Situational awareness of coherency behavior of synchronous generators in a power system with utility-scale photovoltaics

It is important that control center operators be alerted to system disturbances, including where, when and what disturbance occurs, so that proper anticipatory actions can be promptly taken if necessary, avoiding oscillation spreads in the power network. In this paper, the wavelet multi-resolution analysis based method is proposed to identify power system disturbances. Energy of wavelet coefficients are used as a criterion to choose optimal wavelet function and decomposition scale, which are then used for obtaining the maximum wavelet coefficients by identifying the frequency signals from wide area measurement system (WAMS). The maximum wavelet coefficients are then selected to be the indicators for disturbance identifying. The detailed procedure and effectiveness of the proposed method is demonstrated by simulations of a 10-machine 39-bus system. Introduction The synchronized phasor measurement units (PMUs) are able to measure and record the rotor angle, the frequency, the magnitude and phase of voltage and current of power systems. The measured data are sent to the phasor data concentrator (PDC) through high speed internet. Accordingly, a wide area measurement system (WAMS) is constructed based on the PMUs, PDC and internet. Thereby, the operational condition of the power grid can be monitored continuously and the dynamics of the power system can be recorded[1]. One of the most important application of WAMS is using the data recorded by PMUs to identify disturbances in power systems, including fault diagnosis[2], power quality disturbance identifying[3] as well as power network disturbance identifying[4]. The power network disturbance identifying mainly focus on disturbances leading to serious accidents in power system, such as cutting machine, load shedding, etc. Wavelet transform (WT) is a powerful and systematic way of analyzing the abrupt-changing feature of signals, belonging to a type of time-frequency-domain analysis[5]. Using WT, the frequency features of the analyzed signal could be located in time domain. Thus, as a promising tool, WT deserves a thorough study when it is applied to WAMS-based disturbance analysis. In[6], for the first time, the WT was introduced to disturbance identification, detecting the time when disturbance occurred. In this paper, the theory of a wavelet-based power network disturbance identifying method is described. First, the WT-based multi-resolution analysis is introduced in Section 1. As the key part of the method, the theory of power network disturbance identifying method, based on WT, is described in Section 2. The case study is given in Section 3. The conclusion is discussed in Section 4. WT-Based Multi-Resolution Analysis (MRA) WT is a partial time-frequency-domain analysis method, the frequency and time window of which can be changed, obtaining both the time and frequency domain information at the same time. Using WT, signals can be decomposed into several sub-spaces in different resolutions, so that signals with different frequencies are displayed in the different sub-spaces, revealing their characteristics clearly. © 2016. The authors Published by Atlantis Press 1313 4th National Conference on Electrical, Electronics and Computer Engineering (NCEECE 2015)

The invention of Phasor Measurement Units (PMUs) produce synchronized phasor measurements with high resolution real time monitoring and control of power system in smart grids that make possible. PMUs are used in transmitting data to Phasor Data Concentrators (PDC) placed in control centers for monitoring purpose. A primary concern of system operators in control centers is maintaining safe and efficient operation of the power grid. This can be achieved by continuous monitoring of the PMU data that contains both normal and abnormal data. The normal data indicates the normal behavior of the grid whereas the abnormal data indicates fault or abnormal conditions in power grid. As a result, detecting anomalies/abnormal conditions in the fast flowing PMU data that reflects the status of the power system is critical. A novel methodology for detecting and categorizing abnormalities in streaming PMU data is presented in this paper. The proposed method consists of three modules namely, offline Gaussian Mixture Model (GMM), online GMM for identifying anomalies and clustering ensemble model for classifying the anomalies. The significant features of the proposed method are detecting anomalies while taking into account of multivariate nature of the PMU dataset, adapting to concept drift in the flowing PMU data without retraining the existing model unnecessarily and classifying the anomalies. The proposed model is implemented in Python and the testing results prove that the proposed model is well suited for detection and classification of anomalies on the fly.

Electricity grid operators often deal with various challenges to maintain the reliability of the electric power supply because of ever increasing interconnections and complexity of the modern power grid. Power System control centers are responsible for grid monitoring, demand forecasting and dispatching of power in a particular region under their jurisdiction. Lack of Situational Awareness in the control centers may prevent the grid operators from responding effectively to an incident and taking necessary corrective actions. It is essential for the system operators to get a clear idea of the Power System state. Proper coordination amongst the system operators of various control centers are essential for integrated operation of the grid. Therefore, in order to ensure the security of the Power System, adequate situational awareness needs to be maintained in the grid control center. This paper provides an overview of recent developments and the best practices followed in the Eastern Regional Control Center of India to enhance Situational Awareness amongst the system operators for efficient monitoring and control of the Eastern grid.

With the development of distributed clean energy, HVDC and FACTS, power electronic equipments such as SVC/STATCOM, China's power grid has developed into a large-scale complex power grid. The problem of subsynchronous oscillation (SSO) has become more and more prominent in the modern power system, and many SSO events have happened in China. Furthermore, the possibility of the ultra synchronous oscillation(USO) caused by the power electronic devices is also possible theoretically, but none of the existing measurement systems can offer any useful information about it. In addition, the low frequency signal, such as the DC signal at HVDC substation, and the high frequency signal, such as harmonic and interharmonic component, are not measured in typical wide area measurement system(WAMS). This paper is to introduce a novel wide area and broadband measurement system (WABMS), which is composed of advanced phasor measurement units(PMU), communication network and control center. Besides the function of synchrophasor measurement, this system can also synchronously measure the DC, harmonic and interharmonic signal, record the original waveform continuously, and send the synchronized information to the control center. WABMS is able to monitor the broadband signal from 0Hz to 3000Hz, and can be used for state supervisor of fundamental frequency, harmonic and interharmonic component. Especially, for the prominent SSO problem, this system can detect the SSO event and identify the SSO source.

Wide-area measurement -project was started by Fingrid, the Finnish transmission system owner and operator (TSO), back in 2006. Nowadays the system deploys 12 phasor measurement units (PMU) and a phasor data concentrator (PDC) with applications. PMU measurements are also streamed from and to wide-area measurement systems in Norway and Denmark. From the very beginning, Fingrid's focus of the Wide-area measurement system (WAMS) development has been on power oscillation monitoring, and Fingrid has actively worked for algorithm development. Although the original scope was to use WAMS as a monitoring tool in control center, during the project synchrophasor measurements have been successfully applied for various power system planning and analysis purposes. In addition to the WAMS, this paper presents also number of different applications of synchrophasor measurements in Finland. The practical experiences from different applications are described and the main projected challenges especially related to development of real-time stability monitoring applications suitable for Fingrid's purposes are discussed in detail.

Over the years, renewable energy has experienced great growth and attention. The renewable power plants are distributed over large geographical areas and the number of renewable power plants is exponentially increasing. These distributed energy sources may make power system complex and unstable. Further, monitoring and control by existing system such as supervisory control and data acquisition (SCADA) system is facing the limitation to capture power system dynamics. In order to combat these problems, phasor measurement units (PMUs) are installed at power plants and substations to implement wide area measurement system (WAMS). To get accurate, high sampling frequency and synchronized data from PMUs at distributed locations, the WAMS needs high speed and reliable communication network. The communication network plays an important role in WAMS because real-time synchrophasor data and control messages are transmitted through communication network. In this paper, we present a hierarchical communication network architecture for WAMS. The proposed communication network consists of three network levels: generation, substation, and control center. To evaluate the performance of the proposed network, communication network for WAMS is modeled and simulated through OPNET. The simulation results are validated by comparing with the results of numerical analysis. The network performance is evaluated in terms of network delay under various link bandwidth and background traffic.

This paper presents critical survey along with the novel concept of smart power flow controller with Phasor Measurement Units (PMUs) signals for stability enhancement of a large power system. Also, the current status of Wide Area Measurement Systems (WAMS) and developments in real time applications of synchrophasor technology in power system has been adequately addressed. It has been noticed that with the help of synchrophasor technology, the system operators are now able to not only monitor and understand the transient/dynamic behaviour of the power system in real time at the control centres but also take quick restoration measures which was not possible in conventional SCADA system. PMUs deployment has shown encouraging results in recent contingencies, by way of assisting system operator with relatively better visualization, for Indian system. Thus, visibility of the network state at milliseconds level has enhanced the security, reliability and stability of the power system. This paper provides understanding of PMUs application and some novel research concept.

Enhancements of power system security can be achieved by developing an online environment where control center operators have the capability to monitor in real time the power system dynamic behavior, recognize threats to its integrity, evaluate, and implement suitable control actions. The methodological approaches proposed here are respectively a spectral analysis based on wavelet transform and a response-based wide-area control for improving power system dynamic behavior on the transient timescale. The monitoring technique consists in processing real-time data coming from phasor measurement units by adopting an approach based on wavelet spectral analysis. The final result is a diagram that shows the amplitude of different modes usually associated to different phenomena (electromechanical modes, inter-area oscillations, etc.) and their related dampings. The methodology proposed for control assessment is based on the solution of a dynamic optimization problem whose basic variables are acquired through a wide-area measurement system.

Power grids are critical cyber-physical systems that employ advanced Information and Communication Technologies (ICTs), e.g., Wide Area Measurement Systems (WAMSs), to deliver the energy to end users reliably and efficiently. WAMSs are used to collect real-time data from Phasor Measurement Units (PMUs) to improve the operator's situational awareness, as well as to enhance real-time monitoring and control of power systems. The WAMS, however, is vulnerable to cyber-attacks due to the susceptibility of its components-such as PMUs and Phasor Data Concentrators (PDCs)-and the lack of embedded security mechanisms in its communication protocols. Some more-destructive cyber-attacks, such as malware injection, can propagate themselves into the components of a WAMS through the communication network. Thus, in such attacks, an attacker can compromise a larger number of components, resulting in more-severe consequences. Therefore, investigating the propagation of cyber-attacks in WAMSs and devising effective countermeasures for this problem are of paramount importance. On this basis, this paper initially develops a model to analyze cyber-attack propagation in WAMS. Then, the impacts of the attacker's capability and the network operator's defensive ability on attack propagation are investigated in detail. Such a study can elucidate the required security measures and defensive strategies to prevent the spread of cyber-attacks in WAMSs. Finally, a Learning-Based Framework (LBF) is developed to estimate the attacker's capability. The simulation results corroborate the effectiveness of the proposed LBF in estimating the attacker's capability.

Calamitous loss due to mal-operation of traditional backup protection system (i.e. third zone of distance protection relays) was the main cause of many cascaded trips in the system. Some defensive system are needed to trip such failures in the power system, so, this paper is based on novel wide area backup protection system using Phasor measurement units (PMU) as an alternate to the conventional distributed backup protection in substation. Synchronized Measurement technology is a key element and empower the wide area protection, control and monitoring system. Working of Phasor measurement unit is based on GPS system and it gives accurate verdicts. In this system, overall communication is done through optical fiber. And it is expected that wide area protection, control and monitoring (WAPCAM) system reduce the number of disastrous blackouts and improve the reliability and security of the power system. The new backup protection system is based on phasor measurement unit obtained from studies on five bus test system using Matlab Simulink.

Wide Area Measurement Systems (WAMS) are well known for enhancing situational awareness of the grid using IEEE C37.118 phasors from Phasor Measurement Units (PMUs). Recently introduced IEC 61850-90-5 Routable Sample Values (R-SV) have proven promising to communicate timestamped synchrophasors to the control center, fulfilling the purpose. In wide area protection and control schemes, the communication of synchrophasors to the control center is also followed by sending back a supervisory decision signal (based on synchrophasor data) to the physical devices in the field. Development of WAMS testbeds for implementation and assessment of such schemes have often been addressed only from IEEE C37.118 PMU phasors’ perspective alone. This paper presents a comprehensive cyber–physical WAMS testbed capable of real-time communication of synchrophasors using both IEEE C37.118 PMU phasors and IEC 61850-90-5 R-SV. It also facilitates status and feedback signal communication between the control center and substations using IEC 61850-90-5 Routable GOOSE (R-GOOSE). The developed testbed integrates a real-time digital simulator (RTDS), industry-standard hardware devices such as PMUs, Phasor Data Concentrator (PDC), IEDs, Global Positioning System (GPS) synchronization clock, network components, and software components such as IEC 61850 emulator tools. It can be used for end-to-end implementation of a myriad of wide area monitoring protection and control (WAMPAC) applications. It can further facilitate vulnerability analysis of WAMS components, analyze the impact of cyber-attacks on critical applications, and then test and validate various security solutions for cyber resiliency of WAMPAC applications.

Real time monitoring and control of a modern power system has achieved significant development since the incorporation of the phasor measurement unit (PMU). Due to the time-synchronized capabilities, PMU has increased the situational awareness (SA) in a wide area measurement system (WAMS). Operator SA depends on the data pertaining to the real-time health of the grid. This is measured by PMUs and is accessible for data analytics at the data monitoring station referred to as the phasor data concentrator (PDC). Availability of the communication system and communication delay are two of the decisive factors governing the operator SA. This paper presents a pragmatic metric to assess the operator SA and ensure optimal locations for the placement of PMUs, PDC, and the underlying communication infrastructure to increase the efficacy of operator SA. The uses of digital elevation model (DEM) data of the surface topography to determine the optimal locations for the placement of the PMU, and the microwave technology for communicating synchrophasor data is another important contribution carried out in this paper. The practical power grid system of Bihar in India is considered as a case study, and extensive simulation results and analysis are presented for validating the proposed methodology.

Poorly damped low frequency oscillations in power systems have led to system blackouts in the past. Power system stabilizers (PSSs) are installed to improve synchronous generator's oscillation damping capabilities. PSS parameter tuning by various traditional and new optimization methods are studied to ensure stable and secure operation of interconnected power systems with uncertainties. It is imperative to evaluate the tuned PSSs with the different methods to ensure continued security of a power system during operation. There is a lack of such situational awareness at electric utility control centers to assist system operators with the knowledge of synchronous generator's oscillation damping capabilities. Since the human brain responses to images and colors faster compared to text and numbers, it is desirable to develop advanced visualizations and avail them to system operators. These visualizations could utilize real-time data from phasor measurement units. This paper presents the development of a new tool for use in control centers for modal analysis visualization (MAV). Modal analysis is performed on oscillations exhibited by generators in a power system. The MAV enhances situational awareness at control centers by providing near real-time insight into generators' oscillation damping capabilities.

Human operators in today's control centers, such as air or road traffic control, need to monitor a plethora of information obtained from diverse sources. To support them in detecting critical situations within this information flood and taking timely actions, operators thus need adequate information fusion and decision support systems. Research efforts on such dedicated Situation Awareness (SAW) systems have concentrated on assisting the operator in managing the current situations. However, little focus has been so far on integratively supporting the different phases of knowledge management in SAW systems, which encompasses the acquisition, representation, validation, maintenance and reuse of knowledge gathered for and during the use of these systems, such as configuring and maintaining suitable situation templates and exploiting already assessed situations. If operators and domain experts are not supported in these tasks, however, this may discourage them from a successful adoption of such systems in real-world control center applications, as user studies revealed. Based on these, and the lessons learned from the application of our SAW system implementations BeAware! and CSI to the domain of road traffic control, we therefore propose a first step towards a tool suite fostering knowledge management in SAW systems, which stretches from the configuration phase of the system to its runtime maintenance in the light of evolving environments and user needs.

Indian power system is one of the largest synchronous interconnections in the world. The installed capacity of more than 390 GW caters to the daily energy requirement of more than 1.38 billion people of India. The widespread transmission network of more than 448 thousand circuit kilometers experience conditions of high and low voltages. In such a large power system, variation is generally observed across various nodes of the system. The variation in voltage is both diurnal as well as seasonal in nature. During real time system operations, sometimes it becomes very difficult to maintain the system voltages as per the grid standards. The Indian power system has also experienced two major grid disturbances on 30-07-2012 and 31-07-2012. One of the cause of disturbances was voltage instability. After this disturbance, system planners suggested to install Flexible AC Transmission Systems (FACTS) at strategic locations to avoid recurrence of such disturbances in future. FACTS help in better controllability of the system and also improves the power transfer capability of existing transmission system which enhances reliability and security of the system. Indian power system has various FACTS devices in operation across various locations in the grid. The FACTS devices in India comprise of SVC, STATCOM, FSC and TCSC. To ensure better monitoring of the FACTS devices, phasor measurement units (PMU) are being installed at the terminals of FACTS devices. This paper has discussed the performance of SVC and STATCOM during the steady state and dynamic state. After the performance assessment, the system operator can provide the most suitable settings of these devices. The control settings are adopted based on historical data and existing system conditions. The regular feedback helps in optimum utilization as well as better performance of FACTS devices. The assessment of SVC and STATCOM is done using the data made available at control centers by SCADA and Wide Area Measurement Systems (WAMS).