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

Forced Oscillation Source Location via Multivariate Time Series Classification

Precisely locating low-frequency oscillation sources is the prerequisite of suppressing sustained oscillation, which is an essential guarantee for the secure and stable operation of power grids. Using synchrophasor measurements, a machine learning method is proposed to locate the source of forced oscillation in power systems. Rotor angle and active power of each power plant are utilized to construct multivariate time series (MTS). Applying Mahalanobis distance metric and dynamic time warping, the distance between MTS with different phases or lengths can be appropriately measured. The obtained distance metric, representing characteristics during the transient phase of forced oscillation under different disturbance sources, is used for offline classifier training and online matching to locate the disturbance source. Simulation results using the four-machine two-area system and IEEE 39-bus system indicate that the proposed location method can identify the power system forced oscillation source online with high accuracy.Comment: 5 pages, 3 figures. Accepted by 2018 IEEE/PES Transmission and Distribution Conferenc

Location of low-frequency oscillation sources using improved D-S evidence theory

This paper presents a method for localizing oscillation sources based on data fusion Dempster–Shafer (D-S) evidence theory. This study is based on data of each bus from the system collected by phasor measurement units (PMUs). Then the D-S evidence theory algorithm is employed to establish the mass function and the trust degree of each bus. Three traditional methods are used to locate the oscillation source and to provide the calculation results for structuring the mass function of the algorithm. Finally, the decision of oscillation sources localization is made according to synthesis decision value. The higher the synthesis decision value, the higher the possibility is of an oscillation source. The WECC179 bus power system is applied for verification, and the D-S evidence theory method is compared with the above traditional three methods. It is proved that the algorithm can significantly improve the accuracy of locating sources of negatively damped oscillations and forced power oscillations, effectively reduce misjudgment. Meanwhile, this algorithm is also effective for the positioning complex dual oscillation sources.</p

Oscillation Analysis and its Mitigation Using Inverter-Based Resources in Large-Scale Power Grids

In today\u27s interconnected power grids, forced oscillations and poorly damped low-frequency oscillations are major concerns that can damage equipment, limit power transfer capability, and deteriorate power system stability. The first part of the dissertation focuses on the impact of a wide-area power oscillation damping (POD) controller via voltage source converter-based high voltage direct current (VSC-HVDC) in enhancing the power system stability and improving the damping of low-frequency oscillation. The POD controller\u27s performance was investigated under a three-phase temporary line fault. The Great Britain (G.B.) power grid model validated the POD controller performance via active power modulation of VSC-HVDC through TSAT-RTDS hybrid simulation. The developed POD controller is also implemented on a general-purpose hardware platform CompactRIO and tested on a hardware-in-the-loop (HIL) test setup with actual PMU devices and a communication network impairment simulator. A variety of real-world operating conditions is considered in the HIL tests, including measurement error/noise, occasional/consecutive data package losses, constant/random time delays, and multiple backups PMUs. The second part of the dissertation proposes a two‐dimensional scanning forced oscillation grid vulnerability analysis method to identify areas/zones and oscillation frequency in the system critical to forced oscillation. These critical areas/zones can be considered effective actuator locations to deploy forced oscillation damping controllers. Additionally, a POD controller through inverter-based resources (IBRs) is proposed to reduce the forced oscillation impact on the entire grid. The proposed method is tested when the external perturbation is active power and compared with the reactive power perturbation result. The proposed method is validated through a case study on the 2000-bus synthetic Texas power system model. The simulation results demonstrate that the critical areas/zones of forced oscillation are related to the areas that highly participate in the natural oscillation. Furthermore, forced oscillation through active power disturbance can have a more severe impact than reactive power disturbance, especially at resonance. The proposed forced oscillation controller can mitigate the impact of the forced oscillation on the entire system when the actuator is close to the forced oscillation source. In addition, active power modulation of IBR can provide better damping performance than reactive power modulation

An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

An Online Data-Driven Method to Locate Forced Oscillation Sources from Power Plants Based on Sparse Identification of Nonlinear Dynamics (SINDy)

Forced oscillations may jeopardize the secure operation of power systems. To mitigate forced oscillations, locating the sources is critical. In this paper, leveraging on Sparse Identification of Nonlinear Dynamics (SINDy), an online purely data-driven method to locate the forced oscillation is developed. Validations in all simulated cases (in the WECC 179-bus system) and actual oscillation events (in ISO New England system) in the IEEE Task Force test cases library are carried out, which demonstrate that the proposed algorithm, requiring no model information, can accurately locate sources in most cases, even under resonance condition and when the natural modes are poorly damped. The little tuning requirement and low computational cost make the proposed method viable for online application.Comment: ACCEPTED BY IEEE TRANSACTIONS ON POWER SYSTEMS FOR FUTURE PUBLICATIO

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