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Understanding Discrepancy of Power System dynamic security assessment with Unknown Faults: A Reliable Transfer Learning-based Method

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 427-431页

作者： Chao Ren Han Yu Yan Xu Zhao Yang Dong School of Computer Science and Engineering Nanyang Technological UniversitySingapore School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore

This letter proposes a reliable transfer learning(RTL)method for pre-fault dynamic security assessment(DSA)in power systems to improve DSA performance in the presence of potentially related unknown *** takes individual discrepancies into consideration and can handle unknown faults with incomplete *** experiment results demonstrate high DSA accuracy and computational efficiency of the proposed RTL *** analysis shows RTL can guarantee system performance.

关键词： Adversarial training dynamic security assessment maximum classifier discrepancy missing data transfer learning

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Critical Contingencies Ranking for dynamic security assessment Using Neural Networks

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Journal of Energy and Power Engineering 2012年第10期6卷 1663-1672页

作者： Gustavo Schweickardt Juan Manuel Gimenez-Alvarez Energetic Economy Institute Bariloche Atomic Center Bariloche CP 8400 Argentina Faculty of Engineering National University of San Juan San Juan CP 5400 Argentina

A number of contingencies simulated during dynamic security assessment do not generate unacceptable values of power system state variables, due to their small influence on system operation. Their exclusion from the set of contingencies to be simulated in the security assessment would achieve a significant reduction in computation time. This paper defines a critical contingencies selection method for on-line dynamic security assessment. The selection method results from an off-line dynamical analysis, which covers typical scenarios and also covers various related aspects like frequency, voltage, and angle analyses among others. Indexes measured over these typical scenarios are used to train neural networks, capable of performing on-line estimation of a critical contingencies list according to the system state.

关键词： Critical contingencies dynamic security assessment neural networks.

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Two-stage Transient-stability-constrained Optimal Power Flow for Preventive Control of Rotor Angle Stability and Voltage Sags

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Journal of Modern Power Systems and Clean Energy 2024年第5期12卷 1357-1369页

作者： Jorge Uriel Sevilla-Romero Alejandro Pizano-Martínez Claudio Rubén Fuerte-Esquivel Reymundo Ramírez-Betancour the Faculty of Electrical Engineering Universidad Michoacana de San Nicolás de Hidalgo58030 MoreliaMéxico the Department of Electrical Engineering Universidad of Guanajuato36787 SalamancaMéxico the Department of Electrical and Electronic Engineering Universidad Juárez Autónoma de Tabasco86040 VillahermosaMéxico

In practice,an equilibrium point of the power system is considered transiently secure if it can withstand a specified contingency by maintaining transient evolution of rotor angles and voltage magnitudes within set bounds.A novel sequential approach is proposed to obtain transiently stable equilibrium points through the preventive control of transient stability and transient voltage sag(TVS)problems caused by a severe *** proposed approach conducts a sequence of non-heuristic optimal active power re-dispatch of the generators to steer the system toward a transiently secure operating point by sequentially solving the transient-stability-constrained optimal power flow(TSC-OPF)*** the proposed approach,there are two sequential projection stages,with the first stage ensuring the rotor angle stability and the second stage removing TVS in voltage *** both projection stages,the projection operation corresponds to the TSC-OPF,with its formulation directly derived by adding only two steady-state variable-based transient constraints to the conventional OPF *** effectiveness of this approach is numerically demonstrated in terms of its accuracy and computational performance by using the Western System Coordinated Council(WSCC)3-machine 9-bus system and an equivalent model of the Mexican 46-machine 190-bus system.

关键词： dynamic security assessment transient stability transient voltage sag(TVS) optimal power flow(OPF)

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Selecting decision trees for power system security assessment

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Energy and AI 2021年第4期6卷 21-30页

作者： Al-Amin B.Bugaje Jochen L.Cremer Mingyang Sun Goran Strbac Department of Electrical&Electronic Engineering Imperial College LondonLondonSW72AZUK Department of Electrical Sustainable Energy TU DelftMekelweg 52628 CD DelftNetherlands Department of Control Science and Engineering Zhejiang UniversityHangzhou 310027China

Power systems transport an increasing amount of electricity,and in the future,involve more distributed renewables and dynamic interactions of the *** system response to disturbances must be secure and predictable to avoid power *** system response can be simulated in the time ***,this dynamic security assessment(DSA)is not computationally tractable in *** promising is to train decision trees(DTs)from machine learning as interpretable classifiers to predict whether the systemwide responses to disturbances are *** most research,selecting the best DT model focuses on predictive ***,it is insufficient to focus solely on predictive *** alarms and false alarms have drastically different costs,and as security assessment is a critical task,interpretability is crucial for *** this work,the multiple objectives of interpretability,varying costs,and accuracies are considered for DT model *** propose a rigorous workflow to select the best *** addition,we present two graphical approaches for visual inspection to illustrate the selection sensitivity to probability and impacts of *** propose cost curves to inspect selection combining all three objectives for the first *** studies on the IEEE 68 bus system and the French system show that the proposed approach allows for better DT-selections,with an 80%increase in interpretability,5%reduction in expected operating cost,while making almost zero accuracy *** proposed approach scales well with larger systems and can be used for models beyond ***,this work provides insights into criteria for model selection in a promising application for methods from artificial intelligence(AI).

关键词： dynamic security assessment Machine learning Decision trees ROC curve Cost curves Cost sensitivity

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