LAPSE:2020.0962
Published Article
LAPSE:2020.0962
Adaptive Control Strategy of Energy Storage System Participating in Primary Frequency Regulation
Chaoxiong Fang, Yuchen Tang, Rong Ye, Zhangsui Lin, Zhenshan Zhu, Buying Wen, Chengtao Ye
September 15, 2020
In order to solve the capacity shortage problem in power system frequency regulation caused by large-scale integration of renewable energy, the battery energy storage-assisted frequency regulation is introduced. In this paper, an adaptive control strategy for primary frequency regulation of the energy storage system (ESS) was proposed. The control strategy combined virtual droop control, virtual inertial control, and virtual negative inertial control. The virtual inertial control was used to reduce the frequency change rate, and the virtual droop control was used to reduce the steady-state frequency deviation. The virtual droop control and the virtual inertia control were adopted in the frequency deterioration stage to slow down the frequency drop. While in the frequency recovery stage, the virtual negative inertia control worked together with the virtual droop control to accelerate the frequency recovery. Besides, the coefficients of the control methods were related to the state of charge (SOC) of ESS to avoid over-charging and over-discharging of the battery. Finally, a simulation model was built in MATLAB/SIMULINK, and case studies were conducted to verify the proposed control strategy. Results showed that the proposed method could meet the demand for frequency regulation and was beneficial to the cycle life of ESS.
Keywords
drop control, Energy Storage, primary frequency regulation, virtual inertial control
Suggested Citation
Fang C, Tang Y, Ye R, Lin Z, Zhu Z, Wen B, Ye C. Adaptive Control Strategy of Energy Storage System Participating in Primary Frequency Regulation. (2020). LAPSE:2020.0962
Author Affiliations
Fang C: State Grid Fujian Economic Research Institute, Fuzhou 350000, China
Tang Y: State Grid Fujian Economic Research Institute, Fuzhou 350000, China
Ye R: State Grid Fujian Economic Research Institute, Fuzhou 350000, China
Lin Z: State Grid Fujian Economic Research Institute, Fuzhou 350000, China
Zhu Z: College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350116, China [ORCID]
Wen B: College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350116, China
Ye C: College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350116, China
Journal Name
Processes
Volume
8
Issue
6
Article Number
E687
Year
2020
Publication Date
2020-06-12
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr8060687, Publication Type: Journal Article
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LAPSE:2020.0962
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doi:10.3390/pr8060687
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Sep 15, 2020
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Sep 15, 2020
 
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Calvin Tsay
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