Forced Oscillation Source Research Articles

Forced Oscillation Source Location in Power Systems Using MVMD-Assisted DEF in TF Plane

Forced Oscillation Source Location in Power Systems Using MVMD-Assisted DEF in TF Plane

Locating the source of forced oscillations on the basis of Lyapunov modal analysis

Based on the recently proposed Lyapunov modal analysis framework, this study proposes a method for locating the source of forced oscillation in power system when its frequency is close to the natural oscillation of the system. This method combines the selective modal analysis and spectral decomposition of Lyapunov functions, which characterize the energy of voltage perturbation. The proposed modal indicators characterize the energy of voltage disturbances accumulated from the forced oscillation in the nodes. Based on the corresponding spectral decomposition, the part corresponding to the resonance between the forced oscillation and the natural oscillation is subtracted from this energy. “Non-resonant” part of the index calculated in each node of the network allows visualizing the profile of “non-resonant” energy on the power grid graph. Based on the obtained profile it is possible to solve the inverse problem and determine the location of the source of forced oscillations. In a test experiment with IEEE 68 bus system, forced oscillations at a frequency close to the system’s natural oscillation were introduced in different nodes of the system. Profiles of the “non-resonant” part of the energy are obtained on the network graph, from which the location of the source of the forced oscillation can be determined. The profile of the proposed modal indicator on the network graph can be obtained either from a known model of the system or from the measured data.

Forced Oscillation Source Location of Bulk Power Systems Using Synchrosqueezing Wavelet Transform

Forced Oscillation Source Location of Bulk Power Systems Using Synchrosqueezing Wavelet Transform

Confidence Assessment for Regional Forced Oscillation Source Localization: Formulation and Field Validation

Confidence Assessment for Regional Forced Oscillation Source Localization: Formulation and Field Validation

Higher-order motif-based time series classification for forced oscillation source location in power grids

Higher-order motif-based time series classification for forced oscillation source location in power grids

Locating the Source of Forced Oscillations in Transmission Power Grids

Forced oscillation event in power grids refers to a state where malfunctioning or abnormally operating equipment causes persisting periodic disturbances in the system. While power grids are designed to damp most of perturbations during standard operations, some of them can excite normal modes of the system and cause significant energy transfers across the system, creating large oscillations thousands of miles away from the source. Localization of the source of such disturbances remains an outstanding challenge due to a limited knowledge of the system parameters outside of the zone of responsibility of system operators. Here, we propose a new method for locating the source of forced oscillations which addresses this challenge by performing a simultaneous dynamic model identification using a principled maximum likelihood approach. We illustrate the validity of the algorithm on a variety of examples where forcing leads to resonance conditions in the system dynamics. Our results establish that an accurate knowledge of system parameters is not required for a successful inference of the source and frequency of a forced oscillation. We anticipate that our method will find a broader application in general dynamical systems that can be well-described by their linearized dynamics over short periods of time.

Transformer-based deep learning model for forced oscillation localization

Accurately locating Forced Oscillations (FOs) source(s) in a large-scale power system is a challenging task, and an important aspect of power system operation. In this paper, a complementary use of Deep Learning (DL)-based and Dissipating Energy Flow (DEF)-based methods are proposed to localize forced oscillation source(s) using data from Phasor Measurement Units (PMUs), by tracing the forced oscillations source(s) on the branch level in the power system network. The robustness, effectiveness and speed of the proposed approach is demonstrated in a WECC 240-bus test system, with high renewable integration in the system. Several simulated cases were tested, including non-gaussian noise, partially observable system, and operational topology variations in the system which correspond to real-world challenges. Timely localization of forced oscillation at an early stage provides the opportunity for taking remedial reaction. The results show that without the information of system operational topology, the proposed method can achieve high localization accuracy in only 0.33 s.

Complex Dissipating Energy Flow Method for Forced Oscillation Source Location

In this letter we propose an extension of the Dissipating Energy Flow (DEF) method for locating sources of forced oscillations (FOs), based on an energy function constructed by the complex integral approach, which we call Complex DEF (CDEF). To trace sources of FO, we study the scalar projection of CDEF in a specific direction on the complex plane. We show by simulated cases that this alternative has a good performance in cases where the original DEF fails.

A new phase-driven approach to pinpoint source of forced oscillations based on fundamental frequency

A new phase-driven approach to pinpoint source of forced oscillations based on fundamental frequency

Analysis of disturbance source location of direct drive wind turbine based on energy function

In order to locate the disturbance source quickly and accurately in the wind farm, taking the direct drive wind turbine as an example, using the transient energy method, firstly, the transient energy flow formula is derived according to the mathematical model of each part of the direct drive wind turbine, the energy flow power is obtained by linear fitting, and the position of the disturbance source is judged by the positive and negative energy flow power; then a single machine infinite bus system model with forced oscillation source is built on PSCAD/EMTDC simulation platform for simulation. The results show that the transient energy method can accurately locate the disturbance source of direct drive wind turbine unit.

A Comprehensive Method to Mitigate Forced Oscillations in Large Interconnected Power Grids

Multiple severe forced oscillation events have recently been observed across the North American interconnections and around the world. These forced oscillations have caused power swings, limited power transfer capability, damaged equipment, and persisted indefinitely until the driving source was located and removed. This paper proposes a comprehensive method to mitigate forced oscillations. Once a forced oscillation is detected, a new source location algorithm can be used to locate the source based on the oscillation mode angle without requiring system topology information. If the source cannot be quickly located and removed, a control strategy can be activated to modulate the active power of utility-scale inverter-based battery energy storage systems (BESSs) to reduce the energy of forced oscillations to a safe level and allow sufficient time for locating the exact source. The proposed source location algorithm is validated using measurements collected during the January 11, 2019 forced oscillation event in North America and other actual grid events, while the proposed control strategy is verified using the Eastern Interconnection dynamic model under the replicated January 11, 2019 forced oscillation event. The simulation results demonstrated that the proposed source location algorithm can accurately identify the forced oscillation source, and the proposed control strategy can significantly reduce forced oscillation energy.

Time Series Classification for Locating Forced Oscillation Sources

This article presents a machine learning based time-series classification method for using synchrophasor measurements to locate the source of forced oscillation (FO) for fast disturbance removal. First, multivariate time series (MTS) matrices are constructed by the most informative measurements selected by sequential feature selection from each power plant. Then, the Mahalanobis matrix is trained such that the Mahalanobis distance between the MTSs from the same class (i.e., with the same FO source location) are minimized and from different classes (i.e., with different FO source locations) are maximized. This allows MTSs to be classified by classifiers with class membership corresponding to the location of each FO source. To meet the runtime requirements of online matching, class templates are constructed to reduce data size and improve matching efficiency. To account for uncertainty in identifying the exact beginning of an FO event, dynamic time warping is used to align the out-of-sync MTSs. IEEE 39bus and WECC 179bus systems are used for algorithm development and validation. Simulation results demonstrate that the algorithm meets online operation runtime requirement with high accuracy using misaligned data sets.

Analysis of Energy Flow Method for Oscillation Source Location

Sudden occurrence of a large forced oscillation (FO) is a challenging problem for power system operators, especially when the forced oscillation is resonating with a natural system mode. Among the methods for oscillation source location, the energy flow method has shown promise for detecting the source of a natural oscillation as well as a forced oscillation. In this paper, we analyze the performance of the energy flow method in depth by evaluating the expressions of incremental energy in one period of the forced oscillation and by looking at a wide range of forced oscillation frequencies. We show that the energy flow based method can misidentify sources of forced oscillations. That is, the method may not be able to locate the true forced oscillation source as well as identify a non-source device to be the source. Examples are shown for systems with different damping levels of system modes and for different load composition types.

A Synchrophasor Data-Driven Method for Forced Oscillation Localization Under Resonance Conditions

This paper proposes a data-driven algorithm for locating the source of forced oscillations and suggests a physical interpretation for the method. By leveraging the sparsity of forced oscillations along with the low-rank nature of synchrophasor data, the problem of source localization under resonance conditions is cast as computing the sparse and low-rank components using Robust Principal Component Analysis (RPCA), which can be efficiently solved by the exact Augmented Lagrange Multiplier method. Based on this problem formulation, an efficient and practically implementable algorithm is proposed to pinpoint the forced oscillation source during real-time operation. Furthermore, theoretical insights are provided for the efficacy of the proposed approach, by use of physical model-based analysis, specifically by highlighting the low-rank nature of the resonance component matrix. Without the availability of system topology information, the proposed method can achieve high localization accuracy in synthetic cases based on benchmark systems and real-world forced oscillations in the power grid of Texas.

Non-Stationary Power System Forced Oscillation Analysis Using Synchrosqueezing Transform

Non-stationary forced oscillations (FOs) have been observed in power system operations. However, most detection methods assume that the frequency of FOs is stationary. In this paper, we present a methodology for the analysis of non-stationary FOs. Firstly, Fourier synchrosqueezing transform (FSST) is used to provide a concentrated time-frequency representation of the signals that allows identification and retrieval of non-stationary signal components. To continue, the Dissipating Energy Flow (DEF) method is applied to the extracted components to locate the source of forced oscillations. The methodology is tested using simulated as well as real PMU data. The results show that the proposed FSST-based signal decomposition provides a systematic framework for the application of DEF Method to non-stationary FOs.

A Passivity Interpretation of Energy-Based Forced Oscillation Source Location Methods

This paper develops a systematic framework for analyzing how low frequency forced oscillations propagate in electric power systems. Using this framework, the paper shows how to mathematically justify the so-called Dissipating Energy Flow (DEF) forced oscillation source location technique. The DEF's specific deficiencies are pinpointed, and its underlying energy function is analyzed via incremental passivity theory. This analysis is then used to prove that there exists no passivity transformation (i.e. quadratic energy function) which can simultaneously render all components of a lossy classical power system passive. The paper goes on to develop a simulation-free algorithm for predicting the performance of the DEF method in a generalized power system, and it analyzes the passivity of three non-classical load and generation components. The proposed propagation framework and performance algorithm are both tested and illustrated on the IEEE 39-bus New England system and the WECC 179-bus system.

Frequency domain approaches to locate forced oscillation source to control device

The location of the control devices that produce forced oscillation sources is crucial to the elimination of forced oscillations. This paper proposes two frequency domain approaches to reliably locate oscillation sources from mechanical parts and excitation systems of generators to their control devices. Firstly, the transfer function matrix from mechanical disturbances to mechanical powers is demonstrated to be inherently diagonally dominant. The property is used to monitor and preliminarily locate oscillation sources from mechanical parts. Moreover, this paper proposes a systematic method of power spectral density prediction to further locate oscillation source to control device by using the generator terminal voltage (or generator current) to predict the power spectral density of generator responses. It is shown that for non-source generators, the responses are determined by the generator terminal voltage. The generator with distinct mismatch between predicted and measured power spectral density is identified as the oscillation source. The mismatches between predicted and measured power spectral density of different responses are different, further enabling the method to identify the control device producing the oscillation source. The method of power spectral density prediction is used as a general method to provide further and detailed location results. Demonstrative examples of a 39-bus system and the 547-machine 8647-bus North China Power Grid show the effectiveness of the proposed methods.

Forced oscillation source location in power systems using system dissipating energy

A dissipating energy-based technique is proposed to locate the source of forced oscillations (FOs) in power systems. The network and load information is incorporated into the developed algorithm and continuously updated using supervisory control and data acquisition (SCADA) measurement. The effect of electromechanical damping on system response in FO scenario is discussed; and therefore, the efficiency of the proposed technique to locate the source has been investigated. The proposed methodology is tested and verified for different simulation test cases and for different scenario viz. for single and multiple sources of disturbances. In the case of multiple sources of disturbances with different time of initiation of the disturbance, the proposed technique successfully locates all sources in their time durations of disturbance. Different load models have been evaluated for their impact on the success of the proposed algorithm in a real-time digital simulation environment. The proposed technique is successfully verified for the test cases reported by the IEEE PES Task Force on Oscillation Source Location.

Application of unknown input observers to locate forced oscillation source

Application of unknown input observers to locate forced oscillation source

A Bayesian Approach to Forced Oscillation Source Location Given Uncertain Generator Parameters

Since forced oscillations are exogenous to dynamic power system models, the models by themselves cannot predict when or where a forced oscillation will occur. Locating the sources of these oscillations, therefore, is a challenging problem which requires analytical methods capable of using real time power system data to trace an observed oscillation back to its source. The difficulty of this problem is exacerbated by the fact that the parameters associated with a given power system model can range from slightly uncertain to entirely unknown. In this paper, a Bayesian framework, via a two-stage maximum a posteriori optimization routine, is employed in order to locate the most probable source of a forced oscillation given an uncertain prior model. The approach leverages an equivalent circuit representation of the system in the frequency domain and employs a numerical procedure, which makes the problem suitable for real time application. The derived framework lends itself to successful performance in the presence of phasor measurement unit measurement noise, high generator parameter uncertainty, and multiple forced oscillations occurring simultaneously. The approach is tested on a four-bus system with a single forced oscillation source and on the WECC 179-bus system with multiple oscillation sources.