A New Phase Detection Method by Using Kalman Filter

2011 ◽  
Vol 12 (5) ◽  
Author(s):  
Hayato Yamauchi ◽  
Kosuke Uchida ◽  
Atsushi Yona ◽  
Tomonobu Senju
Keyword(s):  
Kalman Filter ◽  
Power Systems ◽  
Detection Method ◽  
Voltage Drop ◽  
Positive Sequence ◽  
Phase Detection ◽  
Harmonic Detection ◽  
Compensation Circuit ◽  
Voltage Compensation ◽  
Unbalanced Voltage

This paper proposes a phase detection method for harmonics and unbalanced voltage conditions. The proposed method uses harmonics and unbalanced voltage compensation circuit in addition to basic PLL (Phase Locked Loop) circuit. In the harmonic compensation circuit, the harmonic voltage component are eliminated from the input voltages using specific harmonic detection method. Besides, frequency information of power system used in the specific harmonic detection method is estimated by an extended complex Kalman filter. In the unbalanced voltage compensation circuit, the input voltage is normalized after the calculated positive sequence component. By means of the proposed method, excellent phase detection performance can be achieved under harmonics and unbalanced voltage conditions. Moreover, detection of positive sequence voltage component becomes possible under voltage drop conditions due to faults in power systems. The effectiveness of the proposed method is verified by simulation results.

scholarly journals An improved ip-iq harmonic detection method

2021 ◽  
Vol 248 ◽  
pp. 02045
Author(s):  
Yang Guoqing ◽  
Yan Kai ◽  
Wang Deyi ◽  
Chai Yuan ◽  
He Xu
Keyword(s):  
Reactive Power ◽  
Detection Method ◽  
Moving Average ◽  
Notch Filter ◽  
Positive Sequence ◽  
Harmonic Detection ◽  
Grid Voltage ◽  
Adaptive Notch Filter ◽  
Voltage Signal ◽  
Low Pass

The ip-iq harmonic detection method based on instantaneous reactive power has been widely used in active power filter (APF). However, the traditional ip-iq detection method has errors when the grid voltage is unbalanced and distorted. This paper proposes an improved ip-iq harmonic detection method, which uses adaptive notch filter (ANF) to extract the fundamental positive-sequence voltage signal, so that the phase locked loop (PLL) can still accurately obtain the phase information under bad grid conditions. At the same time, moving average filter (MAF) is used to replace low-pass filtering to reduce the detection delay. The simulation results show that the improved ip-iq detection method can accurately detect harmonic current under non-ideal grid voltage conditions, and has good dynamic characteristics.

The Selective Harmonic Detection for the Integration Photovoltaic Generation and Active Power Filter

2011 ◽  
Vol 58-60 ◽  
pp. 781-786
Author(s):  
Yan Dan Lin ◽  
Li Qing Tong ◽  
Yao Jie Sun
Keyword(s):  
Control Strategy ◽  
Detection Method ◽  
Active Power Filter ◽  
Active Power ◽  
Positive Sequence ◽  
Harmonic Detection ◽  
Power Filter ◽  
Three Phase ◽  
Frequency Domains ◽  
And Control

To improve the utilization of the inverter of the photovoltaic grid connected systems and decrease the harmonic of the grid, a novel selective harmonic detection method based on the synchronous rotator frame is proposed. Utilizing three-phase Park transform, the rotator vector is transferred to the static vector, and the synchronous harmonic is separated and acquired. The characteristic of negative and positive sequence harmonic is fleetly and exactly presented in all frequency domains. Additional, a new control strategy based on this harmonic detection is proposed for the integration photovoltaic grid connected generation and active power filter. Validity and practicality of the proposed selective harmonic detection method and control strategy are proved.

A Current Harmonic Detection Method via Input Observer

2014 ◽  
Vol 548-549 ◽  
pp. 655-658 ◽  
Author(s):  
Po Li ◽  
Di Bin Huang ◽  
Peng Wang
Keyword(s):  
Power Systems ◽  
Detection Method ◽  
Current Signal ◽  
Matlab Simulation ◽  
Harmonic Detection ◽  
Current Harmonic ◽  
Active Power Filters ◽  
Power Filters ◽  
Error System ◽  
A Current

The current harmonic detection method is an important part in the control of active power filters used in power systems, since inaccuracy in harmonic detection yields to incorrect compensation. In this paper, an input observer for current harmonic detection is proposed. Firstly, a integral unit of the measured current signal is introduced to establish an augment function,then based on the augment system an observer is deduced. By constructing a Lyapunov function, the stabilization of the error system between the augment system and its observer is proved, which means the observed current harmonic approaches their real values. Finally, the proposed method is validated by Matlab simulation.

scholarly journals A rapid harmonic detection method for grid-connected photovoltaic when three-phase voltage is unbalanced

2021 ◽  
Author(s):  
Tiezhou Wu ◽  
An Wang ◽  
Yawen Xu
Keyword(s):  
Phase Angle ◽  
Detection Method ◽  
Positive Sequence ◽  
Harmonic Detection ◽  
Phase Voltage ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Negative Sequence ◽  
Three Phase ◽  
Low Pass

Abstract By using power electronic devices, photovoltaic grid-connected power generation may inject harmonics into the power system. As the photovoltaic grid-connected inverter has the same basic structure as the active power filter, so the unified control of the photovoltaic grid and active filtering can be achieved. When the current unified control system compensates harmonics of the grid side, it mainly uses ip-iq harmonic detection method, which is based on instantaneous reactive power theory. When the three-phase voltage is unbalanced, the method has a large voltage phase angle detection error and the signal of the low-pass filter tracking system is long, detection time delay and even failure occur. This paper proposes an improved fast harmonic detection method. When phase deviation or amplitude change occurs to the three-phase voltage, the positive and negative-sequence voltages are simultaneously park transformed. The negative-sequence component is filtered by the current average module to obtain the fundamental amount of the voltage, then the phase angle of the positive-sequence voltage is accurately calculated to improve the harmonic current detection accuracy. Through the study of the integral method, it is found that the least common multiple of each harmonic period can be used as the integral interval, and the integral value is also zero, so the detection delay time is reduced by replacing the low-pass filter with an integration module. The simulation results show that the proposed harmonic detection algorithm can accurately detect harmonics when the three-phase voltage is unbalanced, and about 0.057 s improve the harmonic detection speed compared with the commonly used ip-iq method.

A New Phase Detection Method by Using Kalman Filter

ENERGYO ◽  
2018 ◽  
Author(s):  
Hayato Yamauchi ◽  
Kosuke Uchida ◽  
Atsushi Yona ◽  
Tomonobu Senju
Keyword(s):  
Kalman Filter ◽  
Detection Method ◽  
Phase Detection ◽  
New Phase

scholarly journals A Two-Phase Fashion Apparel Detection Method Based on YOLOv4

2021 ◽  
Vol 11 (9) ◽  
pp. 3782
Author(s):  
Chu-Hui Lee ◽  
Chen-Wei Lin
Keyword(s):  
Object Detection ◽  
Transfer Learning ◽  
Detection Method ◽  
Phase Transfer ◽  
Recognition Task ◽  
Phase Detection ◽  
Target Domain ◽  
Two Phase ◽  
Detection Technology ◽  
Fashion Apparel

Object detection is one of the important technologies in the field of computer vision. In the area of fashion apparel, object detection technology has various applications, such as apparel recognition, apparel detection, fashion recommendation, and online search. The recognition task is difficult for a computer because fashion apparel images have different characteristics of clothing appearance and material. Currently, fast and accurate object detection is the most important goal in this field. In this study, we proposed a two-phase fashion apparel detection method named YOLOv4-TPD (YOLOv4 Two-Phase Detection), based on the YOLOv4 algorithm, to address this challenge. The target categories for model detection were divided into the jacket, top, pants, skirt, and bag. According to the definition of inductive transfer learning, the purpose was to transfer the knowledge from the source domain to the target domain that could improve the effect of tasks in the target domain. Therefore, we used the two-phase training method to implement the transfer learning. Finally, the experimental results showed that the mAP of our model was better than the original YOLOv4 model through the two-phase transfer learning. The proposed model has multiple potential applications, such as an automatic labeling system, style retrieval, and similarity detection.

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