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

Co-design of Security Aware Power System Distribution Architecture as Cyber Physical System

The modern smart grid would involve deep integration between measurement nodes, communication systems, artificial intelligence, power electronics and distributed resources. On one hand, this type of integration can dramatically improve the grid performance and efficiency, but on the other, it can also introduce new types of vulnerabilities to the grid. To obtain the best performance, while minimizing the risk of vulnerabilities, the physical power system must be designed as a security aware system. In this dissertation, an interoperability and communication framework for microgrid control and Cyber Physical system enhancements is designed and implemented taking into account cyber and physical security aspects. The proposed data-centric interoperability layer provides a common data bus and a resilient control network for seamless integration of distributed energy resources. In addition, a synchronized measurement network and advanced metering infrastructure were developed to provide real-time monitoring for active distribution networks. A hybrid hardware/software testbed environment was developed to represent the smart grid as a cyber-physical system through hardware and software in the loop simulation methods. In addition it provides a flexible interface for remote integration and experimentation of attack scenarios. The work in this dissertation utilizes communication technologies to enhance the performance of the DC microgrids and distribution networks by extending the application of the GPS synchronization to the DC Networks. GPS synchronization allows the operation of distributed DC-DC converters as an interleaved converters system. Along with the GPS synchronization, carrier extraction synchronization technique was developed to improve the system’s security and reliability in the case of GPS signal spoofing or jamming. To improve the integration of the microgrid with the utility system, new synchronization and islanding detection algorithms were developed. The developed algorithms overcome the problem of SCADA and PMU based islanding detection methods such as communication failure and frequency stability. In addition, a real-time energy management system with online optimization was developed to manage the energy resources within the microgrid. The security and privacy were also addressed in both the cyber and physical levels. For the physical design, two techniques were developed to address the physical privacy issues by changing the current and electromagnetic signature. For the cyber level, a security mechanism for IEC 61850 GOOSE messages was developed to address the security shortcomings in the standard

TESTING OF RECURSIVE AND NON-RECURSIVE ALGORITHMS FOR REAL-TIME PHASOR AND FREQUENCY ESTIMATIONS IN POWER SYSTEMS

Steady-state performance of various recursive and non-recursive algorithms are tested in this report according to the test signals given in the IEEE Standard C37.118.1-2011. Phase magnitude and phase angle of the power grid signals have been estimated using Discrete Fourier Transform (non-recursive), Discrete Fourier Transform (recursive), Least Square, and Wavelet Transform Algorithms. Frequency estimation is performed using Discrete Fourier Transform, Weighted Least Square, and Zero Crossing methods. These algorithms are evaluated in LabView software and tested by generating test signals in a Simulink model. Furthermore, Total Vector Error (TVE) is calculated using dynamic test signals as per the IEEE Standard C37.118-2011. Performance of different algorithms are analyzed for various cases and the value of TVE is compared with the permissible error limits given in the standard

Studies of Uncertainties in Smart Grid: Wind Power Generation and Wide-Area Communication

This research work investigates the uncertainties in Smart Grid, with special focus on the uncertain wind power generation in wind energy conversion systems (WECSs) and the uncertain wide-area communication in wide-area measurement systems (WAMSs). For the uncertain wind power generation in WECSs, a new wind speed modeling method and an improved WECS control method are proposed, respectively. The modeling method considers the spatial and temporal distributions of wind speed disturbances and deploys a box uncertain set in wind speed models, which is more realistic for practicing engineers. The control method takes maximum power point tracking, wind speed forecasting, and wind turbine dynamics into account, and achieves a balance between power output maximization and operating cost minimization to further improve the overall efficiency of wind power generation. Specifically, through the proposed modeling and control methods, the wind power control problem is developed as a min-max optimal problem and efficiently solved with semi-definite programming. For the uncertain communication delay and communication loss (i.e. data loss) in WAMSs, the corresponding solutions are presented. First, the real-world communication delay is measured and analyzed, and the bounded modeling method for the communication delay is proposed for widearea applications and further applied for system-area and substation-area protection applications, respectively. The proposed bounded modeling method is expected to be an important tool in the planning, design, and operation of time-critical wide-area applications. Second, the real synchronization signal loss and synchrophasor data loss events are measured and analyzed. For the synchronization signal loss, the potential reasons and solutions are explored. For the synchrophasor data loss, a set of estimation methods are presented, including substitution, interpolation, and forecasting. The estimation methods aim to improve the accuracy and availability of WAMSs, and mitigate the effect of communication failure and data loss on wide-area applications

Ocean Bottom Seismometer: Design and Test of a Measurement System for Marine Seismology

The Ocean Bottom Seismometer (OBS) is a key instrument for the geophysical study of sea sub-bottom layers. At present, more reliable autonomous instruments capable of recording underwater for long periods of time and therefore handling large data storage are needed. This paper presents a new Ocean Bottom Seismometer designed to be used in long duration seismic surveys. Power consumption and noise level of the acquisition system are the key points to optimize the autonomy and the data quality. To achieve our goals, a new low power data logger with high resolution and Signal–to-Noise Ratio (SNR) based on Compact Flash memory card is designed to enable continuous data acquisition. The equipment represents the achievement of joint work from different scientific and technological disciplines as electronics, mechanics, acoustics, communications, information technology, marine geophysics, etc. This easy to handle and sophisticated equipment allows the recording of useful controlled source and passive seismic data, as well as other time varying data, with multiple applications in marine environment research. We have been working on a series of prototypes for ten years to improve many of the aspects that make the equipment easy to handle and useful to work in deep-water areas. Ocean Bottom Seismometers (OBS) have received growing attention from the geoscience community during the last forty years. OBS sensors recording motion of the ocean floor hold key information in order to study offshore seismicity and to explore the Earth’s crust. In a seismic survey, a series of OBSs are placed on the seabed of the area under study, where they record either natural seismic activity or acoustic signals generated by compressed air-guns on the ocean surface. The resulting data sets are subsequently used to model both the earthquake locations and the crustal structure

UAS Flight Path Planning and Collision Avoidance Based on Markov Decision Process

The growing interest and trend for deploying unmanned aircraft systems (UAS) in civil applications require robust traffic management approaches that can safely integrate the unmanned platforms into the airspace. Although there have been significant advances in autonomous navigation, especially in the ground vehicles domain, there are still challenges to address for navigation in a dynamic 3D environment that airspace presents. An integrated approach that facilitates semi-autonomous operations in dynamic environments and also allows for operators to stay in the loop for intervention may provide a workable and practical solution for safe UAS integration in the airspace. This thesis research proposes a new path planning method for UAS flying in a dynamic 3D environment shared by multiple aerial vehicles posing potential conflict risks. This capability is referred to as de-confliction in drone traffic management. It primarily targets applications such as UAM [1] where multiple flying manned and/or unmanned aircraft may be present. A new multi-staged algorithm is designed that combines AFP method and Harmonic functions with AKF and MDP for dynamic path planning. It starts with the prediction of aircraft traffic density in the area and then generates the UAS flight path in a way to minimize the risk of encounters and potential conflicts. Hardware-in-the-loop simulations of the algorithm in various scenarios are presented, with an RGB-D camera and Pixhawk Autopilot to track the target. Numerical simulations show satisfactory results in various scenarios for path planning that considerably reduces the risk of conflict with other static and dynamic obstacles. A comparison with the potential field is provided that illustrates the robust and fast of the MDP algorithm

Development and application of synchronized wide-area power grid measurement

Phasor measurement units (PMUs) provide an innovative technology for real-time monitoring of the operational state of entire power systems and significantly improve power grid dynamic observability. This dissertation focuses on development and application of synchronized power grid measurements. The contributions of this dissertation are as followed:First, a novel method for successive approximation register analog to digital converter control in PMUs is developed to compensate for the sampling time error caused by the division remainder between the desirable sampling rate and the oscillator frequency. A variable sampling interval control method is presented by interlacing two integers under a proposed criterion. The frequency of the onboard oscillator is monitored in using the PPS from GPS.Second, the prevalence of GPS signal loss (GSL) on PMUs is first investigated using real PMU data. The correlation between GSL and time, spatial location, solar activity are explored via comprehensive statistical analysis. Furthermore, the impact of GSL on phasor measurement accuracy has been studied via experiments. Several potential solutions to mitigate the impact of GSL on PMUs are discussed and compared.Third, PMU integrated the novel sensors are presented. First, two innovative designs for non-contact PMUs presented. Compared with conventional synchrophasors, non-contact PMUs are more flexible and have lower costs. Moreover, to address nonlinear issues in conventional CT and PT, an optical sensor is used for signal acquisition in PMU. This is the first time the utilization of an optical sensor in PMUs has ever been reported.Fourth, the development of power grid phasor measurement function on an Android based mobile device is developed. The proposed device has the advantages of flexibility, easy installation, lower cost, data visualization and built-in communication channels, compared with conventional PMUs.Fifth, an identification method combining a wavelet-based signature extraction and artificial neural network based machine learning, is presented to identify the location of unsourced measurements. Experiments at multiple geographic scales are performed to validate the effectiveness of the proposed method using ambient frequency measurements. Identification accuracy is presented and the factors that affect identification performance are discussed

Map Generation from Large Scale Incomplete and Inaccurate Data Labels

Accurately and globally mapping human infrastructure is an important and challenging task with applications in routing, regulation compliance monitoring, and natural disaster response management etc.. In this paper we present progress in developing an algorithmic pipeline and distributed compute system that automates the process of map creation using high resolution aerial images. Unlike previous studies, most of which use datasets that are available only in a few cities across the world, we utilizes publicly available imagery and map data, both of which cover the contiguous United States (CONUS). We approach the technical challenge of inaccurate and incomplete training data adopting state-of-the-art convolutional neural network architectures such as the U-Net and the CycleGAN to incrementally generate maps with increasingly more accurate and more complete labels of man-made infrastructure such as roads and houses. Since scaling the mapping task to CONUS calls for parallelization, we then adopted an asynchronous distributed stochastic parallel gradient descent training scheme to distribute the computational workload onto a cluster of GPUs with nearly linear speed-up.Comment: This paper is accepted by KDD 202

Synchrophasor Measurement Using Substation Intelligent Electronic Devices: Algorithms and Test Methodology

This dissertation studies the performance of synchrophasor measurement obtained using substation Intelligent Electronic Devices (IEDs) and proposes new algorithms and test methodology to improve and verify their performance when used in power system applications. To improve the dynamic performance when exposed to sinusoidal waveform distortions, such as modulation, frequency drift, abrupt change in magnitude, etc, an adaptive approach for accurately estimating phasors while eliminating the effect of various transient disturbances on voltages and currents is proposed. The algorithm pre-analyzes the waveform spanning the window of observation to identify and localize the discontinuities which affect the accuracy of phasor computation. A quadratic polynomial signal model is used to improve the accuracy of phasor estimates during power oscillations. Extensive experimental results demonstrate the advantages. This algorithm can also be used as reference algorithm for testing the performance of the devices extracting synchronized phasor measurements. A novel approach for estimating the phasor parameters, namely frequency, magnitude and angle in real time based on a newly constructed recursive wavelet transform is developed. This algorithm is capable of estimating the phasor parameters in a quarter cycle of an input signal. It features fast response and achieves high accuracy over a wide range of frequency deviations. The signal sampling rate and data window size can be selected to meet desirable application requirements, such as fast response, high accuracy and low computational burden. In addition, an approach for eliminating a decaying DC component, which has significant impact on estimating phasors, is proposed using recursive wavelet transform. This dissertation develops test methodology and tools for evaluating the conformance to standard-define performance for synchrophasor measurements. An interleaving technique applied on output phasors can equivalently increase the reporting rate and can precisely depict the transient behavior of a synchrophasor unit under the step input. A reference phasor estimator is developed and implemented. Various types of Phasor Measurement Units (PMUs) and PMU-enabled IEDs (Intelligent Electronic Devices) and time synchronization options have been tested against the standards using the proposed algorithm. Test results demonstrate the effectiveness and advantages

1992 NASA/ASEE Summer Faculty Fellowship Program

For the 28th consecutive year, a NASA/ASEE Summer Faculty Fellowship Program was conducted at the Marshall Space Flight Center (MSFC). The program was conducted by the University of Alabama and MSFC during the period June 1, 1992 through August 7, 1992. Operated under the auspices of the American Society for Engineering Education, the MSFC program, was well as those at other centers, was sponsored by the Office of Educational Affairs, NASA Headquarters, Washington, DC. The basic objectives of the programs, which are the 29th year of operation nationally, are (1) to further the professional knowledge of qualified engineering and science faculty members; (2) to stimulate and exchange ideas between participants and NASA; (3) to enrich and refresh the research and teaching activities of the participants' institutions; and (4) to contribute to the research objectives of the NASA centers