Simulation of SVC in MATLAB for Transient Mode Analysis
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In MATLAB, we can utilize SVC (Support Vector Classifier) for transient mode simulation. Support Vector Machine is a robust machine learning algorithm that employs nonlinear mapping to perform classification in high-dimensional feature spaces. For power system applications, SVC is implemented to conduct transient stability analysis, ensuring system stability during fault conditions. The simulation approach typically involves using MATLAB's Statistics and Machine Learning Toolbox with key functions like fitcsvc for model training and predict for classification. The algorithm works by finding optimal hyperplanes that maximize margins between different stability classes, using kernel functions (such as RBF or polynomial) to handle nonlinear decision boundaries. This SVC-based simulation helps engineers better understand power system dynamics under disturbances, ultimately enhancing system reliability and robustness through predictive stability assessment.
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