Data processing and annotation started

README.md

@@ -110,6 +110,13 @@ Measurements are taken at the LCL filter output using the default multimeters em
 - Scenario Selection Bias: The choice of disturbances, parameter ranges, and operating modes defines the distribution of system behaviors represented, which may not fully capture real-world variability.
 - Simplified System Bias: The SIIB system abstracts away network-level complexity, limiting representation of multi-node interactions and large-scale grid behavior.
 
+## 3.3- Data Processing, Wrangling, and Annotation
+
+Data processing for this dataset consists exclusively of post-simulation wrangling; no transformations, normalizations, or alterations of signal values are applied at any stage. The goal is purely organizational: to convert, structure, and package raw simulation outputs into a consistent, reusable format without modifying their physical content.
+
+The Python API for the RMS simulation models in MATLAB Simulink write five signal files directly to disk in CSV format at the end of each simulation run: voltage magnitude in d-q axis (Vd, Vq in kV), current (id, iq in kA), powers (P in MW, Q in kvar), voltage angle (phase angle in radians), and an oscillatory state flag. These files are sampled at 1 ms resolution, yielding approximately 10,001 rows per file for a 10-second simulation. No conversion step is required, MATLAB writes these directly in the target format. The decision to write CSVs directly from Simulink was made to minimize pipeline wrangling and reduce the risk of conversion errors. The Python API for PSCAD writes recorded signals in COMTRADE format first, and a dedicated Python conversion script converts these files to the same 5-CSV structure as the MATLAB outputs. For each simulation run in both MATLAB and PSCAD, Python scripts assemble two scenario descriptor files. One records the disturbance type and timing and the other records the stochastically sampled random load parameters. Two CSV files record the active and reactive power reference time-series applied during the simulation. These files are generated directly from the Python scenario-sampling scripts and written alongside the simulation outputs, ensuring that every scenario folder is self-describing.
+
+Note that the native-resolution PSCAD outputs and the MATLAB outputs are not directly time-aligned. Hence, users working with paired EMT/RMS data must account for this resolution difference explicitly, which is the primary intended use case of this dataset.