LAPSE:2019.1046
Published Article
LAPSE:2019.1046
Air-Conditioning Resource Management and Control Method based on Cloud Platform for Wind Power Consumption
Kaixin Liang, Jinying Yu, Xin Wu
September 23, 2019
Air-conditionings have energy storage functions. Through reasonable aggregation control, the output tracking can be implemented for wind power with stronger fluctuation to enhance its utilization rate. Cloud technology and intelligent appliances enable the appliance vendor to implement information interaction with the air-conditioning through cloud platforms to realize flexible regulation. In this paper, a management and control method of air-conditioning based on cloud platform is established. Based on this structure, the air-conditionings are divided into several aggregation groups according to the similarity of parameters, and each group completes the consumption task collaboratively. The consumption evaluation model of the air-conditioning group is established. On this basis, the allocation problem on consumption task for the aggregated group is constructed to implement the optimal solution under the condition of guaranteeing the degree of completion and user comfort. Each group implements the control for air-conditioning inside the group through the sliding mode control model. The simulation experiment verifies that the algorithm can effectively follow the output of clean energy, while intervening less in the air-conditioning operation.
Keywords
air-conditioning grouping collaborative control, air-conditioning management, cloud control, wind power tracking
Suggested Citation
Liang K, Yu J, Wu X. Air-Conditioning Resource Management and Control Method based on Cloud Platform for Wind Power Consumption. (2019). LAPSE:2019.1046
Author Affiliations
Liang K: School of Electric and Electronic Engineering, North China Electric Power University, Beijing 102206, China
Yu J: School of Electric and Electronic Engineering, North China Electric Power University, Beijing 102206, China
Wu X: School of Electric and Electronic Engineering, North China Electric Power University, Beijing 102206, China
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Journal Name
Processes
Volume
7
Issue
7
Article Number
E467
Year
2019
Publication Date
2019-07-19
Published Version
ISSN
2227-9717
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Original Submission
Other Meta
PII: pr7070467, Publication Type: Journal Article
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LAPSE:2019.1046
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doi:10.3390/pr7070467
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Sep 23, 2019
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CC BY 4.0
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Sep 23, 2019
 
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Sep 23, 2019
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Original Submitter
Calvin Tsay
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