LAPSE:2023.6963
Published Article
LAPSE:2023.6963
Demand Response Using Disturbance Estimation-Based Kalman Filtering for the Frequency Control
Xuehua Wu, Qianqian Qian, Yuqing Bao
February 24, 2023
Demand response (DR) has a great potential for stabilizing the frequency of power systems. However, the performance is limited by the accuracy of the frequency detection, which is affected by measurement disturbances. To overcome this problem, this paper proposes a disturbance estimation-based Kalman filtering method, which is utilized for the frequency control. By using the rate of change of frequency (RoCoF), the Kalman filtering method can estimate the state of the ON/OFF loads well. In this way, the influence of detection error can be reduced, and the DR performance can be improved. Test results show that the proposed disturbance estimation-based Kalman filtering method has a higher accuracy of frequency detection than existing methods (such as the low-pass filter method) and therefore improves the frequency control performance of DR.
Keywords
demand response, disturbance estimation, frequency control, Kalman filtering
Suggested Citation
Wu X, Qian Q, Bao Y. Demand Response Using Disturbance Estimation-Based Kalman Filtering for the Frequency Control. (2023). LAPSE:2023.6963
Author Affiliations
Wu X: School of Electrical Engineering, Nanjing Vocational University of Industry Technology, Nanjing 210023, China
Qian Q: School of Electrical Engineering and Automation, Nanjing Normal University, Nanjing 210023, China
Bao Y: School of Electrical Engineering and Automation, Nanjing Normal University, Nanjing 210023, China [ORCID]
Journal Name
Energies
Volume
15
Issue
24
First Page
9377
Year
2022
Publication Date
2022-12-11
Published Version
ISSN
1996-1073
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PII: en15249377, Publication Type: Journal Article
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doi:10.3390/en15249377
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Feb 24, 2023
 
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