Wenxuan Yao

Wide-Area-Measurement System Development at the Distribution Level: An FNET/GridEye Example

Summary form only given. Electric power grid wide-area monitoring system (WAMS) have been extended from the transmission to distribution level. As the first WAMS deployed at the distribution level, the frequency monitoring network FNET/GridEye uses GPS-time-synchronized monitors called frequency disturbance recorders (FDRs) to capture dynamic grid behaviors. In this paper, the latest developments of monitor design and the state-of-the-art data analytics applications of FNET/GridEye are introduced. Its innovations and uniqueness are also discussed. Thanks to its low cost, easy installation and multi-functionalities, FNET/GridEye works as a cost-effective situational awareness tool for power grid operators and pioneers the development of WAMS in electric power grids.

Utilization of Chip-Scale Atomic Clock for Synchrophasor Measurements

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, chip scale atomic clock (CSAC) 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.

Impact of High PV Penetration on the Inter-Area Oscillations in the U.S. Eastern Interconnection

This study explores the impact of high-photovoltaic (PV) penetration on the inter-area oscillation modes of large-scale power grids. A series of dynamic models with various PV penetration levels are developed based on a detailed model representing the U.S. Eastern Interconnection (EI). Transient simulations are performed to investigate the change of inter-area oscillation modes with PV penetration. The impact of PV control strategies and parameter settings on inter-area oscillations is studied. This paper finds that as PV increases, the damping of the dominant oscillation mode decreases monotonically. It is also observed that the mode shape varies with the PV control strategy and new oscillation modes may emerge under inappropriate parameter settings in PV plant controls.

A Distribution Level Wide Area Monitoring System for the Electric Power Grid–FNET/GridEye

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.

Ring-down oscillation mode identification using multivariate Empirical Mode Decomposition

Inter-area oscillation in a large power systems draws much attention because it might severely influence system security and reduce transmission capability. The recent large-scale deployment of phasor measurement units (PMUs) enables online measurement-based monitoring and analysis on inter-area oscillatory modes. However, the nonstationary characteristics of measurements become obstacles for oscillation analysis. This work proposes multivariate empirical mode decomposition (MEMD), a multi-channel time frequency analysis method, for ring-down oscillation mode identification. The capability of the MEMD in oscillation mode identification is verified based on a test system. In addition, MEMD is compared with classical Empirical Mode Decomposition (EMD) and Fast Fourier Transform (FFT) for evaluation. The result shows that MEMD can improve oscillation identification through separating different oscillation modes while persevering their phase and amplitude information.

Electrical field based wireless devices for contactless power gird phasor measurement

In conventional power grid phasor measurements, the transformers must be physically connected to lines or buses being measured for acquiring the input voltage signal. This paper presents an innovative contactless phasor measurement device, the wireless frequency disturbance recorder (wireless FDR), to realize contactless power grid phasor measurements based on the electrical field generated by high-voltage power transmission lines. The wireless FDR has the merit of portability and flexibility, making it possible to obtain the phasor parameters at any point under the transmission line. Both the laboratory and field test results show that the wireless FDR satisfies the requirements for power system phasor analysis.

Application of wide area power system measurement for digital authentication

The Electric Network Frequency (ENF) analysis of a digital recording is a two-step process. First, an ENF extraction algorithm is applied to the recording and the second step is comparing the extracted target sequence to subsequences contained in a grid reference database. In this paper, a new comparison algorithm is created that can remove the effects of oscillator errors from comparisons. Another study is to have a better understanding of the phenomenology by which sinusoidal grid signals find their way onto digital recordings. In addition, a study that uses both frequency and phase angle is done to determine whether tampering has occurred in digital recordings. Besides being able to determine the recording time, a study that distinguishes the frequency from different locations is performed to possibly determine the location of the recording.

Non-Invasive Identification of Inertia Distribution Change in High Renewable Systems Using Distribution Level PMU

This letter proposed an approach to identify the change of inertia distribution in high renewable power systems. Using the footprints of electromechanical wave propagation at the distribution level, this approach provides a new and non-invasive way to aware the system inertia distribution for primary frequency response. Actual measurements and high renewable dynamic models validated effectiveness of the approach.

Pioneer Design of Non-contact Synchronized Measurement Devices Using Electric and Magnetic Field Sensors

Traditional synchrophasors rely on current transformers and potential transformers physically connected to transmission lines or buses to acquire input signals for phasor measurement. However, it is challenging to install and maintain traditional phasor measurement units in some remote areas due to lack of facilities. Since transmission lines naturally generate alternating electrical and magnetic fields in the surrounding atmosphere, this paper presents two innovative designs for non-contact synchronized measurement devices (NCSMDs), including an electric field sensor-based non-contact SMD (E-NCSMD) and a magnetic field sensor-based non-contact SMD (M-NCSMD). Compared with conventional synchrophasors, E-NCSMD and M-NCSMD are much more flexible to be deployed and have much lower costs, making E-NCSMDs and M-NCSMD highly accessible and useful for a wide array of phasor measurement applications. Laboratory and field experiment results verified the effectiveness of the designs of both E-NCSMD and M-NCSMD.

Source Location Identification of Distribution-Level Electric Network Frequency Signals at Multiple Geographic Scales

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.