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Synchronised measurements based transient security assessment of power systems using AdaBoost classifiers

IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第17期13卷 3980-3987页

作者： Venkatesh, Thirugnanasambandam Jain, Trapti Indian Inst Technol Indore Discipline Elect Engn Indore 452020 Madhya Pradesh India VIT Bhopal Univ Sch Elect Engn Kothrikalan 466114 India

This study proposes an adaptive boosting (AdaBoost) algorithm for precise and accurate prediction of transient security assessment of power systems using synchronised measurements. The proposed approach (PRPA) also determines the generator coherent state as well as the synchronism status of each generating unit. The PRPA consists of three classifier models, in which classifier I determines the transient security status and classifier II is used to determine the generator coherency. Classifier III is a hybrid classifier, which determines the individual generator synchronism state for a given operating condition. This hybrid classifier consists of an array of parallel classifiers, where one classifier is assigned to each generating unit of the power system. For this assessment, the measured rotor angles of the generators are used as inputs to the proposed classifier models. In classification stage, several weak classifiers are combined in a linear manner to construct a strong classifier. The performance of the AdaBoost algorithm is further improved by a new weight updation strategy using fuzzy clustering thresholding technique. Simulation results obtained from IEEE 14-bus, IEEE 30-bus and Indian 246-bus systems reveal that the PRPA can enhance the overall monitoring and assessment of power system using synchronised measurements.

关键词： synchronisation pattern classification fuzzy set theory power system security pattern clustering rotors learning (artificial intelligence) power engineering computing power system transients power system measurement AdaBoost classifiers precise prediction generator coherent state synchronism status generating unit classifier models transient security status classifier II generator coherency classifier III hybrid classifier parallel classifiers Indian 246-bus systems rotor angles synchronised measurementsbased transient security assessment generator synchronism state adaptive boosting algorithm power system transient security assessment weight updation strategy fuzzy clustering thresholding technique IEEE 30-bus systems IEEE 14-bus systems

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AdaBoost classifiers for phasor measurements-based security assessment of power systems

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IET GENERATION TRANSMISSION & DISTRIBUTION 2018年第8期12卷 1747-1755页

作者： Thirugnanasambandam, Venkatesh Jain, Trapti Indian Inst Technol Indore Discipline Elect Engn Indore 452020 Madhya Pradesh India

Power system security is a major concern in real-time operation. It is essential to protect the system from blackout by taking proper control actions. This study proposes a boosting algorithm for the precise and accurate prediction of static security assessment of power systems using synchronised measurements. In addition to security status, the proposed approach also predicts the type of violations which may be either line overload/voltage violation or both of the insecure operating conditions. To overcome the computational complexity, the number of input phasor measurements is reduced by a statistical approach based on class separability and correlation coefficient indices. In the classification stage, support vector machines (SVMs) are used as weak classifiers and a strong classifier is constructed as the linear combination of many weak SVM classifiers. The performance of the Adaptive Boosting (AdaBoost) algorithm is further improved by a new weight updation strategy using fuzzy clustering thresholding technique. The efficiency of the proposed approach is demonstrated on IEEE 14-bus, IEEE 30-bus, and Indian 246-bus systems. Further, the test results reveal that the proposed method of security assessment performs better than the other traditional classifiers viz. SVM, feed forward neural network and k-nearest neighbour classifier.

关键词： power system security phasor measurement learning (artificial intelligence) synchronisation computational complexity statistical analysis correlation methods support vector machines pattern clustering fuzzy set theory power engineering computing AdaBoost classifier power system security blackout static security assessment synchronised measurement line overload-voltage violation computational complexity input phasor measurement statistical approach correlation coefficient support vector machine weak SVM classifier adaptive boosting algorithm weight updation strategy fuzzy clustering thresholding technique IEEE 14-bus system IEEE 30-bus system Indian 246-bus system feed forward neural network k-nearest neighbour classifier

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