Demand Response Using Disturbance Estimation-Based Kalman Filtering for the Frequency Control

Xuehua Wu, Qianqian Qian and Yuqing Bao ()
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Xuehua Wu: School of Electrical Engineering, Nanjing Vocational University of Industry Technology, Nanjing 210023, China
Qianqian Qian: School of Electrical Engineering and Automation, Nanjing Normal University, Nanjing 210023, China
Yuqing Bao: School of Electrical Engineering and Automation, Nanjing Normal University, Nanjing 210023, China

Energies, 2022, vol. 15, issue 24, 1-14

Abstract: 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; Kalman filtering; frequency control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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