☀️ Solar Performance Analytics

A Python-based data analytics project that analyzes solar plant performance using historical Performance Ratio (PR) data. The project preprocesses raw solar datasets, computes key performance metrics, and generates insightful visualizations to evaluate plant efficiency over time.

---

📌 Features

• Data preprocessing and cleaning
• Performance Ratio (PR) analysis
• GHI-based scatter plot visualization
• 30-day moving average
• Dynamic Target Budget PR line
• Average PR statistics
• Percentage of PR values above the Target Budget PR
• High-quality PNG output graph

---

📂 Project Structure

solar-performance-analytics/
│
├── data/                     # Input datasets (not included)
├── output/
│   └── output-graph.png      # Generated visualization
├── preprocess.py             # Data preprocessing script
├── visualize.py              # Visualization script
├── processed_data.csv        # Processed dataset (generated)
├── requirements.txt
├── .gitignore
└── README.md

---

🚀 Installation

Clone the repository:

git clone https://github.com/syedmohammedsaad/solar-performance-analytics.git
cd solar-performance-analytics

Install dependencies:

pip install -r requirements.txt

---

📊 Input Dataset

Place the required solar dataset inside the data/ folder before running the project.

Example:

data/
    solar_data.csv

---

▶️ Usage

Step 1: Preprocess the dataset

python preprocess.py

Step 2: Generate visualization

python visualize.py

The generated graph will be saved as:

output/output-graph.png

---

📈 Sample Output

The generated visualization includes:

• Performance Ratio (PR) scatter plot
• GHI-based color coding
• 30-day moving average
• Dynamic Target Budget PR
• Average PR statistics
• Percentage of PR values above Target Budget PR

Sample Visualization

---

🛠 Technologies Used

• Python
• Pandas
• NumPy
• Matplotlib

---

📊 Performance Metrics

The project computes:

• Daily Performance Ratio
• Average PR
• 30-Day Moving Average
• Dynamic Target Budget PR
• Percentage of PR above Target Budget

---

📷 Output

The visualization displays:

• PR scatter plot
• Target Budget PR line
• 30-day moving average
• PR statistics
• Date-wise trend analysis

---

⚠️ Notes

• Input datasets are not included in this repository.
• Place the required dataset inside the data/ directory before running the project.
• Ensure all dependencies are installed before execution.

---

👨‍💻 Author

Syed Mohammed Saad