With the aid of global positioning system (GPS), synchronized measurement devices (SMDs) are increasingly deployed across power systems to monitor the status of electric grids by providing accurate measurement data along with unified time stamps. Unfortunately, GPS receivers tend to lose signal lock when certain uncontrollable and unpredictable factors arise. In order to investigate the presence of GPS signal loss (GSL) issues on measurement devices, analysis is performed on historical data from both phasor data concentrators and FNET/GridEye servers. Meanwhile, the impact of GSL on field measurement accuracy has not been previously explored in depth. Through analysis and experimental tests, this paper discovers angle drift caused by GSL, which consequently leads to the total vector error exceeding the IEEE standard C37.118.1-2011. Furthermore, a compensation method is proposed to rectify the angle drift and laboratory experiments demonstrate that the proposed method does effectively reduce angle drift and mitigate the impact of GSL in SMDs.

The distribution-level electric network frequency (ENF) extracted from an electric power signal is a promising forensic tool for multimedia recording authentication. Local characteristics in ENF signals recorded in different locations act as environmental signatures, which can be potentially used as a fingerprint for location identification. In this paper, a reference database is established for distribution-level ENF using FNET/GridEye system. An ENF identification method that combines a wavelet-based signature extraction and feedforward artificial neural network-based machine learning is presented to identify the location of unsourced ENF signals without relying on the availability of concurrent signals. Experiments are performed to validate the effectiveness of the proposed method using ambient frequency measurements at multiple geographic scales. Identification accuracy is presented, and the factors that affect identification performance are discussed.

The wide area monitoring system (WAMS) is considered a pivotal component of future electric power grids. As a pilot WAMS that has been operated for more than a decade, the frequency monitoring network FNET/GridEye makes use of hundreds of global positioning system-synchronized phasor measurement sensors to capture the increasingly complicated grid behaviors across the interconnected power systems. In this paper, the FNET/GridEye system is overviewed and its operation experiences in electric power grid wide area monitoring are presented. Particularly, the implementation of a number of data analytics applications will be discussed in details. FNET/GridEye lays a firm foundation for the later WAMS operation in the electric power industry.

This study presents a method to locate power system disturbances using wide‐area synchropahsor measurements. The merits of the proposed method include robustness and ease of visualisation. In addition, the proposed method facilitates the calculation of electromechanical wave propagation speed distribution. Examples of locating the disturbance and generating the propagation speed distribution are demonstrated using the FNET/GridEye system, a distribution‐level wide‐area measurement system. Without losing generality, the proposed method can be implemented in any other wide‐area measurement system.

Global positioning system (GPS)-based phasor measurement units (PMUs) are increasingly deployed in the power system in order to monitor the grid status in real time. Nevertheless, GPS receivers inside PMUs tend to lose signal lock when certain uncontrollable and unpredictable factors arise. To address this issue, the chip-scale atomic clock is proposed to be used as a backup solution for time synchronization in this paper. It is the first time ever reporting the utilization of CSAC in the electric power grid. Test results show that CSAC can work as a reliable and accurate backup for GPS timing.

This paper focuses on a novel method for successive approximation register analog to digital converter control in synchronized phasor measurement units (PMUs). To compensate for the sampling time error caused by the division remainder between the desirable sampling rate and the oscillator frequency, a variable sampling interval control method is presented by interlacing two integers under a proposed criterion. The frequency of the onboard oscillator is monitored in real-time using the pulse per second (PPS) timing reference from global positioning system. The sampling control is adaptively adjusted each second according to the latest estimated oscillator frequency. The “saw tooth” in phasor angle error and DC offset and spikes in frequency error can be effectively eliminated by applying the proposed method. The simulation and experiment results validate the effectiveness and accuracy of the proposed method, which is believed to be able to greatly improve the performance of PPS-disciplined synchronous sampling methods in PMUs.