Welcome to TSOC Data Analysis’s documentation!
Author: Sustainable Power Systems Lab (SPSL), https://sps-lab.org, contact: info@sps-lab.org
A Python tool for analyzing the TSOC power system operational data from Excel files. The tool provides a modular Python API for load analysis, generator categorization, wind power analysis, reactive power calculations, and representative operating point extraction.
Features
Month-based data filtering for efficient processing of large datasets
Load calculations (Total Load, Net Load) with comprehensive statistics
Wind power analysis with generation statistics and profiles
Generator categorization (Voltage Control vs PQ Control)
Reactive power analysis with comprehensive calculations
Data validation with type checking, limit validation, and gap filling
Representative operating points extraction using K-means clustering with performance optimizations
Comprehensive logging and error handling
Quick Start
from tsoc_data_analysis import execute, extract_representative_ops, extract_representative_ops_enhanced
# Load and analyze data
success, df = execute(month='2024-01', data_dir='raw_data', output_dir='results')
if success:
# Extract representative points (standard method)
rep_df, diagnostics = extract_representative_ops(
df, max_power=450, MAPGL=200, output_dir='results'
)
# Or use enhanced clustering for better quality
enh_rep_df, enh_diagnostics = extract_representative_ops_enhanced(
df, max_power=450, MAPGL=200, output_dir='results_enhanced',
use_enhanced_preprocessing=True, try_alternative_algorithms=True
)