Research on collaborative wind and solar energy storage system based on machine learning

Weihong Cao; Yingxue Sun; Wei Zhang

doi:10.1117/12.3006625

24 October 2023 Research on collaborative wind and solar energy storage system based on machine learning

Weihong Cao, Yingxue Sun, Wei Zhang

Proceedings Volume 12804, Second International Conference on Sustainable Technology and Management (ICSTM 2023); 128042P (2023) https://doi.org/10.1117/12.3006625
Event: 2nd International Conference on Sustainable Technology and Management (ICSTM2023), 2023, Dongguan, China

Abstract

On September 22,2020, China has pledged to the UN General Assembly to peak its carbon emissions by 2030 and to become carbon neutral by 2060.Under the expectation of achieving carbon neutrality, the sustainable development of renewable energy is the fundamental way to effectively solve ecological and environmental problems, reduce carbon dioxide emissions, and achieve the gradual replacement of coal and other fossil resources. In this paper in view of the independent scenery power generation system abandon power phenomenon, with a large office in Changchun city, Jilin province as the research object, On the basis of the independent landscape power generation system, the battery storage system is added, using the battery storage charging and discharging characteristics to balance the system power. The first step is to meet the demand of the building's electrical load.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Weihong Cao, Yingxue Sun, and Wei Zhang "Research on collaborative wind and solar energy storage system based on machine learning", Proc. SPIE 12804, Second International Conference on Sustainable Technology and Management (ICSTM 2023), 128042P (24 October 2023); https://doi.org/10.1117/12.3006625

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