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access icon free New phasor-based approach for online and fast prediction of generators grouping using decision tree

© The Institution of Engineering and Technology
Received 11/09/2016, Accepted 02/01/2017, Revised 15/12/2016, Published 23/01/2017

Fast and accurate identification of coherent generator groups is helpful in dynamic and transient stability analysis as well as other applications such as controlled islanding. In this study, a new method is presented for predicting the generators’ grouping scheme based on the data measured before and in a short time after the disturbance occurrence. To do that, a classifier model is trained using a training dataset. In the training dataset, the input is the attributes, which are obtained directly or indirectly from the data measured by phasor measurement units. On the other hand, the target in the training dataset is the generators’ grouping, which in this study is calculated using a new method called subtractive technique. In subtractive technique, coherent generator groups are determined based on the generator density values. When the classifier model is built using the training dataset, it can be used for online applications. In this study, the well-known 68-bus, 16-machine power system as well as the Iranian 400 and 230 kV south east regional grid are used as the test systems for investigating the efficiency of proposed coherent group prediction method. Results show that the proposed method can predict the generators’ grouping scheme with high accuracy.

Inspec keywords: decision trees; phasor measurement; power system stability; power distribution faults

Other keywords: controlled islanding; decision tree; subtractive technique; transient stability analysis; phasor-based approach; phasor measurement units; disturbance occurrence; generators grouping

Subjects: Distribution networks; Combinatorial mathematics; Power system measurement and metering

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