Author: Sustainable Power Systems Lab (SPSL), https://sps-lab.org, contact: info@sps-lab.org
A comprehensive Python tool for analyzing TSOC power system operational data from Excel files. Provides a powerful command-line interface (CLI) and modular Python API for load analysis, generator categorization, wind power analysis, reactive power calculations, and representative operating point extraction.
For complete installation instructions, detailed usage examples, configuration options, and troubleshooting, visit:
https://tsoc-data-analysis.sps-lab.org/
pip install tsoc-data-analysisfrom tsoc_data_analysis import execute, extract_representative_ops
# Load and analyze data
success, df = execute(month='2024-01', data_dir='raw_data', output_dir='results')
if success:
# Extract representative points
rep_df, diagnostics = extract_representative_ops(
df, max_power=450, MAPGL=200, output_dir='results'
)- Month-based data filtering for efficient processing
- Load calculations (Total Load, Net Load) with statistics
- Wind power analysis with generation profiles
- Generator categorization (Voltage Control vs PQ Control)
- Reactive power analysis with comprehensive calculations
- Data validation with advanced gap filling and anomaly detection
- Representative operating points extraction using K-means clustering
- Comprehensive logging and error handling
- Python 3.7+
- pandas>=1.3.0, numpy>=1.20.0, matplotlib>=3.3.0, seaborn>=0.11.0
- openpyxl>=3.0.0, scikit-learn>=1.0.0, scipy>=1.7.0
- psutil>=5.8.0, joblib>=1.1.0
- Installation Guide - Detailed setup instructions
- User Guide - Getting started and basic workflow
- Configuration Guide - Customizing system parameters
- Examples - Code examples and workflows
- Troubleshooting - Common issues and solutions
For detailed information, examples, and troubleshooting, please visit the full documentation.
Licensed under the Apache License 2.0. See LICENSE for details.