhu, Haibo Wang, Peng Liu, Jiaren He, Optimization Strategy of New Energy Distributed Energy Storage Cluster Based on Intelligent Manufacturing. Automation and Machine Learning (2023) Vol. 4: 63-70. DOI: http://dx.doi.org/10.23977/autml.2023.040110.

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