Open AccessNew approach to transient stability prediction of power systems in wide area measurement systems based on multiple‐criteria decision making theory
Author(s) -
Hosseini Hossein,
Naderi Soheil,
Afsharnia Saeed
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.5313
Subject(s) - support vector machine , electric power system , computer science , transient (computer programming) , classifier (uml) , stability (learning theory) , control theory (sociology) , remedial education , remedial action , artificial intelligence , machine learning , power (physics) , mathematics , control (management) , ecology , physics , mathematics education , quantum mechanics , contamination , biology , environmental remediation , operating system
To prevent power system blackouts following a large disturbance such as a fault, the speed and precision of the stability status prediction are two important factors for the remedial action schemes. A new approach for the transient stability prediction is presented employing the multi‐criteria decision making (MCD) theory to consider both factors simultaneously in this study. It is shown that they depend on the prediction time, therefore solving the MCD problem results in finding the best time for the stability prediction. As the criteria quantifying is necessary in the MCD methods, in this study a new index is proposed to quantify the prediction speed. Furthermore, the support vector machine (SVM) classifier is employed as a transient stability predictor. In addition, the best features are selected and incorporated as the inputs of the SVM classifier according to the features selection methods. Finally, all proposed schemes are implemented on the IEEE 39‐Bus test system. The obtained results show the prediction of stability at the optimum time causing the instability prevention with the less required remedial action.