Investigation on microwave photonic filter group delay performance

2017 ◽  
Vol 15 (8) ◽  
pp. 080604
Author(s):  
Bijuan Chen Bijuan Chen ◽  
Erwin H. W. Chan Erwin H. W. Chan ◽  
Xinhuan Feng Xinhuan Feng ◽  
Xudong Wang Xudong Wang ◽  
Bai-Ou Guan Bai-Ou Guan
Keyword(s):  
Group Delay ◽  
Delay Performance ◽  
Microwave Photonic ◽  
Filter Group

scholarly journals Few-Mode Fibers With Uniform Differential Mode Group Delay for Microwave Photonic Signal Processing

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 135176-135183 ◽  
Author(s):  
Jian Zhao ◽  
Huan Zhang ◽  
Zhiqun Yang ◽  
Jinsheng Xu ◽  
Tianhua Xu ◽  
...  
Keyword(s):  
Signal Processing ◽  
Group Delay ◽  
Differential Mode ◽  
Microwave Photonic ◽  
Mode Group

Continuously tunable microwave photonic notch filter based on the differential group delay

2010 ◽  
Vol 53 (1) ◽  
pp. 121-123 ◽  
Author(s):  
Yongxing Jin ◽  
Xinyong Dong ◽  
Junqiang Zhou ◽  
Perry Ping Shum
Keyword(s):  
Group Delay ◽  
Notch Filter ◽  
Differential Group Delay ◽  
Microwave Photonic ◽  
Differential Group ◽  
Tunable Microwave

Influences of group delay ripples of fiber gratings on characteristics of microwave photonic filter

2013 ◽  
Vol 25 (1) ◽  
pp. 12-16
Author(s):  
戈伟伟 Ge Weiwei ◽  
邹喜华 Zou Xihua ◽  
何梓昂 He Ziang ◽  
潘炜 Pan Wei ◽  
罗斌 Luo Bin ◽  
...  
Keyword(s):  
Group Delay ◽  
Fiber Gratings ◽  
Microwave Photonic

A Novel All-Pass Network Implementation for Improved Group Delay Performance

2016 ◽  
Vol 26 (10) ◽  
pp. 804-806 ◽  
Author(s):  
P. Keerthan ◽  
Ritesh Kumar ◽  
K. J. Vinoy
Keyword(s):  
Group Delay ◽  
Delay Performance

Resolving group delay of narrowband optical filters from their transmission characteristics

2009 ◽  
Vol 17 (4) ◽  
Author(s):  
Ł. Śliwczyński
Keyword(s):  
Group Delay ◽  
Power Transmission ◽  
Optical Filter ◽  
Optical Filters ◽  
Optical Spectrum Analyzer ◽  
Frequency Range ◽  
Transmission Characteristics ◽  
Factors Affecting ◽  
Filter Group ◽  
Limited Frequency

AbstractIn the paper, the factors affecting the accuracy of calculating the optical filter group delay basing on the measured power transmission characteristic are analyzed. Having the phase characteristic of the filter recovered from its transmission, the group delay is usually calculated via differentiation. The new, direct formula is proposed giving more accurate results when the characteristic of the filter is available in the limited frequency range. Also the limitations arising from the noise of the optical spectrum analyzer are examined.

An integrated PMU architecture for power system applications

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Mir Khadim Aalam ◽  
K.N. Shubhanga
Keyword(s):  
Power System ◽  
Group Delay ◽  
Small Signal Stability ◽  
Monitoring And Control ◽  
Delay Compensation ◽  
Delay Performance ◽  
Power System Monitoring ◽  
Stability Performance ◽  
Synchronized Phasors ◽  
System Stabilizer

Abstract Time synchronized phasors obtained using Phasor Measurement Units (PMU) spread across wide areas have revolutionized power system monitoring and control. These synchronized measurements must be accurate and fast in order to comply with the latest IEEE standards for synchrophasor measurements. The speed at which a PMU provides an output depends on the group delay associated with that PMU and the permissible group delay in-turn decides the utility of a PMU for either control or measurement application. Based on the group delay compensation techniques, in the literature, two individual types of PMUs, such as causal and non-causal PMUs have been introduced. This paper presents an approach where both causal and non-causal PMUs are combined in an integrated PMU architecture. This method not only illustrates the group delay performance of two PMUs in a single module, but also can be used for multiple functions. In this environment several PMU algorithms have been compared with respect to their group delays and their effect on the response time. Application of the integrated PMU architecture to a four-machine 10-bus power system has been demonstrated using a six-input PMU with three-phase voltage and current signals as inputs. Different causal compensation schemes are introduced due to the availability of voltage and current-based frequency and ROCOF signals. Impact of these compensation schemes on PMU accuracy is evaluated through the Total Vector Error (TVE) index. The influence of these compensation schemes on measurements like power and impedance is also investigated. Finally, outputs from the integrated PMU architecture are fed into a Power System Stabilizer (PSS) to control the small-signal stability performance of a power system during dynamic conditions.

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