Techniques for determining hidden properties of large-scale power systems

The contributions in this dissertation are towards augmenting and enhancing the knowledge in power system equivalent modeling, and dynamic mode estimation. Work related to these respective topics is presented herein in two parts -- (i) Network Based Methods, and (ii) Measurement Based Methods. The first part focuses on the problem of creating limit preserving equivalents (LPEs). There is a push to develop LPEs for power system interconnections to be used in markets and reliability studies. The equivalents that exist for these interconnections do not capture thermal limits of equivalent lines, which results in their transmission limits being significantly different from the original interconnection limits. Assigning non-infinite and non-zero limits to equivalent lines is the niche of this work. This is done by considering an unloaded network, which is operating point independent. A solution method is developed and discussed, which is capable of assigning lower, best and upper estimates for equivalent line limits, and is proposed for use towards developing LPEs. In the second part, a relatively new method for simultaneous modal analysis of multiple time-series signals is presented. Here, Dynamic Mode Decomposition (DMD) is successfully applied towards transmission-level power system measurements in an implementation that is able to run in real-time. Since power systems are considered as non-linear and time-varying, on-line modal identification is capable of monitoring the evolution of large-scale power system dynamics by providing a breakdown of the constituent oscillation frequencies and damping ratios, and their respective amplitudes. The outputs provided by DMD can enable on-line spatio-temporal analyses, improve situational awareness, and could even contribute towards control strategies. This work presents the theory of DMD, followed by results and visualization. It shows that using frequency and voltage data together helps with precision, while maintaining fast calculation speeds. The key advantage of this implementation is its relatively fast computation; for example, it is able to process each time-window, consisting of 3392 signals with 211 time points, in 0.185 s. Modal content alarm processing, and efficient wide-area modal visualization are two proposed on-line applications. The desire to reduce model-dependency has driven measurement-based modal identification methods, as an alternative to analyzing linearized system models. Using this relatively fast DMD algorithm, this work also presents an interactive modal-identification tool for spatio-temporal analysis of measurement data. The tool can automatically scan through measurements, and display the values of oscillation frequency and damping ratio, as well as reconstruct signals. The use of this tool, its options, and visualization capabilities are illustrated using simulated measurements from an interconnected power grid. DMD being a data-driven modeling technique is able to handle large data sets and has shown fast computation times. The by-products of DMD provide an understanding of the wide-area spatio-temporal structures in power systems. Studies based on a large-scale model of an interconnected power grid are presented, along with visualizations that elucidate the spatial structure of wide-area dynamics, and their dependency on operating points

Data Analytics and Wide-Area Visualization Associated with Power Systems Using Phasor Measurements

As power system research becomes more data-driven, this study presents a framework for the analysis and visualization of phasor measurement unit (PMU) data obtained from large, interconnected systems. The proposed framework has been implemented in three steps: (a) large-scale, synthetic PMU data generation: conducted to generate research-based measurements with the inclusion of features associated with industry-grade PMU data; (b) error and event detection: conducted to assess risk levels and data accuracy of phasor measurements, and furthermore search for system events or disturbances; (c) oscillation mode visualization: conducted to present wide-area, modal information associated with large-scale power grids. To address the challenges due to real data confidentiality, the creation of realistic, synthetic PMU measurements is proposed for research use. First, data error propagation models are generated after a study of some of the issues associated with the unique time-synchronization feature of PMUs. An analysis of some of the features of real PMU data is performed to extract some of the statistics associated with data errors. Afterwards, an approach which leverages on existing, large-scale, synthetic networks to model the constantly-changing dynamics often observed in real measurements is used to generate an initial synthetic dataset. Further inclusion of PMU-related data anomalies ensures the production of realistic, synthetic measurements fit for research purposes. An application of different techniques based on a moving-window approach is suggested for use in the detection of events in real and synthetic PMU measurements. These fast methods rely on smaller time-windows to assess fewer measurement samples for events, classify disturbances into global or local events, and detect unreliable measurement sources. For large-scale power grids with complex dynamics, a distributed error analysis is proposed for the isolation of local dynamics prior any reliability assessment of PMU-obtained measurements. Finally, fundamental system dynamics which are inherent in complex, interconnected power systems are made apparent through a wide-area visualization of large-scale, electric grid oscillation modes. The approach ensures a holistic interpretation of modal information given that large amounts of modal data are often generated in these complex systems irrespective of the technique that is used

Analysis of Reinforced Concrete Buildings Using Multipath Lidar

International audienceThis paper compares the modal analysis of reinforced-concrete buildings obtained using sensitive velocimeters and coherent LIDAR. Ambient vibrations are recorded by these two systems and processing using operative modal analysis method for getting building frequency and mode shapes. Real-scale trials applied to five buildings located at Grenoble (France) are presented. The efficiency and reliability of the Lidar is discussed and the modal parameters measured by Lidar at a range of 200m and by in-situ velocimeters are compared. The results are in good agreement and allow us to conclude on the ability of the coherent Lidar to assess modal parameters of existing buildings at long range and without any retroreflectors placed on the structures. The results open new perspectives for remotely testing buildings, without getting inside, facilitating dynamic analysis of buildings for earthquake engineering applications

Operational modal analysis and continuous dynamic monitoring of footbridges

Tese de doutoramento. Engenharia Civil. Universidade do Porto. Faculdade de Engenharia. 201

Health monitoring of civil infrastructures by subspace system identification method: an overview

Structural health monitoring (SHM) is the main contributor of the future's smart city to deal with the need for safety, lower maintenance costs, and reliable condition assessment of structures. Among the algorithms used for SHM to identify the system parameters of structures, subspace system identification (SSI) is a reliable method in the time-domain that takes advantages of using extended observability matrices. Considerable numbers of studies have specifically concentrated on practical applications of SSI in recent years. To the best of author's knowledge, no study has been undertaken to review and investigate the application of SSI in the monitoring of civil engineering structures. This paper aims to review studies that have used the SSI algorithm for the damage identification and modal analysis of structures. The fundamental focus is on data-driven and covariance-driven SSI algorithms. In this review, we consider the subspace algorithm to resolve the problem of a real-world application for SHM. With regard to performance, a comparison between SSI and other methods is provided in order to investigate its advantages and disadvantages. The applied methods of SHM in civil engineering structures are categorized into three classes, from simple one-dimensional (1D) to very complex structures, and the detectability of the SSI for different damage scenarios are reported. Finally, the available software incorporating SSI as their system identification technique are investigated

Load Estimation, Structural Identification and Human Comfort Assessment of Flexible Structures

Stadiums, pedestrian bridges, dance floors, and concert halls are distinct from other civil engineering structures due to several challenges in their design and dynamic behavior. These challenges originate from the flexible inherent nature of these structures coupled with human interactions in the form of loading. The investigations in past literature on this topic clearly state that the design of flexible structures can be improved with better load modeling strategies acquired with reliable load quantification, a deeper understanding of structural response, generation of simple and efficient human-structure interaction models and new measurement and assessment criteria for acceptable vibration levels. In contribution to these possible improvements, this dissertation taps into three specific areas: the load quantification of lively individuals or crowds, the structural identification under non-stationary and narrowband disturbances and the measurement of excessive vibration levels for human comfort. For load quantification, a computer vision based approach capable of tracking both individual and crowd motion is used. For structural identification, a noise-assisted Multivariate Empirical Mode Decomposition (MEMD) algorithm is incorporated into the operational modal analysis. The measurement of excessive vibration levels and the assessment of human comfort are accomplished through computer vision based human and object tracking, which provides a more convenient means for measurement and computation. All the proposed methods are tested in the laboratory environment utilizing a grandstand simulator and in the field on a pedestrian bridge and on a football stadium. Findings and interpretations from the experimental results are presented. The dissertation is concluded by highlighting the critical findings and the possible future work that may be conducted