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Open AccessArticle
A Cloud–Edge Collaborative Multi-Timescale Scheduling Strategy for Peak Regulation and Renewable Energy Integration in Distributed Multi-Energy Systems
by
Zhilong Yin
Zhilong Yin 1,
Zhiyuan Zhou
Zhiyuan Zhou 2,
Feng Yu
Feng Yu 3,*
,
Pan Gao
Pan Gao 1,
Shuo Ni
Shuo Ni 1 and
Haohao Li
Haohao Li 1
1
Xi’an Dynamic Inspection and Testing Co., Ltd., Xi’an 710061, China
2
Power Dispatch Control Center, State Grid Shaanxi Electric Power Co., Ltd., Xi’an 710048, China
3
School of Electrical Engineering, Nantong University, Nantong 226019, China
*
Author to whom correspondence should be addressed.
Energies 2024, 17(15), 3764; https://doi.org/10.3390/en17153764 (registering DOI)
Submission received: 5 July 2024
/
Revised: 27 July 2024
/
Accepted: 27 July 2024
/
Published: 30 July 2024
Abstract
Incorporating renewable energy sources into the grid poses challenges due to their volatility and uncertainty in optimizing dispatch strategies. In response, this article proposes a cloud–edge collaborative scheduling strategy for distributed multi-energy systems, operating across various time scales. The strategy integrates day-ahead dispatch, intra-day optimization, and real-time adjustments to minimize operational costs, reduce the wastage of renewable energy, and enhance overall system reliability. Furthermore, the cloud–edge collaborative framework helps mitigate scalability challenges. Crucially, the strategy considers the multi-timescale characteristics of two types of energy storage systems (ESSs) and three types of demand response (DR), aimed at optimizing resource allocation efficiently. Comparative simulation results evaluate the strategy, providing insights into the significant impacts of different ESS and DR types on system performance. By offering a comprehensive approach, this strategy aims to address operational complexities. It aims to contribute to the seamless integration of renewable energy into distributed systems, potentially enhancing sustainability and resilience in energy management.
Share and Cite
MDPI and ACS Style
Yin, Z.; Zhou, Z.; Yu, F.; Gao, P.; Ni, S.; Li, H.
A Cloud–Edge Collaborative Multi-Timescale Scheduling Strategy for Peak Regulation and Renewable Energy Integration in Distributed Multi-Energy Systems. Energies 2024, 17, 3764.
https://doi.org/10.3390/en17153764
AMA Style
Yin Z, Zhou Z, Yu F, Gao P, Ni S, Li H.
A Cloud–Edge Collaborative Multi-Timescale Scheduling Strategy for Peak Regulation and Renewable Energy Integration in Distributed Multi-Energy Systems. Energies. 2024; 17(15):3764.
https://doi.org/10.3390/en17153764
Chicago/Turabian Style
Yin, Zhilong, Zhiyuan Zhou, Feng Yu, Pan Gao, Shuo Ni, and Haohao Li.
2024. "A Cloud–Edge Collaborative Multi-Timescale Scheduling Strategy for Peak Regulation and Renewable Energy Integration in Distributed Multi-Energy Systems" Energies 17, no. 15: 3764.
https://doi.org/10.3390/en17153764
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