2,111 research outputs found

    Wide-area Situational Awareness Application Developments

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    This dissertation expands the topics from the wide-area situational awareness application development, system architecture design, to power system disturbance analysis. All the works are grounded on the wide-area Frequency Monitoring Network (FNET). The FNET system takes GPS-synchronized wide-area measurements in a low-cost, easily deployable manner at 120V single-phase power outlet. These synchronized observations enables the monitoring of bulk power systems, and provides critical information for understanding power system disturbances and system operations. Firstly, the work addresses the viability of angle measurement to serve different types of situational awareness applications, including the development of new angle-based event location estimation methods, the design of real-time system visualization framework using angle measurement. Secondly, a sound FNET power system event monitoring and automatic event reporting system framework is introduced, with NERC Frequency Response Initiative (FRI) tasks included to improve power system situational awareness capability. Lastly, the work covers different types of power system disturbance analysis, including the statistical analysis of frequency disturbances in NA power grid from 2008 to 2011; analysis of typical frequency response characteristics of the generation and load loss events in Europe power grid; analysis of some major disturbances in NA power grid from 2010 to 2011; and the inter-area oscillation modal analysis in the WECC system

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

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    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

    Wide-Area Synchrophasor Measurement Applications and Power System Dynamic Modeling

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    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

    Wide-Area Synchrophasor Data Server System and Data Analytics Platform

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    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

    Electromechanical Dynamics of High Photovoltaic Power Grids

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    This dissertation study focuses on the impact of high PV penetration on power grid electromechanical dynamics. Several major aspects of power grid electromechanical dynamics are studied under high PV penetration, including frequency response and control, inter-area oscillations, transient rotor angle stability and electromechanical wave propagation.To obtain dynamic models that can reasonably represent future power systems, Chapter One studies the co-optimization of generation and transmission with large-scale wind and solar. The stochastic nature of renewables is considered in the formulation of mixed-integer programming model. Chapter Two presents the development procedures of high PV model and investigates the impact of high PV penetration on frequency responses. Chapter Three studies the impact of PV penetration on inter-area oscillations of the U.S. Eastern Interconnection system. Chapter Four presents the impacts of high PV on other electromechanical dynamic issues, including transient rotor angle stability and electromechanical wave propagation. Chapter Five investigates the frequency response enhancement by conventional resources. Chapter Six explores system frequency response improvement through real power control of wind and PV. For improving situation awareness and frequency control, Chapter Seven studies disturbance location determination based on electromechanical wave propagation. In addition, a new method is developed to generate the electromechanical wave propagation speed map, which is useful to detect system inertia distribution change. Chapter Eight provides a review on power grid data architectures for monitoring and controlling power grids. Challenges and essential elements of data architecture are analyzed to identify various requirements for operating high-renewable power grids and a conceptual data architecture is proposed. Conclusions of this dissertation study are given in Chapter Nine

    EXTRACTION OF PICTORIAL ENERGY INFORMATION FROM CAMPUS UNMETERED BUILDINGS USING IMAGE PROCESSING TECHNIQUES

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    In recent years, advanced metering infrastructure (AMI) has been the main research focus due to the traditional power grid has been restricted to meet development requirements. There has been an ongoing effort to increase the number of AMI devices that provide real-time data readings to improve system observability. Deployed AMI across distribution secondary networks provides load and consumption information for individual households which can improve grid management. Significant upgrade costs associated with retrofitting existing meters with network-capable sensing can be made more economical by using image processing methods to extract usage information from images of the existing meters. This thesis presents a new solution that uses online data exchange of power consumption information to a cloud server without modifying the existing electromechanical analog meters. In this framework, application of a systematic approach to extract energy data from images replaces the manual reading process. One case study illustrates the digital imaging approach is compared to the averages determined by visual readings over a one-month period

    Data Mining and Machine Learning Applications of Wide-Area Measurement Data in Electric Power Systems

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    Wide-area measurement systems (WAMS) are quickly becoming an important part of modern power system operation. By utilizing the Global Positioning System, WAMS offer highly accurate time-synchronized measurements that can reveal previously unobtainable insights into the grid’s status. An example WAMS is the Frequency Monitoring Network (FNET), which utilizes a large number of Internet-connected low-cost Frequency Disturbance Recorders (FDRs) that are installed at the distribution level. The large amounts of data collected by FNET and other WAMS present unique opportunities for data mining and machine learning applications, yet these techniques have only recently been applied in this domain. The research presented here explores some additional applications that may prove useful once WAMS are fully integrated into the power system. Chapter 1 provides a brief overview of the FNET system that supplies the data used for this research. Chapter 2 reviews recent research efforts in the application of data mining and machine learning techniques to wide-area measurement data. In Chapter 3, patterns in frequency extrema in the Eastern and Western Interconnections are explored using cluster analysis. In Chapter 4, an artificial neural network (ANN)-based classifier is presented that can reliably distinguish between different types of power system disturbances based solely on their frequency signatures. Chapter 5 presents a technique for constructing electromechanical transient speed maps for large power systems using FNET data from previously detected events. Chapter 6 describes an object-oriented software framework useful for developing FNET data analysis applications. In the United States, recent environmental regulations will likely result in the removal of nearly 30 GW of oil and coal-fired generation from the grid, mostly in the Eastern Interconnection (EI). The effects of this transition on voltage stability and transmission line flows have previously not been studied from a system-wide perspective. Chapter 7 discusses the results of power flow studies designed to simulate the evolution of the EI over the next few years as traditional generation sources are replaced with greener ones such as natural gas and wind. Conclusions, a summary of the main contributions of this work, and a discussion of possible future research topics are given in Chapter 8

    Frequency Monitoring Network (FNET) Data Center Development and Data Analysis

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    Frequency Monitoring Network (FNET) is an Internet-based, wide-area phasor measurement system that collects power system data using Frequency Disturbance Recorders (FDRs) that are installed at the distribution level. The FNET data center enables the monitoring of bulk power systems, and provides wide-area situational awareness and disturbance analysis for understanding power system disturbances and system operations. Therefore, the data center plays a very critical role in the entire FNET system framework. In recent years, many potential challenges brought by the rapid expansion of the FNET system have underlined the importance of designing the next-generation FNET data center. More discussions about the motivation and guidelines to design the next-generation FNET data center will be presented in Chapter 2, along with a brief introduction of the new infrastructure composing of multiple data storage and application layers. A distributed alarming agent that communicates between real-time applications and near-real-time applications is discussed in detail. Chapter 3 proposes the data storage solutions for FNET time-series measurement data, configuration data and analysis records. Chapter 4 addresses the challenges of the real-time application development. The algorithm, configuration parameters and data processing procedures of the real-time event detection, oscillation detection, and islanding detection are presented in detail. Chapter 5 introduces the implementation of the FNET map-based web display using the measurement data feed provided by the openHistorian data publisher service. Besides contributing to the situation awareness applications, the researches presented here explore novel data analysis perspectives to investigate power grids’ behavior. Chapter 6 introduces a frequency distribution probability calculation method, applies this method to frequency measurement data from 2005-2013 collected by the FNET system, investigates the distribution probability of frequency data over North American and also worldwide power grids, and compares the distribution patterns during different years, seasons, days of a week and periods of a day. Chapter 7 presents a solution method to produce replay videos based on FDRs’ normalized voltage magnitude data and investigates the voltage magnitude pattern changes over the Eastern Interconnection (EI) during events and days by using historical FNET measurement data. Conclusions and possible future research topics are given in Chapter 8

    Inferring Power Grid Information with Power Line Communications: Review and Insights

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    High-frequency signals were widely studied in the last decade to identify grid and channel conditions in PLNs. PLMs operating on the grid's physical layer are capable of transmitting such signals to infer information about the grid. Hence, PLC is a suitable communication technology for SG applications, especially suited for grid monitoring and surveillance. In this paper, we provide several contributions: 1) a classification of PLC-based applications; 2) a taxonomy of the related methodologies; 3) a review of the literature in the area of PLC Grid Information Inference (GII); and, insights that can be leveraged to further advance the field. We found research contributions addressing PLMs for three main PLC-GII applications: topology inference, anomaly detection, and physical layer key generation. In addition, various PLC-GII measurement, processing, and analysis approaches were found to provide distinctive features in measurement resolution, computation complexity, and analysis accuracy. We utilize the outcome of our review to shed light on the current limitations of the research contributions and suggest future research directions in this field.Comment: IEEE Communication Surveys and Tutorials Journa
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