LAPSE:2023.36658
Published Article
LAPSE:2023.36658
A Cloud-Edge Computing Method for Integrated Electricity-Gas System Dispatch
Xueping Li, Ziyang Wang
September 20, 2023
An integrated electric−gas system (IEGS) is the manifestation and development direction of a modern smart power system. This paper employs the cloud-edge computing method to research IEGS’s optimal dispatch to satisfy data protection requirements between power systems and natural gas systems and reduce data transmission pressure. Based on cloud-edge computing architecture, this paper constructs a cloud-edge computing method based on the Multi-agent Deep Deterministic Policy Gradient (MADDPG) algorithm to solve optimal dispatch problems. Then, this paper proposes an IEGS dispatch strategy based on cloud-edge computing, which conducts distributed computing independently at the edge of power and natural gas, and the cloud implements global dispatch based on boundary information and edge learning parameters. This method does not require the exchange of all information between the power system and natural gas system, effectively protecting data privacy. This paper takes the improved IEGS of the IEEE 9 node and Gas 8 node as an example to analyze. The equipment output of this dispatch method is within a reasonable range, and the cost is reduced by 0.21% to 1.03% compared with other methods, which verifies the effectiveness of the cloud-edge computing method in solving dispatch problems.
Keywords
cloud-edge computing, integrated electric–gas system, MADDPG, optimal dispatch
Suggested Citation
Li X, Wang Z. A Cloud-Edge Computing Method for Integrated Electricity-Gas System Dispatch. (2023). LAPSE:2023.36658
Author Affiliations
Li X: Key Lab of Power Electronics for Energy Conservation and Motor Drive of Hebei Province, Yanshan University, Qinhuangdao 066004, China
Wang Z: Key Lab of Power Electronics for Energy Conservation and Motor Drive of Hebei Province, Yanshan University, Qinhuangdao 066004, China
Journal Name
Processes
Volume
11
Issue
8
First Page
2299
Year
2023
Publication Date
2023-07-31
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr11082299, Publication Type: Journal Article
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LAPSE:2023.36658
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doi:10.3390/pr11082299
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Sep 20, 2023
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CC BY 4.0
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[v1] (Original Submission)
Sep 20, 2023
 
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Sep 20, 2023
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Original Submitter
Calvin Tsay
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