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VBN
Article . 2021
Data sources: VBN
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Applied Energy
Article . 2021 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Multi-View clustering and discrete consensus based tri-level coordinated control of wind farm and adiabatic compressed air energy storage for providing frequency regulation service

Authors: Ji Han; Shihong Miao; Zhe Chen; Zhou Liu; Yaowang Li; Weichen Yang; Ziwen Liu;

Multi-View clustering and discrete consensus based tri-level coordinated control of wind farm and adiabatic compressed air energy storage for providing frequency regulation service

Abstract

Due to the intermittency and uncertainty natures of wind power, electrical energy storages (EESs) are often equipped in the power systems to reduce the side-effect of wind power fluctuations, and adiabatic compressed air energy storage (A-CAES) is one of EES technologies to smooth the power fluctuation of wind farms (WFs). This paper proposes a coordinated control framework of WF and A-CAES station to achieve frequency response, and discusses the active power distribution scheme among wind turbines (WTs) and A-CAES units during frequency regulation. Firstly, the models of WT and A-CAES used in frequency regulation are presented. Then, considering that the power distribution might go through a long iteration process when the number of WTs in WF is quite large, these WTs are clustered into several groups using a comprehensive multi-view grouping indicator. On the basis of the WTs grouping result and with a defined generalized energy increment (GEI), this paper proposes a discrete consensus based tri-level coordinated frequency control method, which divides the control into three levels, i.e., group level, wind farm level and coordinated level. Through the three levels’ control, the method can reasonably and rapidly distribute the frequency regulation powers among WTs and A-CAES units without being limited by the scale of WF, and the coordination of WF and A-CAES station during frequency regulation is achieved. To demonstrate the effectiveness of the proposed method, a modified WF in Inner Mongolia of China is utilized for case study. Simulation results show that the proposed method is valid in various frequency events and can reach consensus within 4 s in the studied cases, and it is well-performed with different capacities of wind powers and A-CAESs in the power systems. The common communication failures have few influences on the methods, and the frequency nadirs fluctuate lower than 0.1 Hz with time delays in the communications. Compared with centralized and multi-machine equivalent methods, the proposed distributed method can balance the computational speed and the solution accuracy, and thus is beneficial to improve the system frequency nadirs when frequency drops.

Country
Denmark
Related Organizations
Keywords

Wind farm, Frequency regulation, Discrete consensus control, Multi-view clustering, Adiabatic compressed air energy storage

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Top 10%
Top 10%