Power System Frequency Measurement Based Data Analytics and Situational Awareness

This dissertation presents several measurement-based research from power system wide-area dynamics data analytics to real-time situational awareness application development. All the research are grounded on the power system phasor measurements provided by wide-area Frequency Monitoring Network (FNET/GridEye), which collects the Global Positioning System (GPS) signal synchronized power system phasor measurements at distribution networks. The synchronized frequency measurement at FNET/GridEye enables real-time monitoring of bulk power systems (BPSs) and allows the dynamics interpretation of power system disturbances. Research on both the dynamic and ambient frequency measurements are conducted in this dissertation.The dynamics refer to the frequency measurement when the system is experiencing sudden contingencies. This dissertation focuses on two types of contingency: generation trip and oscillation and conducts both data analytics and corresponding real-time applications. Historical generation trip events in North America are analyzed in purpose to develop a frequency measurement based indicator of power systems low inertia events. Then the frequency response study is extended to bulk power systems worldwide to derive its association with system capacity size. As an essential parameter involved in the frequency response, the magnitude of the power imbalances is estimated based on multiple linear regression for improved accuracy. With respect to situational awareness, a real-time FNET/GridEye generation trip detection tool is developed for PMU use at power utilities and ISOs, which overcomes several challenges brought by different data situations.Regarding the oscillation dynamics, statistical analysis is accomplished on power system inter-area oscillations demonstrating the yearly trend of low-frequency oscillations and the association with system load. A novel real-time application is developed to detect power systems sustained oscillation in large area. The application would significantly facilitate the power grid situational awareness enhancement and system resiliency improvement.Furthermore, an additional project is executed on the ambient frequency measurement at FNET/GridEye. This project discloses the correlation between power system frequency and the electric clock time drift. In practice, this technique serves to track the time drifts in traffic signal systems

Wide-Area Synchrophasor Data Server System and Data Analytics Platform

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 (WAMS). The Frequency Monitoring Network (FNET/GridEye) is a WAMS network that collects data from hundreds of Frequency Disturbance Recorders (FDRs) 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 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. Multiple power system disturbance detection and analysis applications are redesigned to take advantage of this platform. Data quality and data security are monitored in real-time. Future data analytics applications can be easily developed and plugged into the system with simple configuration

Application of Advanced Early Warning Systems with Adaptive Protection

This project developed and field-tested two methods of Adaptive Protection systems utilizing synchrophasor data. One method detects conditions of system stress that can lead to unintended relay operation, and initiates a supervisory signal to modify relay response in real time to avoid false trips. The second method detects the possibility of false trips of impedance relays as stable system swings “encroach” on the relays’ impedance zones, and produces an early warning so that relay engineers can re-evaluate relay settings. In addition, real-time synchrophasor data produced by this project was used to develop advanced visualization techniques for display of synchrophasor data to utility operators and engineers

Novel performance evaluation of information and communication technologies to enable wide area monitoring systems for enhanced transmission network operation

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.The penetration of renewable energy sources has increased significantly in recent years due to the ongoing depletion of conventional resources and the transition to a low carbon energy system. Renewable energy sources such as wind energy are highly intermittent and unpredictable in nature, which makes the operation of the power grid more dynamic and therefore more complex. In order to operate the power system reliably under such conditions, Phasor Measurement Units (PMUs) through the use of satellite technology can offer a state-of-the-art Wide Area Monitoring System (WAMS) for improving power system monitoring, control and protection. They can improve the operation by providing highly precise and synchronised measurements near to real-time with higher frequency and accuracy. In order to achieve such objectives, a high-speed and reliable communications infrastructure is required to transfer time-critical PMU data from remote locations to the control centre. The signals measured by PMUs are transmitted across Local and Wide Area Networks, where they may encounter excessive delays. Signal delays can have a disruptive effect and make applications at best inefficient and at worse ineffective. The main research contribution of this thesis is the performance evaluation of communication infrastructures for WAMS. The evaluation begins from inside substations and continues over wide areas from substations to control centre. Through laboratory-based investigations and simulations, the performance of communications infrastructure in a typical power system substation has been analysed. In addition, the performance evaluation of WAMS communications infrastructure has been presented. In the modelling and analysis, an existing WAMS as installed on the GB transmission system has been considered. The actual PMU packets as received at the Phasor Data Concentrator (PDC) were captured for latency analysis. A novel algorithmic procedure has been developed and implemented to automate the large-scale latency calculations. Furthermore, the internal delays of PMUs have been investigated, determined and analysed. Subsequently, the WAMS has been simulated and detailed comparisons have been performed between the simulated model results and WAMS performance data captured from the actual WAMS. The validated WAMS model has been used for analysing possible future developments as well as to test newly proposed mechanisms, protocols, etc. in order to improve the communications infrastructure performance

Big data analytics on PMU measurements

Phasor Measurement Units (PMUs) are being rapidly deployed in power grids due to their high sampling rates. PMUs offer a more current and accurate visibility of the power grids than traditional SCADA systems. However, the high sampling rates of PMUs bring in two major challenges that need to be addressed to fully benefit from these PMU measurements. On one hand, any transient events captured in the PMU measurements can negatively impact the performance of steady state analysis. On the other hand, processing the high volumes of PMU data in a timely manner poses another challenge in computation. This paper presents PDFA, a parallel detrended fluctuation analysis approach for fast detection of transient events on massive PMU measurements utilizing a computer cluster. The performance of PDFA is evaluated from the aspects of speedup, scalability and accuracy in comparison with the standalone DFA approach

Wide-Area Synchrophasor Measurement Applications and Power System Dynamic Modeling

The use of synchrophasor measurements system-wide has been providing significant assistance for grid dynamic monitoring, situation awareness and reliability improvement. Frequency Monitoring Network (FNET), as an academia-run synchrophasor measurement system, utilizes a large number of Internet-connected low-cost Frequency Disturbance Recorders (FDRs) installed at the distribution level to measure power system dynamics and provide both online and off-line applications, such as event detection, oscillation modes estimation, event replay, etc. This work aims to further explore applications of the FNET measurements and utilize measurement-based method in dynamic modeling. Measurement-based dynamic reduction is an important application of synchrophasor measurement, especially considering the fact that when the system model is large, measurements provide a precise insight of system dynamics in order to determine equivalent regions. Another important application is to investigate Super Bowl games as an example to evaluate the influence of synchronized human activities on the power system. Featured characteristics drawn from the frequency data detected during the Super Bowl games are discussed. Increased penetration levels of wind generation and retirements of conventional plants have caused concerns about a decline of system inertia and primary frequency response. This work evaluates the impact of wind power on the system inertial response, simulation scenarios with different wind penetration levels are developed based on the U.S. Northeast Power Coordinating Council (NPCC) system. A user-defined electrical control model is also introduced to provide inertia and governor control to wind generations. Except for wind generation, frequency regulation can also be achieved by supplementary control of High Voltage Direct Current (HVDC) transmission line. A multi-terminal Voltage Source Converter (VSC) HVDC model is constructed to prove the effective control. In order to transmit large amount of intermittent and remote renewable energy over long distance to load centers, a potential solution is to upgrade the transmission system at a higher voltage by constructing an overlay HVDC grid on top of the original transmission system. The VSC HVDC model is utilized to build the HVDC overlay grid, and the overlay grid is tested with interconnection models. Conclusions and possible future research topics are given in the end

Exploiting phasor measurement units for enhanced transmission network operation and control

This thesis was submitted for the degree of Doctor of Engineering and awarded by Brunel UniversityIn order to achieve binding Government targets towards the decarbonisation of the electricity network, the GB power system is undergoing an unprecedented amount of change. A series of new technologies designed to integrate massive volumes of renewable generation, predominantly in the form of offshore wind, asynchronously connecting to the periphery of the transmission system, are transforming the requirements of the network. This displacement of traditional thermal generation is leading to a significant reduction in system inertia, thus making the task of system operation more challenging. It is therefore deemed necessary to develop tools and technologies that provide far greater insight into the state of the power system in real-time and give rise to methods for improving offline modelling practices through an enhanced understanding of the systems performance. To that extent PMUs are seen as one of the key enablers of the Smart Grid, providing accurate time-synchronised measurements on the state of the power system, allowing the true dynamics of the power system to be captured and analysed. This thesis provides an analysis of the existing PMU deployment on the GB transmission system with a view to the future system monitoring requirements. A critical evaluation and comparison is also provided on the suitability of a University based Low Voltage PMU network to further enhance the visibility of the GB system. In addition a novel event detection algorithm based on Detrended Fluctuation Analysis is developed and demonstrated, designed to determine the exact start time of a transmission event, as well as the suitability of such an event for additional transmission system analysis, namely inertia estimation. Finally, a reliable method for the estimation of total system inertia is proposed that includes an estimate of the contribution from residual sources, of which there is currently no visibility. The proposed method identifies the importance of regional inertia and its impact to the operation of the GB transmission system.Engineering and Physical Sciences Research Council (EPSRC) and National Grid

A Cyber-Physical Anomaly Detection for Wide-Area Protection using Machine Learning

Wide-area protection scheme (WAPS) provides system-wide protection by detecting and mitigating small and large-scale disturbances that are difficult to resolve using local protection schemes. As this protection scheme is evolving from a substation-based distributed remedial action scheme (DRAS) to the control center-based centralized RAS (CRAS), it presents severe challenges to their cybersecurity because of its heavy reliance on an insecure grid communication, and its compromise would lead to system failure. This paper presents an architecture and methodology for developing a cyber-physical anomaly detection system (CPADS) that utilizes synchrophasor measurements and properties of network packets to detect data integrity and communication failure attacks on measurement and control signals in CRAS. The proposed machine leaning-based methodology applies a rules-based approach to select relevant input features, utilizes variational mode decomposition (VMD) and decision tree (DT) algorithms to develop multiple classification models, and performs final event identification using a rules-based decision logic. We have evaluated the proposed methodology of CPADS using the IEEE 39 bus system for several performance measures (accuracy, recall, precision, and F-measure) in a cyber-physical testbed environment. Our experimental results reveal that the proposed algorithm (VMD-DT) of CPADS outperforms the existing machine learning classifiers during noisy and noise-free measurements while incurring an acceptable processing overhead

Virtual Synchronous Generator Operation of Full Converter Wind Turbine ‒ Control and Testing in a Hardware Based Emulation Platform

Wind is one of the most promising renewable energy forms that can be harvested to into the electrical power system. The installation has been rising worldwide in the past and will continue to steadily increase. The high penetration of wind energy has bought about a number of difficulties to the power system operation due to its stochastic nature, lack of exhibited inertia, and differing responses to the traditional energy sources in grid disturbances. Various grid support functions are then proposed to resolve the issues. One solution is to allow the renewable energy sources to behave like a traditional synchronous generator in the system, as a virtual synchronous generator (VSG). On the other hand, testing the control of the future power grid with high penetration renewable often relies on digital simulation or hardware-based experiments. But they either suffer from fidelity and numerical stability issues, or are bulky and inflexible. A power electronics based power system emulation platform is built in the University of Tennessee. This Hardware Testbed (HTB) allows testing of both system level and component level controls, with a good balance between the fidelity of the hardware-based testing platform, and the coverage of the digital simulation.This dissertation proposal investigates the VSG operation of the full converter wind turbine (FCWT), focusing on its control and testing in the HTB. Specifically, a FCWT emulator was developed using a single converter to include its physical model and control strategies. The existing grid support functions are also included to demonstrate their feasibility.The comprehensive VSG controls are then proposed for a FCWT with short term energy storage. The dynamic response of the FCWT can be comparable to the traditional generation during grid disturbance. The control can also allow the FCWT to be dispatched by the system operator, and even operate stand-alone without other grid sources.To study the system response under faults, a short circuit fault emulator was developed in the HTB platform. Four basic types of the short circuit faults with various fault impedance can be emulated using the emulator. The power system transient stability in terms of critical clearing time can be measured using the developed fault emulator

Performance Improvement of Wide-Area-Monitoring-System (WAMS) and Applications Development

Wide area monitoring system (WAMS), as an application of situation awareness, provides essential information for power system monitoring, planning, operation, and control. To fully utilize WAMS in smart grid, it is important to investigate and improve its performance, and develop advanced applications based on the data from WAMS. In this dissertation, the work on improving the WAMS performance and developing advanced applications are introduced.To improve the performance of WAMS, the work includes investigation of the impacts of measurement error and the requirements of system based on WAMS, and the solutions. PMU is one of the main sensors for WAMS. The phasor and frequency estimation algorithms implemented highly influence the performance of PMUs, and therefore the WAMS. The algorithms of PMUs are reviewed in Chapter 2. To understand how the errors impact WAMS application, different applications are investigated in Chapter 3, and their requirements of accuracy are given. In chapter 4, the error model of PMUs are developed, regarding different parameters of input signals and PMU operation conditions. The factors influence of accuracy of PMUs are analyzed in Chapter 5, including both internal and external error sources. Specifically, the impacts of increase renewables are analyzed. Based on the analysis above, a novel PMU is developed in Chapter 6, including algorithm and realization. This PMU is able to provide high accurate and fast responding measurements during both steady and dynamic state. It is potential to improve the performance of WAMS. To improve the interoperability, the C37.118.2 based data communication protocol is curtailed and realized for single-phase distribution-level PMUs, which are presented in Chapter 7.WAMS-based applications are developed and introduced in Chapter 8-10. The first application is to use the spatial and temporal characterization of power system frequency for data authentication, location estimation and the detection of cyber-attack. The second application is to detect the GPS attack on the synchronized time interval. The third application is to detect the geomagnetically induced currents (GIC) resulted from GMD and EMP-E3. These applications, benefited from the novel PMU proposed in Chapter 6, can be used to enhance the security and robust of power system