Risk Assessment of Cascading Outages: Methodologies and Challenges

Vaiman, Marianna; Bell, Keith; Chen, Y.; Chowdhury, Badrul; Dobson, Ian; Hines, Paul; Papic, Milorad; Miller, Stephen; Zhang, P.

doi:10.1109/tpwrs.2011.2177868

Cited by 364 publications

(224 citation statements)

References 32 publications

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“…Cascading effects of contingencies in the power grid are very complex phenomenona, and identifying the typical mechanisms of cascading failures and understanding how these mechanisms interact during blackouts is an important research area [58][59][60][61][62][63]. Potential mechanisms that might be modeled include overloaded line tripping by impedance relays due to the low voltage and high current operating conditions, line tripping due to loss of synchronism, the undesirable generator tripping events by overexcitation protection, generator tripping due to abnormal voltage and frequency system condition, and under-frequency or under-voltage load shedding.…”

Section: Integrated Simulation Framework For Security Of Supply Analysismentioning

confidence: 99%

Development of a Simulation Framework for Analyzing Security of Supply in Integrated Gas and Electric Power Systems

et al. 2017

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Gas and power networks are tightly coupled and interact with each other due to physically interconnected facilities. In an integrated gas and power network, a contingency observed in one system may cause iterative cascading failures, resulting in network wide disruptions. Therefore, understanding the impacts of the interactions in both systems is crucial for governments, system operators, regulators and operational planners, particularly, to ensure security of supply for the overall energy system. Although simulation has been widely used in the assessment of gas systems as well as power systems, there is a significant gap in simulation models that are able to address the coupling of both systems. In this paper, a simulation framework that models and simulates the gas and power network in an integrated manner is proposed. The framework consists of a transient model for the gas system and a steady state model for the power system based on AC-Optimal Power Flow. The gas and power system model are coupled through an interface which uses the coupling equations to establish the data exchange and coordination between the individual models. The bidirectional interlink between both systems considered in this studies are the fuel gas offtake of gas fired power plants for power generation and the power supply to liquefied natural gas (LNG) terminals and electric drivers installed in gas compressor stations and underground gas storage facilities. The simulation framework is implemented into an innovative simulation tool named SAInt (Scenario Analysis Interface for Energy Systems) and the capabilities of the tool are demonstrated by performing a contingency analysis for a real world example. Results indicate how a disruption triggered in one system propagates to the other system and affects the operation of critical facilities. In addition, the studies show the importance of using transient gas models for security of supply studies instead of successions of steady state models, where the time evolution of the line pack is not captured correctly.

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Section: Integrated Simulation Framework For Security Of Supply Analysismentioning

confidence: 99%

Development of a Simulation Framework for Analyzing Security of Supply in Integrated Gas and Electric Power Systems

et al. 2017

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“…One of the local issues experienced in Malaysia was the major blackout event in 13 January 2005 and ultimately enforced the local authority to shed some of the load to balance the demands (Vaiman et al, 2012).…”

Section: Voltage Stability Assessmentmentioning

confidence: 99%

Comparative Study of Different Kalman Filter Implementations in Power System Stability

Goh¹

2014

American Journal of Applied Sciences

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Voltage stability and voltage collapse issues have in recent years begun to constitute an unpleasant warning to the operational security of power systems. Many techniques have been investigated in order to predict the point of voltage collapse. However, there are still several restrictions due to the insufficiency of current system state information. Accompanied by the commencement of the Phasor Measurement Units (PMUs) evolving technology, it donates a solution to enhance the existing power system state estimation. In consequence, the significances to develop preferable methods that would provide a preliminary warning before the voltage collapse had grabbed the attention. This study covers the forming of real-time system monitoring methods that able to provide a timely warning in the power system. The algorithms used to estimate the points of collapse are according to the theory that voltage instability is approximately linked to the maximum load ability of a transmission network. As a result, the critical operating conditions (peak of maximum deliverable power) come when the system Thevenin impedance is equal to the load impedance. This study focuses specifically on research about the motivation and the application of different Kalman filter implementations such as Discrete Kalman Filter (DKF), Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) are used to track the Thevenin parameters. Therefore, the implications of this research paper are to determine the robustness and reliability of the proposed tracking methods. As compared to previous studies, the tracking process is just mainly focused on DKF method only, while the novelty throughout this study is to compare the performances and efficiencies of different Kalman filters in determining the maximum load ability on the 2 different types of test systems. Accompanying, the parameters are utilized in real-time voltage instability estimator to discover the current system's condition. In this study, the effectiveness of the proposed algorithms is assessed under a large number of random operating conditions on the Malaysia's power system 132 kV, 2-bus and 10-bus systems. Eventually, the results are differentiated by using the early-warning index of voltage collapse. All through the test cases, EKF method shows the best ability to track the Thevenin parameters as compared to DKF and UKF. Last but not least, the earlywarning index acted as a pioneer implication in estimating the maximum load power ability of the power system right before load shedding methods are being executed.

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“…In the last two decades, a number of large blackouts occurred all over the world due to the loss of synchronization caused by cascading failures [1]. Insufficient online implementations and lack of timely emergency controls, such as load shedding, generator tripping and proactive islanding, are said to be the common causes of those accidents [2]. The increasing renewable energy integration brings dynamic security deterioration of power systems, which would lead to the operation risks [3].…”

Section: Introductionmentioning

confidence: 99%

High-performance predictor for critical unstable generators based on scalable parallelized neural networks

Liu¹,

Yang²,

et al. 2016

J. Mod. Power Syst. Clean Energy

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A high-performance predictor for critical unstable generators (CUGs) of power systems is presented in this paper. The predictor is driven by the MapReduce based parallelized neural networks. Specifically, a group of back propagation neural networks (BPNNs), fed by massive response trajectories data, are efficiently organized and concurrently trained in Hadoop to identify dynamic behavior of individual generator. Rather than simply classifying global stability of power systems, the presented approach is able to distinguish unstable generators accurately with a few cycles of synchronized trajectories after fault clearing, enabling more in-depth emergency awareness based on wide-area implementation. In addition, the technique is of rich scalability due to Hadoop framework, which can be deployed in the control centers as a high-performance computing infrastructure for real-time instability alert. Numerical examples are studied using NPCC 48-machines test system and a realistic power system of China.

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Risk Assessment of Cascading Outages: Methodologies and Challenges

Cited by 364 publications

References 32 publications

Development of a Simulation Framework for Analyzing Security of Supply in Integrated Gas and Electric Power Systems

Development of a Simulation Framework for Analyzing Security of Supply in Integrated Gas and Electric Power Systems

Comparative Study of Different Kalman Filter Implementations in Power System Stability

High-performance predictor for critical unstable generators based on scalable parallelized neural networks

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