Classification of Frequency Disturbance Event in Power Systems Considering Optimal PMU Placement

Keyphrases

• Power System 100%
• PMU Placement 100%
• Frequency Disturbance Events 100%
• Feature Data 66%
• Partial Observability 66%
• Node Features 66%
• Deep Learning 33%
• Greedy Algorithm 33%
• Relative Angle 33%
• Deep Learning Model 33%
• Grid Stability 33%
• Transmission Events 33%
• Rate of Change of Frequency (ROCOF) 33%
• Suppression Measures 33%
• Convolutional Neural Network Model 33%
• IEEE 39-bus System 33%
• Load Disconnection 33%
• Generator Tripping 33%
• Power System Frequency 33%
• Optimized Arrangement 33%
• Reaching Development 33%

Engineering

• Nodes 100%
• Observability 100%
• Power Engineering 100%
• Deep Learning Method 100%
• System Frequency 50%
• Bus System 50%
• Relative Angle 50%
• Network Model 50%
• Change Rate 50%
• Disconnections 50%
• Greedy Algorithm 50%
• Convolutional Neural Network 50%

Earth and Planetary Sciences

• Greedy Algorithm 100%