Codes for data processing and figure generation used in the paper "Bulk electrical power extraction through tunnel transmission technology from renewable energy concentrated zones"

This sharing contains all the codes for data processing and figure generation used in the paper "Bulk electrical power extraction through tunnel transmission technology from renewable energy concentrated zones", as well as the running programs in both MATLAB and Python. The data required for the operation of these programs is also included in this sharing as Excel files. Single_Cond_Ana processes the single-line simulation data results and enables data visualization for AC, DC XLPE cables, and GIL.ACDC_Temp_Ana and GIL_Temp_Ana respectively process the data operation results of AC/DC cable tunnels and GIL tunnels under various simulation scenarios. With conductor temperature as the constraint, they calculate the maximum current-carrying capacity under different line spatial layouts through data interpolation and realize visual presentation.Venti_AC_All_Final.m processes the ventilation simulation data of AC cable tunnels. Taking conductor temperature and air temperature as constraints, it calculates the maximum current-carrying capacity under various ventilation conditions via data interpolation and achieves visual presentation. The data results generated in this process can be used for Venti_AC_data.py.Venti_DC_All_Final.m processes the ventilation simulation data of DC cable tunnels. With conductor temperature and air temperature as constraints, it computes the maximum current-carrying capacity under different ventilation scenarios through data interpolation and realizes visual presentation. The data results produced during this process can be applied to Venti_DC_data.py.Venti_GIL.m processes the ventilation simulation data of GIL tunnels. Taking conductor temperature, shell temperature, and air temperature as constraints, it calculates the maximum current-carrying capacity under various ventilation conditions using data interpolation and achieves visual presentation. The data results generated in this process can be used for Venti_GIL_data.py.