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In this paper, a long short-term memory (LSTM)-based method with a multi-input tensor approach is used for the classification of events that affect the power quality (PQ) in power systems with distributed generation sources. The considered events are line faults (one line, two lines, and three lines faulted), islanding events, sudden load variations, and generation tripping. The proposed LSTM-based method was trained and tested using the signals produced by the events simulated in a study system with distributed generation sources via PSCAD®. Then, noise with different levels was added to the testing set for a thorough assessment, and the results were compared with other well-known methods such as convolutional and simple recurrent neuronal networks. The LSTM-based method with multi-input proved to be effective for event classification, achieving remarkable classification performance even in noisy conditions. [ABSTRACT FROM AUTHOR]

It is not uncommon for oscillatory electric power system modes to move close to a resonance in which eigenvalues coincide. In a weak resonance, the modes are decoupled and the eigenvalues do not interact. We analyze general perturbations of a weak resonance and find two distinct behaviors, including interactions near strong resonances in which the eigenvalues quickly change direction. The possible perturbations are illustrated with interactions between electromechanical modes in a 4-generator power system. Some of the interactions are similar to subsynchronous resonance and can lead to oscillatory instability. Index Terms--Eigenvalues and eigenfunctions, Hopf bifurcation, oscillations, power system dynamic stability, resonance, root loci, snbsynchronous resonance.

Power system normal form analysis has developed coefficients and indices in modal coordinates to quantify nonlinear modal interactions. We study the changes in the coefficients and indices when the power system equations are expressed in different coordinates or units and show that they can be normalized to be invariant to coordinate changes and thus intrinsic to the power system. The results are illustrated on a 4-generator system. An example shows that the coefficients and indices not only detect nonlinear interactions but also can become very large near a strong resonance in the system linearization. Index Terms--Nonlinear modal behavior, normal form method, power system dynamics, strong resonance.

Identification of coherent generators and the determination of the stability system condition in large interconnected power system is one of the key steps to carry out different control system strategies to avoid a partial or complete blackout of a power system. However, the oscillatory trends, the larger amount data available and the non-linear dynamic behaviour of the frequency measurements often mislead the appropriate knowledge of the actual coherent groups, making wide-area coherency monitoring a challenging task. This paper presents a novel online unsupervised data mining technique to identify coherent groups, to detect the power system disturbance event and determine status stability condition of the system. The innovative part of the proposed approach resides on combining traditional plain algorithms such as singular value decomposition (SVD) and Kmeans for clustering together with new concept based on clustering slopes. The proposed combination provides an added value to other applications relying on similar algorithms available in the literature. To validate the effectiveness of the proposed method, two case studies are presented, where data is extracted from the large and comprehensive initial dynamic model of ENTSO-E and the results compared to other alternative methods available in the literature. [ABSTRACT FROM AUTHOR]

This paper proposes a light, flexible, and yet reliable multiparametric estimation algorithm for grid-connected voltage-source-converter-based systems. This approach combines the nonlinear least squares (NLSQ) fitting algorithm and the steady-state extended harmonic domain (EHD) model to take into account the harmonic effects. The EHD model is used to take advantage of the harmonic content of the electrical signals to provide robustness and improved performance to the NLSQ estimation methodology. In addition, this harmonic formulation reduces the necessity of synchronized measurements. Details of the implementation are provided by an experimental case study, in which the grid equivalent (Thevenin voltage, inductance, and resistance), the ac-side filter (inductance and resistance), and the converter switching and conduction loss resistance are accurately estimated for three different operating conditions. [ABSTRACT FROM AUTHOR]

A method to solve a multi‐objective optimal power flow (MOOPF) problem with multiple and competing objective functions (OF) is presented. The modified flower pollination algorithm and the normal boundary intersection method are used in a complementary way to determine the Pareto front solution of the MOOPF problem. To help in the decision making process, an intuitive criterion based on the centroid concept is proposed to select the best compromise solution from the Pareto frontier. To demonstrate the capabilities of the proposed method, different OFs are combined to calculate the Pareto front solution on the IEEE 30 bus test system. Finally, a comparison of the proposed centroid based method against the well‐known fuzzy membership and entropy criterions is provided in the results section. [ABSTRACT FROM AUTHOR]

A global multiscale method based on a dynamic mode decomposition (DMD) algorithm to characterize the global behavior of transient processes recorded using wide-area sensors is proposed. The method interprets global dynamic behavior in terms of both, spatial patterns or shapes and temporal patterns associated with dynamic modes containing essentially single-frequency components, from which the mode shapes, frequencies and growth and decay rates of the modes can be extracted simultaneously. These modes are then used to detect the coherent and dominant structures within the data. The technique is well suited for fast wide-area monitoring and assessment of global instability in the context of modern data fusion-based estimation techniques. Results of the application of the proposed method to large, high-dimensional data sets are encouraging. [ABSTRACT FROM PUBLISHER]

This paper presents a control scheme of a wide-area controlled static VAr compensator (WAC-SVC) and its real-time implementation in a hardware-in-the-loop (HIL) simulation scheme with three control objectives: (1) to increase the critical clearing time, (2) to damp the power oscillations, and (3) to minimize the maximum line current. The proposed control scheme considers a correction strategy to compensate the delays up to 200 ms. In addition to this, a generator tripping scheme based on synchrophasor measurements to determine the proximity to the loss of synchronism is proposed. A delay compensation algorithm based on polynomial approximations is also developed. The proposed WAC-SVC is experimentally validated using a Real-Time Digital Simulator platform (RTDS), industrial communication protocols, a commercial device for PMU-based control implementations, and digital relays with PMU capability. The real-time simulation results confirm its effectiveness and feasibility in real industrial applications. Furthermore, practical guidelines to implement this kind of control schemes are provided. [ABSTRACT FROM AUTHOR]