Solar Panel Fault Analysis using MATLAB Simulink and Machine Learning with Python | PV Fault Detection & Classification
This video presents an advanced Solar Panel (PV) Fault Analysis system combining MATLAB/Simulink modeling with Machine Learning techniques implemented in Python.
The project detects and classifies common photovoltaic faults using electrical signal data and ML algorithms, improving reliability, efficiency, and maintenance planning of solar energy systems.
We first simulate different PV fault conditions in MATLAB/Simulink, extract key electrical features, and then apply machine learning models (Python) to accurately identify and classify faults.
📦 Project Support
🌐 www.matlabprojectscode.com
📧 matlabprojectscode@gmail.com
📱 WhatsApp: +91 8300015425
🔍 Faults Analyzed
Partial Shading Fault
Line-to-Line (L–L) Fault
Line-to-Ground (L–G) Fault
Open-Circuit Fault
Short-Circuit Fault
Normal Operating Condition
⚙️ Workflow Explained
Solar PV system modeling in MATLAB/Simulink
Fault injection and data generation
Feature extraction (Voltage, Current, Power, I–V & P–V curves)
Dataset formation and preprocessing
Machine Learning classification using Python
SVM
Random Forest
KNN
ANN / Deep Learning (optional)
Performance evaluation: Accuracy, Confusion Matrix, Precision & Recall
🎓 Applications
Smart solar farms & PV monitoring systems
Fault-tolerant renewable energy systems
Industrial and grid-connected PV plants
BTech / MTech / MSc / PhD research projects
AI-based predictive maintenance systems
👨💻 Who Should Watch
Renewable energy & electrical engineering students
Data science and machine learning learners
Researchers working on AI-based energy systems
Engineers developing intelligent PV monitoring tools
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PV I V curve fault analysis,
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line to ground fault PV,
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PhD Research Labs solar project
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Two-Area Load Frequency Control (LFC) using Grey Wolf Fuzzy-PID Controller | MATLAB Simulink Simulation This video presents the modeling and simulation of a Two-Area Power System Load Frequency Control (LFC) using an intelligent hybrid controller — the Grey Wolf Optimization (GWO) tuned Fuzzy-PID Controller implemented in MATLAB/Simulink. The proposed controller improves dynamic performance, frequency stability, and tie-line power oscillation damping compared to conventional PID and Fuzzy controllers. 👨💻 Project Support 🌐 www.matlabprojectscode.com 📧 matlabprojectscode@gmail.com 📱 WhatsApp: +91 8300015425 🔍 Topics Covered Modeling of two-area interconnected thermal power system Governor, turbine, and tie-line power flow representation Fuzzy logic controller for adaptive gain tuning Grey Wolf Optimization (GWO) algorithm for optimal PID parameter selection Simulation of load disturbances and system response Comparison of PID, Fuzzy-PID, and GWO-Fuzzy-PID controllers Performa...
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