_DFIG_HVDC.py

# -*- coding: utf-8 -*-
"""
Created on Thu Oct 12 16:50:48 2023

@author: Gregory_Guo
"""

"""
Main Function for Paper: Model Identification of Grid-following System for
Stability Evaluation with Transient Data
"""

from Algo import System_Build as SB
from Tools import Model_Analysis
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import control as ct
from scipy import io
plt.style.use( ['science',"grid","ieee"])

color_dict = {
    "classic":[(205/255,92/255,92/255),(60/255,179/255,113/255),(65/255,105/255,225/255)],
    "千里江山":[(117/255,159/255,107/255),(189/255,144/255,43/255),(70/255,141/255,165/255)],
    "琉璃":[(145/255,187/255,221/255),(33/255,65/255,107/255),(172/255,75/255,71/255)],
    "天青":[(70/255,128/255,139/255),(143/255,209/255,225/255),(194/255,225/255,230/255)],
    "玄泽":[(143/255,110/255,103/255),(220/255,169/255,104/255),(56/255,5/255,9/255)]
    }


########################################################
###############   DFIG & HVDC Operation   ##############
########################################################

Block_num = 24
Algebra_num = 17

### Algorithm Parameters
Time_windows = 0.2       # [s] simulation time
Shift_windows = 0.09      # [s] simulation time

m = r"C:\Users\29639\Desktop\研二上研究\上海会议\coding\System_DFIG_HVDC.csv"  # files root
source = ('PowerFactory', m)
windows_num = 3
print("Configure1 Finished...\n")

# System generation
first1 = SB.System('first1', Block_num, Algebra_num, source, 
             windows_num, Time_windows, Shift_windows)

train_list = [1]
print(f"Now train the model with list {train_list[0]} to {train_list[-1]}\n")
first1.Block_generation(train_list, train_list)

# Other processing
print("Now error analysis:\n")
for num in range(Block_num + Algebra_num):
    first1.Blocks[num].Error_analysis()  # Error Analysis


first1_ana = Model_Analysis.Analysis(first1, ['S1UD', 'S1UQ', 'S2UD', 'S2UQ'], ['P_right', 'Qright', 'P_left', 'Qleft'])
first1_ana.Jacobian_mat()
ret = first1_ana.Damp_analysis()
filter_poles = first1_ana.Plot_range_poles(ret[2], [-100,0], [-100,100])


A = first1_ana.state_space.A

B = first1_ana.state_space.B

C = first1_ana.state_space.C

D = first1_ana.state_space.D


mat_file_A = 'A.mat'
mat_file_B = 'B.mat'
mat_file_C = 'C.mat'
mat_file_D = 'D.mat'

io.savemat(mat_file_A, {'A': A})
io.savemat(mat_file_B, {'B': B})
io.savemat(mat_file_C, {'C': C})
io.savemat(mat_file_D, {'D': D})

ct.bode(ct.ss(A,B,C,D)[0,0], dB=True, Hz =True)

print("Now coefficient analysis:\n")

block_num_dominant = [16,17,18,20]
train_series = [[1],[1,2],[1,2,3]]
first1.Coefficient_analysis(block_num_dominant, train_series)

print("Now draw the picture:\n")
Length = int(0.02 * 1e5 - 1)
win_num = 1

first1.Figure_plot(Length, win_num)

first1.Figure_paper_X(Length, [14,15,33,34], 1, [2,2])
first1.Figure_paper_R(Length, [1,3,5,7,16,17,18,20,23], 1, [3,3])

first1.Figure_paper_X(Length, [2,1], 1, [1,2])
first1.Figure_paper_R(Length, [1,2], 1, [2,1])