Yong Liu

Application of wide area measurement systems to islanding detection of bulk power systems

A fast islanding detection tool can help power dispatchers monitor and control power system operations. Frequency monitoring network (FNET) is a low cost and quickly deployable wide-area phasor measurement system at the distribution system level. The frequency disturbance recorder (FDR) in FNET is actually a single-phase phasor measurement unit (PMU) installed at ordinary 120 V outlets in the sense that it measures the voltage phase angle, amplitude, and frequency from a single-phase voltage source. Based on the data collected by the FDRs deployed in the North American power grid, two islanding detection methods, the frequency difference method and the change of angle difference method, are proposed. The nine real cases recorded, including islanding cases, generation trip cases, load shedding cases and oscillation cases, are presented to verify the proposed methods of islanding detection. Sensitivity analysis on the thresholds of the frequency deviation and angle deviation is done based on the real measurement data for obtaining the insensitive interval of two thresholds. The results show that the proposed methods can correctly detect power system islanding, and will not be falsely triggered by generation trips, load shedding and system oscillations.

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.

Frequency Regulation and Oscillation Damping Contributions of Variable-Speed Wind Generators in the U.S. Eastern Interconnection (EI)

The U.S. Eastern Interconnection (EI) is one of the largest electric power grids in the world and is expected to have difficulties in dealing with frequency regulation and oscillation damping issues caused by the increasing wind power. On the other side, variable-speed wind generators can actively engage in frequency regulation or oscillation damping with supplementary control loops. This paper creates a 5% wind power penetration simulation scenario based on the 16 000-bus EI system dynamic model and developed the user-defined wind electrical control model in PSSE that incorporates additional frequency regulation and oscillation damping control loops. The potential contributions of variable-speed wind generations to the EI system frequency regulation and oscillation damping are evaluated and simulation results demonstrate that current and future penetrations of wind power are promising in the EI system frequency regulation and oscillation damping.

Design and Implementation of a Real-Time Off-Grid Operation Detection Tool from a Wide-Area Measurements Perspective

Real-time situational awareness tools are of critical importance to power system operators, especially during emergencies. The availability of electric power has become a linchpin of most post-disaster response efforts, because public and private sector services depend upon it. Knowledge of the scope and extent of facilities impacted, as well as the duration of their dependence on backup power, enables emergency response officials to plan for contingencies and provide a better overall response. Based on the measurement data acquired by the frequency disturbance recorders deployed in the North American power grids, an off-grid detection method is proposed and implemented. This method monitors the critical electrical loads and detects the transition of these loads from an on-grid operation to an off-grid operation, during which the loads are fed by an uninterrupted power supply or a backup generation system. The details of the detection algorithm are presented, and some case studies and off-grid detection scenarios are also provided to verify the effectiveness and robustness. This paper also presents the real-time implementation of this method and several effectively detected off-grid situations. Moreover, two visualization tools are developed to display the real-time system operation condition in an intuitive manor.

ARMAX-Based Transfer Function Model Identification Using Wide-Area Measurement for Adaptive and Coordinated Damping Control

One of the main drawbacks of the existing oscillation damping controllers that are designed based on offline dynamic models is adaptivity to the power system operating condition. With the increasing availability of wide-area measurements and the rapid development of system identification techniques, it is possible to identify a measurement-based transfer function model online that can be used to tune the oscillation damping controller. Such a model could capture all dominant oscillation modes for adaptive and coordinated oscillation damping control. This paper describes a comprehensive approach to identify a low-order transfer function model of a power system using a multi-input multi-output (MIMO) autoregressive moving average exogenous (ARMAX) model. This methodology consists of five steps: 1) input selection; 2) output selection; 3) identification trigger; 4) model estimation; and 5) model validation. The proposed method is validated by using ambient data and ring-down data in the 16-machine 68-bus Northeast Power Coordinating Council system. The results demonstrate that the measurement-based model using MIMO ARMAX can capture all the dominant oscillation modes. Compared with the MIMO subspace state space model, the MIMO ARMAX model has equivalent accuracy but lower order and improved computational efficiency. The proposed model can be applied for adaptive and coordinated oscillation damping control.

Distributed Data Analytics Platform for Wide-Area Synchrophasor Measurement Systems

As synchrophasor data start to play a significant role in power system operation and dynamic study, data processing and data analysis capability are critical to wide-area measurement systems (WAMSs). The frequency monitoring network (FNET/GridEye) is a WAMS network that collects data from hundreds of frequency disturbance recorders at the distribution level. The previous FNET/GridEye data center is limited by its data storage capability and computation power. Targeting scalability, extensibility, concurrency, and robustness, a distributed data analytics platform is proposed in this paper to process large volume, high velocity dataset. A variety of real-time and non-real-time synchrophasor data analytics applications are hosted by this platform. The computation load is shared with balance by multiple nodes of the analytics cluster, and big data analytics tools such as Apache Spark are adopted to manage large volume data and to boost the data processing speed. Future data analytics applications can be easily developed and plugged into the system with simple configuration.

Dynamic Single-Phase Synchronized Phase and Frequency Estimation at the Distribution Level

This paper proposes a method for estimating synchronized phase and frequency at the distribution level under both steady-state and dynamic conditions. The discrete Fourier transform-based method is widely used for phasor and frequency estimation, thanks to its low computational burden. However, errors arise when the power system is operating at off-nominal frequency, especially under dynamic conditions such as phase modulation. Additionally, the power grid signal at the distribution level contains more noise and harmonics, which cause phase and frequency estimation errors. In this paper, a synchronized phase and frequency estimation algorithm suitable for measurement at the distribution level is proposed and tested under noise and harmonic conditions, as well as various conditions in the phasor measurement unit Standard (C37.118.1-2011 and C37.118.1a-2014), to verify its measurement accuracy at the distribution level.

Impact of GPS Signal Loss and Its Mitigation in Power System Synchronized Measurement Devices

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.

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.

Universal Grid Analyzer design and development

This paper promotes a better understanding of the power grid quality and dynamics through the introduction of a newly developed Universal Grid Analyzer (UGA). The UGA is a real-time, highly accurate, and GPS synchronized power grid monitoring device used at distribution level. They can function as a power quality analyzer by performing harmonics measurement along with voltage sag and swell detection. They can also be used as a phasor measurement unit (PMU) at distribution level. Accurate synchronous sampling is challenging and it is the hardware core of PMUs, thus a new synchronous sampling method is proposed to achieve accurate synchronous sampling. More importantly, the UGA can analyze power grid signal in a wide-frequency range through the “noise analysis” function, and analyze true synchrophasor measurement errors when the UGA is connected to the power grid. A prototype UGA is built to evaluate functions and measurement accuracy of the UGA.