Penn N. Markham

Wide-Area Frequency Monitoring Network (FNET) Architecture and Applications

Recent developments in smart grid technology have spawned interest in the use of phasor measurement units to help create a reliable power system transmission and distribution infrastructure. Wide-area monitoring systems (WAMSs) utilizing synchrophasor measurements can help with understanding, forecasting, or even controlling the status of power grid stability in real-time. A power system frequency monitoring network (FNET) was first proposed in 2001 and was established in 2004. As a pioneering WAMS, it serves the entire North American power grid through advanced situational awareness techniques, such as real-time event alerts, accurate event location estimation, animated event visualization, and post event analysis. Several papers published in the past several years discussed the FNET structure and its functionality. This paper presents some of the latest implementations of FNETs applications, which add significant capacities to this system for observing power system problems.

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.

Inter-area oscillation analysis using wide area voltage angle measurements from FNET

The inter-area oscillations occurring in the Eastern Interconnection (EI) are investigated by six typical cases using the FNET data. The matrix pencil method of multiple signals is used for the modal analysis. The parameters related to mode shape are calculated. The mode shapes for the dominant mode are revealed for each case. Analysis results depict a view of inter-area mode distribution in the Eastern Interconnection.

Analysis of Nonlinear Characteristics for a Three-Phase, Five-Limb Transformer Under DC Bias

Monopole HVDC systems create dc current flow in the earth, which can cause the grounding location potential to rise relative to infinite spot and alters the working point of the transformer core. Because of the nonlinearity of the transformer core, the exciting current produces the amount of harmonics under dc bias. Past research has focused almost on simulation and testing dc bias problems of single-phase transformers. However, due to the complicated magnetic circuit structure in a three-phase five-limb transformer, there are some difficulties in studying its dc bias problem. In this paper, a new model and algorithm are proposed to find the nonlinear characteristics for the three-phase five-limb transformer under dc bias. Maxwells equations are used to replace the magnetic circuit model of the transformer. By combining an electrical circuit with the nonlinear characteristic curve of the core, dc bias problems for a three-phase five-limb transformer are studied. Results show that the waveform of the no-load current and magnetic field intensity of the transformer are distorted under dc current inrush, and low-order harmonics increase with increasing dc current. Finally the interior and exterior nonlinear curve characteristics under dc bias are discussed.

Application of Power System Frequency for Digital Audio Authentication

Frequency is an important parameter for the operation and control of power systems. One novel application of frequency measurements involves using this information to authenticate a digital audio/video recording presented as forensic evidence in legal proceedings. To apply this technique, called the electrical network frequency (ENF) criterion, both a reference frequency database and an accurate frequency estimation method are required. This paper briefly introduces a wide-area frequency monitoring network (FNET) as the reference frequency database and analyzes statistical features of frequency of the four North American interconnections in terms of different time scales. Combined with digital filtering and a three-sample interpolation, the short-time Fourier transform (STFT) is adjusted to estimate the ENF embedded in digital audio recordings. A procedure of using the ENF criterion, ranging from signal preprocessing to ENF estimation and reference frequency database matching, is then proposed. Further, oscillator error of the digital recording device is considered and an iterative error correction method is given to assist with the frequency database matching. Factors which influence the accuracy of frequency estimation, such as parameter selections of the STFT and signal-to-noise ratio, are also discussed. Test results show that the procedure is capable of performing digital audio authentication.

Wide-area frequency as a criterion for digital audio recording authentication

The Electrical Network Frequency (ENF) criterion is a novel method for digital audio recording authentication in the field of forensic science. Both an accurate frequency estimation method and a reliable frequency reference database are the key requirements for this technique. This paper briefly introduces the Frequency Monitoring Network (FNET) at UTK and analyzes the frequency characteristics of the four North American interconnections. Wide-area frequency measurements in each interconnection conform to the Gaussian distribution, but with slightly varied parameters. Short-time Fourier transform (STFT) is adopted to estimate the power system frequency signal embedded in audio files, and a procedure for using the ENF criterion, ranging from signal preprocessing to frequency estimation and frequency data matching, is proposed and then tested by two cases. Results show that the STFT can be used as an accurate ENF extraction method. Furthermore, factors which influence the accuracy of frequency estimation, such as the signal-to-noise ratio (SNR) and the recording hardware, are also discussed.

An Improved Discrete Fourier Transform-Based Algorithm for Electric Network Frequency Extraction

This paper introduces a Discrete Fourier Transform (DFT)-based algorithm to extract the Electric Network Frequency (ENF) information from an audio recording for use in audio authentication. The basic idea of the proposed algorithm is to calculate the specific spectral lines by DFT in the frequency domain at the desired frequency point instead of throughout the entire frequency band. Then a binary search technique is employed to search the next desired frequency bin to repeat the spectral line calculation until the hidden ENF information is extracted. The purpose is to improve the accuracy and precision of conventional ENF extraction methods and also to enhance the calculation efficiency. Both simulated audio signals with different signal-to-noise ratios (SNRs) and actual audio recordings are studied to verify the performance of the proposed algorithm. Two error-evaluation criteria, frequency offset and frequency bias, are defined to evaluate the algorithm performance on accuracy and precision. The test results and the error evaluation prove the validation and demonstrate the improvement of the proposed algorithm.

Multiple Event Detection and Recognition Through Sparse Unmixing for High-Resolution Situational Awareness in Power Grid

A situational awareness system is essential to provide accurate understanding of power system dynamics, such that proper actions can be taken in real time in response to system disturbances and to avoid cascading blackouts. Event analysis has been an important component in any situational awareness system. However, most state-of-the-art techniques can only handle single event analysis. This paper tackles the challenging problem of multiple event detection and recognition. We propose a new conceptual framework, referred to as event unmixing, where we consider real-world events mixtures of more than one constituent root event. This concept is a key enabler for analysis of events to go beyond what are immediately detectable in a system, providing high-resolution data understanding at a finer scale. We interpret the event formation process from a linear mixing perspective and propose an innovative nonnegative sparse event unmixing (NSEU) algorithm for multiple event separation and temporal localization. The proposed framework has been evaluated using both PSS/E simulated cases and real event cases collected from the frequency disturbance recorders (FDRs) of the Frequency Monitoring Network (FNET). The experimental results demonstrate that the framework is reliable to detect and recognize multiple cascading events as well as their time of occurrence with high accuracy.

Impact of Governor Deadband on Frequency Response of the U.S. Eastern Interconnection

This paper documents the effort to perform dynamic model validation for the U.S. Eastern Interconnection (EI) by modeling the governor deadband. The Western Electricity Coordinating Council-modified 1981 IEEE type 1 turbine governor model (WSIEG1) was added to the EI model. A frequency response sensitivity study is conducted to look at the impacts of a few major factors. The significance of modeling governor dead band is evident. Simulated frequency responses are adjusted and validated against the measurements collected by the frequency monitoring network. Two actual events are replicated in a 16 000-bus EI dynamic model. This paper demonstrates the need for a comprehensive effort on governor dead band modeling by the industry.

Visualization of wide area measurement information from the FNET system

Analysis of power system dynamics helps to understand the operation of a power system. Therefore, it is significant to design and develop advanced visualization tools to interpret frequency, voltage magnitude, and phase angle information so that it can be presented to the operators in an intuitive manner. On the basis of the measurement data collected by widely-distributed frequency disturbance recorders (FDRs), visualization tools have been implemented for the FNET system. A number of FNET visualization tools are discussed in this paper, including real-time visualization, animated event replay, visualization of oscillation mode analysis and visualization of propagation effects in two dimensional systems. These tools correlate the FDR measurements with their corresponding geographical information, and transform the combined matrices into different graphic formats using various computer techniques and programming languages. The graphics generated by these tools facilitate power system operation by allowing an operator to monitor power system dynamics, perform post-event analysis and identify modal oscillations more efficiently.