Online dynamic security assessment with missing pmu measurements: A data mining approach

He, Miao; Vittal, Vijay; Zhang, Junshan

doi:10.1109/tpwrs.2013.2246822

Cited by 147 publications

(84 citation statements)

References 19 publications

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“…For the two power systems, the corresponding WAMS was assumed to have a hierarchical architecture [28]. The power systems were monitored with different areas, and the PMU measurements from different substations in different areas were collected, time aligned by the phasor data concentrator, and then submitted to the monitoring center.…”

Section: Simulation Resultsmentioning

confidence: 99%

Wide-Area Measurement—Based Model-Free Approach for Online Power System Transient Stability Assessment

Huang

Chen

et al. 2018

Energies

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Online assessment of transient stability of power systems is critical for avoiding blackout. The increasing installation of phasor measurement units in power systems and the advancement of the wide-area measurement systems make it possible to develop methods for online assessment of power systems by using a large amount of real-time synchronous data. In this paper, we propose an approach based on the largest Lyapunov exponent (LLE) for online transient rotor angle stability assessment, using only wide-area measurement systems data. Through establishing a mathematical model that accounts for the LLE value and the rotor speed, as well as analyzing the post-fault phase-plane trajectory, we present a fast stability criterion to determine whether transient instability occurs. The proposed approach is model-free and does not need long-time LLE data to identify the final sign of the LLE. Furthermore, to reduce computational cost and realize online assessment for large-scale power systems, the critical generator pair (CGP) is recognized as the observation for the rotor angle stability assessment, and an effective algorithm for identifying the CGP is presented. Several case studies on the IEEE-39 bus test system and East China power grid are reported to demonstrate the accuracy and effectiveness of the proposed approach.Keywords: power system stability; online stability assessment; the largest Lyapunov exponent (LLE); rotor angle speed; wide-area measurement system (WAMS)

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Section: Simulation Resultsmentioning

confidence: 99%

Wide-Area Measurement—Based Model-Free Approach for Online Power System Transient Stability Assessment

Huang

Chen

et al. 2018

Energies

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“…In the literature, ensemble learning has been widely used in power system dynamic security assessment [9,10,12,16,23]. For ensemble learning, a set of single learning units are individually trained and combined together to make the final decision.…”

Section: Elm Ensemble Learningmentioning

confidence: 99%

“…To achieve fast real-time TSA, intelligent system IS-based methods have been identified as a promising solution [7][8][9][10][11][12][13][14][15][16]. In IS-based TSA, the conventional T-D simulation data constructs the database to train the intelligent models at offline stage, and then the trained models can perform fast online TSA with the minimal computation effort.…”

Section: Introductionmentioning

confidence: 99%

“…In IS-based TSA, the conventional T-D simulation data constructs the database to train the intelligent models at offline stage, and then the trained models can perform fast online TSA with the minimal computation effort. In the literature, the intelligent models, such as decision tree (DT) [10][11][12], artificial neural network (ANN) [13] and support vector machine (SVM) [14], have demonstrated their strengths in power system stability assessment.…”

Section: Introductionmentioning

confidence: 99%

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Post-disturbance transient stability assessment of power systems towards optimal accuracy-speed tradeoff

Ren

Zhang

2018

Prot Control Mod Power Syst

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The recent development of phasor measurement technique opens the way for real-time post-disturbance transient stability assessment (TSA). Following a disturbance, since the transient instability can occur very fast, there is an urgent need for fast TSA with sufficient accuracy. This paper first identifies the tradeoff relationship between the accuracy and speed in post-disturbance TSA, and then proposes an optimal self-adaptive TSA method to optimally balance such tradeoff. It uses ensemble learning and credible decision-making rule to progressively predict the post-disturbance transient stability status, and models a multi-objective optimization problem to search for the optimal balance between TSA accuracy and speed. With such optimally balanced TSA performance, the TSA decision can be made as fast as possible while maintaining an acceptable level of accuracy. The proposed method is tested on New England 10-machine 39-bus system, and the simulation results verify its high efficacy.

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“…The above discussed approaches, including [16], uses databases generated in off-line aiming to cover all the possible operating conditions and topology changes. The application of data mining techniques to speed up the DSA process by using the historical data from large databases is investigated in [25] and [26]. However, it is challenging to determine if an initially trained network is valid to assess the stability of a particular system state once the system state is evolved to a different operating state or a different network topology.…”

Section: Machine Learning Techniquesmentioning

confidence: 99%

Application of energy-based power system features for dynamic security assessment

Geeganage

Annakkage

Weekes

et al. 2015

2015 IEEE Power &Amp; Energy Society General Meeting

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To date, the potential of on-line Dynamic Security Assessment (DSA)-to monitor, alert, and enhance system security-is constrained by the longer computational cycle time. Traditional techniques requiring extensive numerical computations makes it challenging to complete the assessment within an acceptable time. Longer computational cycles produce obsolete security assessment results as the system operating point evolves continuously. This thesis presents a DSA algorithm, based on Transient Energy Function (TEF) method and machine learning, to enable frequent computational cycles in on-line DSA of power systems.The use of selected terms of the TEF as pre-processed input features for machine learning demonstrated the ability to successfully train a contingency-independent classifier that is capable of classifying stable and unstable operating points. The network is trained for current system topology and loading conditions. The classifier can be trained using a small dataset when the TEF terms are used as input features. The prediction accuracy of the proposed scheme was tested under the balanced and unbalanced faults with the presence of voltage sensitive and dynamic loads for different operating points. The test results demonstrate the potential of using the proposed technique for power system on-line DSA. Power system devices such as HVDC and FACTS can be included in the algorithm by incorporating the effective terms of a corresponding TEF.An on-line DSA system requires the integration of several functional components.Some of these components already exist and the others are newly introduced to the i power system. The practicality of the proposed technique in terms of a) critical data communications aspects b) computational hardware requirements; and c) capabilities and limitations of the tools in use was tested using an implementation of an on-line DSA system. The test power system model was simulated using a real-time digital simulator. The other functional units were distributed over the Local Area Network (LAN). The implementation indicated that an acceptable computational cycle time can be achieved using the proposed method.In addition, the work carried out during this thesis has produced two tools that can be used for a) web-based automated data generation for power system studies; and b) testing of on-line DSA algorithms.ii

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Online dynamic security assessment with missing pmu measurements: A data mining approach

Cited by 147 publications

References 19 publications

Wide-Area Measurement—Based Model-Free Approach for Online Power System Transient Stability Assessment

Wide-Area Measurement—Based Model-Free Approach for Online Power System Transient Stability Assessment

Post-disturbance transient stability assessment of power systems towards optimal accuracy-speed tradeoff

Application of energy-based power system features for dynamic security assessment

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