Python study notes (nine) - written in Python flow calculation (polar coordinates)

Foreword

Nothing to made up a load flow calculation, polar coordinates, cattle - Rafah, when it is practiced hands, for your reference ~

1. The main function

# coding=UTF-8
import NetData
from YData import GetY
from InitateU import PolarU
from NewtonRaphson import PolarNR
from OutTxt import SingleTxt,StringTxt
# 获取支路参数
RootPath = 'F:\\FunctionLibrary\\runpfM\\' # 读取文件，得到节点和支路数据 
FilePath_Node = RootPath+'NodeData.txt'    
FilePath_Line = RootPath+'LineData.txt'
Out_Path = 'Cal-Process.txt'
S0 = '-'
for i in range(130):
    S0 = S0+'-' 
StringTxt(path=Out_Path,string=S0+'\n初始化参数：\n',fmt='w')
NodeData = NetData.GetNodeData(FilePath_Node,show=1)
LineData = NetData.GetLineData(FilePath_Line,show=1)
# 节点导纳矩阵
Y = GetY(NodeData,LineData,path=Out_Path,width=6)
# 初始化
U,Angle = PolarU(NodeData[:,8],NodeData[:,9],path=Out_Path,width=9)
# 开始计算
PQNode,PVNode,SlackNode,P_Real,Q_Real = NetData.GetNetData(NodeData,LineData,path=Out_Path)
Iter = 0
MaxIter = 10
Tol = 1e-4
while True:
    Iter = Iter+1
    StringTxt(path=Out_Path,string='\n\n'+S0)
    SingleTxt(Iter,path=Out_Path,string='迭代次数：')
    U,Angle,MaxError = PolarNR(U,Angle,Y,PQNode,PVNode,SlackNode,P_Real,Q_Real,Tol,path=Out_Path,width=9)
    if Iter>MaxIter or MaxError<Tol:
        break
# 结束循环，输出结果
if MaxError<Tol:
    SingleTxt(Iter-1,path=Out_Path,string='迭代完成，更新次数为：')
    SingleTxt(MaxError,path=Out_Path,string='最大误差为：')
else:
    SingleTxt(MaxError,path=Out_Path,string='结果不收敛!')

2. Obtain the network parameters

# coding=UTF-8
import numpy as np
#----------------------------NodeData-------------------------#
# NodeData: bus_i type Pd Qd Pg Qg Gs Bs Vm Va
# bus_i为节点编号
# Pd和Qd为节点的负荷功率
# Pg和Qg为节点的发电机输出功率
# Gs和Bs为节点对地电导和电纳
# Vm为电压幅值，Va为电压相角
def GetNumNode(FilePath_Node):
    with open(FilePath_Node,'r') as file:  
        NumNode = 0
        for line in file: 
            NumNode = NumNode+1  # 得到节点数目
        print('节点数目：',NumNode)
    return(NumNode)
def GetNodeData(FilePath_Node,*NumNode,**PlotOption):
    if not NumNode:  # 空的
        NumNode = GetNumNode(FilePath_Node)
    NodeData = np.zeros([NumNode,10]) # 初始化
    i = 0
    with open(FilePath_Node,'r') as file:  
        for line in file:
            NodeData[i,:] = np.array([float(i) for i in line.split()])
            i = i+1
    if 'show' in PlotOption and PlotOption['show'] == 1:
        print('NodeData=',NodeData)
    return(NodeData) 

#----------------------------LineData------------------------#
# LineData:fbus  tbus   r    x    b    ratio
# fbus为起始节点
# tbus为终止节点
# r为支路电阻
# x为支路电抗
# b为节点对地导纳
# ratio为变压器变比
def GetNumLine(FilePath_Line):
    with open(FilePath_Line,'r') as file:  
        NumLine = 0
        for line in file: 
            NumLine = NumLine+1  # 得到节点数目
        print('支路数目：',NumLine)
    return(NumLine)

def GetLineData(FilePath_Line,*NumLine,**PlotOption):
    if not NumLine:  # 空的
        NumLine = GetNumLine(FilePath_Line)
    LineData = np.zeros([NumLine,6]) # 初始化
    i = 0
    with open(FilePath_Line,'r') as file:  
        for line in file:
            LineData[i,:] = np.array([float(i) for i in line.split()])
            i = i+1
    if 'show' in PlotOption and PlotOption['show'] == 1:
        print('LineData = ',LineData)
    return(LineData) 
#-输出网络参数--------#
def GetNetData(NodeData,LineData,**Option):
    PQNode = NodeData[np.where(NodeData[:,1]==1),0] # PQ节点
    PVNode = NodeData[np.where(NodeData[:,1]==2),0] # PV节点
    SlackNode = NodeData[np.where(NodeData[:,1]==3),0] # 平衡节点
    # SlackNode = SlackNode[0]
    # print(SlackNode)
    P_Real = -NodeData[:,2]+NodeData[:,4]  # 节点输入有功功率
    Q_Real = -NodeData[:,3]+NodeData[:,5]  # 节点输入无功功率
    from OutTxt import Real
    flag = 0
    if 'string' not in Option:
        flag = 1
        Option['string'] = 'PQ节点：\n'
    Real(PQNode,**Option)
    if flag:
        Option['string'] = 'PV节点：\n'
    Real(PVNode,**Option)
    if flag:
        Option['string'] = '平衡节点：\n'
    Real(SlackNode,**Option)
    if flag:
        Option['string'] = '注入节点有功功率：\n'
    Real(P_Real,**Option)
    if flag:
        Option['string'] = '注入节点无功功率：\n'
    Real(Q_Real,**Option)
    return(PQNode,PVNode,SlackNode,P_Real,Q_Real)

3. The node admittance matrix

# coding=UTF-8
# 形成节点导纳矩阵
# NodeData: bus_i type Pd Qd Pg Qg Gs Bs Vm Va
# LineData: fbus  tbus r  x  b_2  ratio
import numpy as np
import OutTxt
def GetY(NodeData,LineData,**Option):
    NumNode = NodeData.shape[0]
    NumLine = LineData.shape[0]
    Y = np.zeros([NumNode,NumNode])+np.zeros([NumNode,NumNode])*1j
    G0 = NodeData[:,6]  # 节点对地电导
    B0 = NodeData[:,7]  # 节点对地电纳
    for i in range(NumLine):
        Node1 = int(LineData[i,0]-1)
        Node2 = int(LineData[i,1]-1)
        # print(Node1,Node2)
        R = LineData[i,2] 
        X = LineData[i,3] 
        if LineData[i,5]==0:   # 普通线路，无变压器
            B_2 = LineData[i,4] 
            Y[Node1,Node1] = Y[Node1,Node1]+B_2*1j+1/(R+1j*X) 
            Y[Node2,Node2] = Y[Node2,Node2]+B_2*1j+1/(R+1j*X) 
            Y[Node1,Node2] = Y[Node1,Node2]-1/(R+1j*X) 
            Y[Node2,Node1] = Y[Node2,Node1]-1/(R+1j*X) 
        else:  # 有变压器支路
            K  = LineData[i,5] 
            YT = 1/(R+1j*X) 
            Y[Node1,Node1] = Y[Node1,Node1]+(K-1)/K*YT+YT/K 
            Y[Node2,Node2] = Y[Node2,Node2]+(1-K)/K**2*YT+YT/K 
            Y[Node1,Node2] = Y[Node1,Node2]-1/K*YT 
            Y[Node2,Node1] = Y[Node2,Node1]-1/K*YT 
    for i in range(NumLine):
        Node = int(NodeData[i,0]-1)   # 第一列为节点编号
        Y[Node,Node] = Y[Node,Node]+G0[i]+1j*B0[i] 
    #----------输出到txt文件--------#
    if 'string' not in Option:
        Option['string'] = 'Y矩阵：\n'
    OutTxt.Complex(Y,**Option)  # 元组
    return(Y)

4. The initialization voltage

# coding=UTF-8
#---------------极坐标形式----------------#
from numpy import cos,sin,angle
import OutTxt
def PolarU(U_Amplitude,U_Angle,**Option):          
    U_Complex = U_Amplitude*cos(U_Angle)+U_Amplitude*sin(U_Angle)*1j
    U = abs(U_Complex)
    Angle = angle(U_Complex)
    if 'string' not in Option:
        Option['string'] = '\n电压初始化为：\n'
        OutTxt.Complex(U_Complex,**Option)    
    return(U,Angle)

#---------------直角坐标形式--------------#    
def RectanU(U_Amplitude,U_Angle,**Option):
    U_e = U_Amplitude*cos(U_Angle)
    U_f = U_Amplitude*cos(U_Angle)
    if 'string' not in Option:
        Option['string'] = '\n 电压实部初始化为：\n'
        OutTxt.Real(U_e,**Option)
        Option['string'] = '\n 电压虚部初始化为：\n'
        OutTxt.Real(U_f,**Option)
    return(U_e,U_f)

4. Bovine - pull Solving

# coding=UTF-8
# 形成节点导纳矩阵
import numpy as np
from OutTxt import Real
def PolarNR(U,Angle,Y,PQNode,PVNode,SlackNode,P_Real,Q_Real,Tol,**Option):
    P_iter = 0  # 为形成雅可比矩阵
    Q_iter = 0  # 为形成雅可比矩阵
    PQNode = PQNode-1
    PVNode = PVNode-1
    SlackNode = SlackNode-1
    NumNode = Y.shape[0] # 节点数目
    NumPQ = max(PQNode.shape) # PQ节点数目
    G = Y.real
    B = Y.imag
    P = np.zeros([NumNode,1])
    Q = np.zeros([NumNode,1])
    DeltaP = np.zeros([NumNode-1,1])
    DeltaQ = np.zeros([NumPQ,1])
    for i in range(NumNode):  # 求解功率不平衡量
        P[i] = U[i]*np.sum(U*(G[i,:]*np.cos(Angle[i]-Angle) +  B[i,:]*np.sin(Angle[i]-Angle)))
        Q[i] = U[i]*np.sum(U*(G[i,:]* np.sin(Angle[i]-Angle) -  B[i,:]*np.cos(Angle[i]-Angle)))
        if i!=SlackNode:    # 不是平衡节点
            DeltaP[P_iter] = P_Real[i]-P[i]  # NumPQ+NumPV
            if i in PQNode:    # PQ节点
                DeltaQ[Q_iter] = Q_Real[i]-Q[i] # NumPQ
                Q_iter = Q_iter+1
            P_iter = P_iter+1
    DeltaPQ = np.vstack([DeltaP,DeltaQ])  # 功率不平衡量
    Option['string'] = '功率不平衡量为：\n'
    Real(DeltaPQ,**Option)
    MaxError = np.max(np.abs(DeltaPQ))
    print(MaxError)
    if MaxError<Tol:
        return(U,Angle,MaxError)
    ## H and N     
    HN_iter = -1   # 初始化雅可比矩阵
    H = np.zeros([NumNode-1,NumNode-1])
    N = np.zeros([NumNode-1,NumPQ])
    # H and N
    for i in range(NumNode):
        if i!=SlackNode:  # PQ或PV节点
            H_iter_y = -1 
            N_iter_y = -1
            HN_iter = HN_iter+1  # 记录H和N的行数
            for j in range(NumNode):
                if j != SlackNode:
                    H_iter_y = H_iter_y+1  # 记录H列数
                    if i != j:   # 非平衡节点计算H矩阵
                        Angleij = Angle[i]-Angle[j]
                        H[HN_iter,H_iter_y] = -U[i]*U[j]*(G[i,j]*np.sin(Angleij)-B[i,j]*np.cos(Angleij))
                    else:
                        H[HN_iter,H_iter_y] = Q[i]+U[i]**2*B[i,i]
                    if j in PQNode:
                        N_iter_y = N_iter_y+1  # 记录N的列数
                        if i != j:
                            Angleij = Angle[i]-Angle[j]
                            N[HN_iter,N_iter_y] = -U[i]*U[j]*(G[i,j]*np.cos(Angleij)+B[i,j]*np.sin(Angleij))
                        else:
                            N[HN_iter,N_iter_y] = -P[i]-G[i,i]*U[i]**2
    ## J and L
    JL_iter = -1   # 初始化雅可比矩阵
    J = np.zeros([NumPQ,NumNode-1])
    L = np.zeros([NumPQ,NumPQ])
    for i in range(NumNode):
        if i in PQNode:    # PQ节点
            JL_iter = JL_iter+1 # J和L的行数
            J_iter_y = -1
            L_iter_y = -1
            for j in range(NumNode):
                if j!=SlackNode:  # 非平衡节点
                    J_iter_y = J_iter_y+1
                    if i!=j:
                        Angleij = Angle[i]-Angle[j]
                        J[JL_iter,J_iter_y] = U[i]*U[j]*(G[i,j]*np.cos(Angleij)+B[i,j]*np.sin(Angleij))
                    else:
                        J[JL_iter,J_iter_y] = -P[i]+G[i,i]*U[i]**2
                    if j in PQNode:  # PQ节点
                        L_iter_y = L_iter_y+1
                        if i!=j:
                            Angleij = Angle[i]-Angle[j]
                            L[JL_iter,L_iter_y] = -U[i]*U[j]*(G[i,j]*np.sin(Angleij)-B[i,j]*np.cos(Angleij))
                        else:
                            L[JL_iter,L_iter_y] = -Q[i]+B[i,i]*U[i]**2
    # 修正
    Jaccobi = np.vstack([np.hstack([H,N]),np.hstack([J,L])])
    Option['string'] = 'jacobi矩阵为：\n'
    Real(Jaccobi,**Option)
    Delta = np.linalg.solve(Jaccobi,DeltaPQ)
    Option['string'] = '方程组求解结果：\n'
    Real(Delta,**Option)
    DeltaAngle = Delta[0:NumNode-1]  # 注意下标
    DeltaU_U = Delta[NumNode-1:]
    DA_iter = -1
    U_U_iter = -1
    for i in range(NumNode):
        if i!=SlackNode:
            DA_iter = DA_iter+1
            Angle[i] = Angle[i]-DeltaAngle[DA_iter]
            if i in PQNode:
                U_U_iter = U_U_iter+1
                U[i] = U[i]-U[i]*DeltaU_U[U_U_iter]
    Option['string'] = '更新之后的电压幅值为：\n'
    Real(U,**Option)
    Option['string'] = '相角为：\n'
    Real(Angle,**Option)
    return(U,Angle,MaxError)

5. Output File

# coding=UTF-8
def ArgOption(**Option):       # 解析可选参数
    if 'string' in Option:
        String = Option['string']
    else:
        String = '输出的矩阵：\n'  # 默认值
    if 'path' in Option:
        FilePath = Option['path']
    else:
        FilePath = 'untitled.txt'  # 默认为未命名的
    if 'width' in Option:
        N = Option['width']
    else:
        N = 8   # 默认值
    if 'fmt' in Option:
        Fmt = Option['fmt']
    else:
        Fmt = 'a'    # 默认值
    return(String,FilePath,N,Fmt)

#---------------------实数矩阵-----------------------#
def Real(Matrix,**Option):
    string,FilePath,N,Fmt = ArgOption(**Option)
    with open(FilePath,Fmt) as file:
        file.write(string)
        Ndim = Matrix.ndim
        if Ndim == 1:   # (Num)
            Num = Matrix.shape[0]
            for i in range(Num): 
                file.write(str(Dot10(Matrix[i])).ljust(N+1)[0:N-1])
                file.write('  ')
            file.write('\n')
        elif Ndim == 2: # ([NumR,NumC])
            NumR,NumC = Matrix.shape
            for i in range(NumR):
                for j in range(NumC):
                    file.write(str(Dot10(Matrix[i,j])).ljust(N+1)[0:N-1])
                    file.write('  ')
                file.write('\n')

#-------------------复数矩阵-----------------------#          
def Complex(Matrix,**Option):
    string,FilePath,N,Fmt = ArgOption(**Option)
    RealM = Matrix.real
    ImagM = Matrix.imag
    # print(FilePath)
    with open(FilePath,Fmt) as file:
        file.write(string) 
        Ndim = Matrix.ndim
        if Ndim == 1:   # (Num)
            Num = Matrix.shape[0]
            for i in range(Num):
                file.write(str(Dot10(RealM[i])).ljust(N+1)[0:N-1])
                file.write('+')
                file.write('j'+str(Dot10(ImagM[i])).ljust(N+1)[0:N-1])
                file.write('  ')
            file.write('\n')
        elif Ndim == 2: # ([NumR,NumC])
            NumR,NumC = Matrix.shape
            for i in range(NumR):
                for j in range(NumC):
                    file.write(str(Dot10(RealM[i,j])).ljust(N+1)[0:N-1])
                    file.write('+')
                    file.write('j'+str(Dot10(ImagM[i,j])).ljust(N+1)[0:N-1])
                    file.write('  ')
                file.write('\n')
#--单变量-----------------------#
def SingleTxt(Number,**Option):
    string,FilePath,N,Fmt = ArgOption(**Option)
    with open(FilePath,Fmt) as file:
        file.write(string)
        file.write(str(Dot10(Number)).ljust(N+1)[0:N-1])
        file.write('\n')
#--字符串-----------------------#
def StringTxt(**Option):
    string,FilePath,N,Fmt = ArgOption(**Option)
    with open(FilePath,Fmt) as file:
        file.write(string)
        file.write('\n')
#--小数点后保留位数---
def Dot10(x):
    if isinstance(x,int):  # 整数的话，就不用变为浮点数
        return(x)
    else:
        return('{:.10f}'.format(x))

6. screen output

节点数目： 9
NodeData= [[1.    1.    1.25  0.5   0.    0.    0.    0.    1.    0.   ]
 [2.    1.    0.    0.    0.    0.    0.    0.    1.    0.   ]
 [3.    1.    0.9   0.3   0.    0.    0.    0.    1.    0.   ]
 [4.    1.    0.    0.    0.    0.    0.    0.    1.    0.   ]
 [5.    1.    1.    0.35  0.    0.    0.    0.    1.    0.   ]
 [6.    1.    0.    0.    0.    0.    0.    0.    1.    0.   ]
 [7.    2.    0.    0.    1.63  0.    0.    0.    1.025 0.   ]
 [8.    2.    0.    0.    0.85  0.    0.    0.    1.025 0.   ]
 [9.    3.    0.    0.    0.    0.    0.    0.    1.04  0.   ]]
支路数目： 9
LineData =  [[1.    2.    0.01  0.085 0.088 0.   ]
 [1.    6.    0.032 0.161 0.153 0.   ]
 [2.    3.    0.017 0.092 0.079 0.   ]
 [2.    9.    0.    0.058 0.    1.   ]
 [3.    4.    0.039 0.17  0.179 0.   ]
 [4.    5.    0.012 0.101 0.105 0.   ]
 [4.    8.    0.    0.059 0.    1.   ]
 [5.    6.    0.019 0.072 0.075 0.   ]
 [6.    7.    0.    0.063 0.    1.   ]]
1.63
0.18620555300855945
0.002147363829061549
3.6215137443425437e-07

7.txt file output

-----------------------------------------------------------------------------------------------------------------------------------
初始化参数：

Y矩阵：
2.552+j-17.3  -1.36+j11.60  0.000+j0.000  0.000+j0.000  0.000+j0.000  -1.18+j5.975  0.000+j0.000  0.000+j0.000  0.000+j0.000  
-1.36+j11.60  3.307+j-39.1  -1.94+j10.51  0.000+j0.000  0.000+j0.000  0.000+j0.000  0.000+j0.000  0.000+j0.000  0.000+j17.24  
0.000+j0.000  -1.94+j10.51  3.224+j-15.8  -1.28+j5.588  0.000+j0.000  0.000+j0.000  0.000+j0.000  0.000+j0.000  0.000+j0.000  
0.000+j0.000  0.000+j0.000  -1.28+j5.588  2.441+j-32.0  -1.15+j9.763  0.000+j0.000  0.000+j0.000  0.000+j16.94  0.000+j0.000  
0.000+j0.000  0.000+j0.000  0.000+j0.000  -1.15+j9.763  4.586+j-22.5  -3.42+j12.98  0.000+j0.000  0.000+j0.000  0.000+j0.000  
-1.18+j5.975  0.000+j0.000  0.000+j0.000  0.000+j0.000  -3.42+j12.98  4.614+j-34.6  0.000+j15.87  0.000+j0.000  0.000+j0.000  
0.000+j0.000  0.000+j0.000  0.000+j0.000  0.000+j0.000  0.000+j0.000  0.000+j15.87  0.000+j-15.8  0.000+j0.000  0.000+j0.000  
0.000+j0.000  0.000+j0.000  0.000+j0.000  0.000+j16.94  0.000+j0.000  0.000+j0.000  0.000+j0.000  0.000+j-16.9  0.000+j0.000  
0.000+j0.000  0.000+j17.24  0.000+j0.000  0.000+j0.000  0.000+j0.000  0.000+j0.000  0.000+j0.000  0.000+j0.000  0.000+j-17.2  

电压初始化为：
1.000000+j0.000000  1.000000+j0.000000  1.000000+j0.000000  1.000000+j0.000000  1.000000+j0.000000  1.000000+j0.000000  1.025000+j0.000000  1.025000+j0.000000  1.040000+j0.000000  
PQ节点：
1.00000  2.00000  3.00000  4.00000  5.00000  6.00000  
PV节点：
7.00000  8.00000  
平衡节点：
9.00000  
注入节点有功功率：
-1.2500  0.00000  -0.9000  0.00000  -1.0000  0.00000  1.63000  0.85000  0.00000  
注入节点无功功率：
-0.5000  0.00000  -0.3000  0.00000  -0.3500  0.00000  0.00000  0.00000  0.00000  


-----------------------------------------------------------------------------------------------------------------------------------
迭代次数：1      
功率不平衡量为：
-1.25000  
0.000000  
-0.90000  
0.000000  
-1.00000  
0.000000  
1.630000  
0.850000  
-0.25900  
0.856655  
-0.04200  
0.707728  
-0.17000  
0.624825  
jacobi矩阵为：
-17.5792  11.60409  -0.00000  -0.00000  -0.00000  5.975134  -0.00000  -0.00000  -2.55279  1.365187  -0.00000  -0.00000  -0.00000  1.187604  
11.60409  -40.0458  10.51068  -0.00000  -0.00000  -0.00000  -0.00000  -0.00000  1.365187  -3.30737  1.942191  -0.00000  -0.00000  -0.00000  
-0.00000  10.51068  -16.0989  5.588244  -0.00000  -0.00000  -0.00000  -0.00000  -0.00000  1.942191  -3.22420  1.282009  -0.00000  -0.00000  
-0.00000  -0.00000  5.588244  -32.7242  9.763170  -0.00000  -0.00000  17.37288  -0.00000  -0.00000  1.282009  -2.44198  1.159980  -0.00000  
-0.00000  -0.00000  -0.00000  9.763170  -22.7478  12.98467  -0.00000  -0.00000  -0.00000  -0.00000  -0.00000  1.159980  -4.58649  3.426510  
5.975134  -0.00000  -0.00000  -0.00000  12.98467  -35.2296  16.26984  -0.00000  1.187604  -0.00000  -0.00000  -0.00000  3.426510  -4.61411  
-0.00000  -0.00000  -0.00000  -0.00000  -0.00000  16.26984  -16.2698  -0.00000  -0.00000  -0.00000  -0.00000  -0.00000  -0.00000  -0.00000  
-0.00000  -0.00000  -0.00000  17.37288  -0.00000  -0.00000  -0.00000  -17.3728  -0.00000  -0.00000  -0.00000  -0.00000  -0.00000  -0.00000  
2.552792  -1.36518  0.000000  0.000000  0.000000  -1.18760  0.000000  0.000000  -17.0972  11.60409  -0.00000  -0.00000  -0.00000  5.975134  
-1.36518  3.307378  -1.94219  0.000000  0.000000  0.000000  0.000000  0.000000  11.60409  -38.3325  10.51068  -0.00000  -0.00000  -0.00000  
0.000000  -1.94219  3.224200  -1.28200  0.000000  0.000000  0.000000  0.000000  -0.00000  10.51068  -15.5829  5.588244  -0.00000  -0.00000  
0.000000  0.000000  -1.28200  2.441989  -1.15998  0.000000  0.000000  0.000000  -0.00000  -0.00000  5.588244  -31.3088  9.763170  -0.00000  
0.000000  0.000000  0.000000  -1.15998  4.586491  -3.42651  0.000000  0.000000  -0.00000  -0.00000  -0.00000  9.763170  -22.3878  12.98467  
-1.18760  0.000000  0.000000  0.000000  -3.42651  4.614114  0.000000  0.000000  5.975134  -0.00000  -0.00000  -0.00000  12.98467  -33.9799  
方程组求解结果：
0.067047  
0.037365  
0.063033  
-0.04188  
-0.01900  
-0.07300  
-0.17318  
-0.09080  
-0.00902  
-0.03343  
-0.02187  
-0.03861  
-0.02232  
-0.03884  
更新之后的电压幅值为：
1.009020  1.033434  1.021873  1.038614  1.022326  1.038845  1.025000  1.025000  1.040000  
相角为：
-0.06704  -0.03736  -0.06303  0.041882  0.019005  0.073003  0.173189  0.090808  0.000000  


-----------------------------------------------------------------------------------------------------------------------------------
迭代次数：2      
功率不平衡量为：
0.039962  
-0.01068  
0.042708  
-0.02549  
0.052979  
-0.04120  
-0.06048  
-0.03247  
-0.07164  
-0.05002  
-0.04221  
-0.08189  
-0.02740  
-0.18620  
jacobi矩阵为：
-18.0808  12.05267  0.000000  0.000000  0.000000  6.028138  0.000000  0.000000  -1.30909  1.782033  -0.00000  -0.00000  -0.00000  2.106986  
12.13716  -41.8034  11.14866  0.000000  0.000000  0.000000  0.000000  0.000000  1.063829  -3.54292  1.765476  -0.00000  -0.00000  -0.00000  
-0.00000  11.04338  -16.7992  5.755881  0.000000  0.000000  0.000000  0.000000  -0.00000  2.335229  -2.42408  1.974267  -0.00000  -0.00000  
-0.00000  -0.00000  6.040862  -34.4550  10.39202  0.000000  0.000000  18.02213  -0.00000  -0.00000  0.732043  -2.65971  0.994216  -0.00000  
-0.00000  -0.00000  -0.00000  10.33567  -23.9093  13.57371  0.000000  0.000000  -0.00000  -0.00000  -0.00000  1.468480  -3.74059  4.378073  
6.375689  -0.00000  -0.00000  -0.00000  13.96653  -37.1593  16.81710  0.000000  0.358370  -0.00000  -0.00000  -0.00000  2.889494  -5.02075  
-0.00000  -0.00000  -0.00000  -0.00000  -0.00000  16.81710  -16.8171  -0.00000  -0.00000  -0.00000  -0.00000  -0.00000  -0.00000  -1.69048  
-0.00000  -0.00000  -0.00000  18.02213  -0.00000  -0.00000  0.000000  -18.0221  -0.00000  -0.00000  -0.00000  -0.88247  -0.00000  -0.00000  
3.889020  -1.78203  0.000000  0.000000  0.000000  -2.10698  0.000000  0.000000  -17.2241  12.05267  0.000000  0.000000  0.000000  6.028138  
-1.06382  3.521544  -1.76547  0.000000  0.000000  0.000000  0.000000  0.000000  12.13716  -41.9034  11.14866  0.000000  0.000000  0.000000  
0.000000  -2.33522  4.309497  -1.97426  0.000000  0.000000  0.000000  0.000000  -0.00000  11.04338  -16.2837  5.755881  0.000000  0.000000  
0.000000  0.000000  -0.73204  2.608730  -0.99421  0.000000  0.000000  -0.88247  -0.00000  -0.00000  6.040862  -34.6188  10.39202  0.000000  
0.000000  0.000000  0.000000  -1.46848  5.846554  -4.37807  0.000000  0.000000  -0.00000  -0.00000  -0.00000  10.33567  -23.2642  13.57371  
-0.35837  0.000000  0.000000  0.000000  -2.88949  4.938352  -1.69048  0.000000  6.375689  -0.00000  -0.00000  -0.00000  13.96653  -37.5317  
方程组求解结果：
0.003254  
0.001876  
0.002173  
0.008650  
0.007655  
0.009333  
0.011816  
0.010095  
0.012547  
0.007307  
0.009379  
0.007281  
0.010495  
0.011073  
更新之后的电压幅值为：
0.996360  1.025882  1.012288  1.031051  1.011596  1.027341  1.025000  1.025000  1.040000  
相角为：
-0.07030  -0.03924  -0.06520  0.033231  0.011350  0.063670  0.161372  0.080713  0.000000  


-----------------------------------------------------------------------------------------------------------------------------------
迭代次数：3      
功率不平衡量为：
0.000539  
0.000159  
0.000522  
-0.00067  
0.000757  
-0.00119  
-0.00045  
-0.00018  
-0.00120  
-0.00043  
-0.00062  
-0.00068  
-0.00043  
-0.00214  
jacobi矩阵为：
-17.7110  11.81205  0.000000  0.000000  0.000000  5.898982  0.000000  0.000000  -1.28370  1.763095  -0.00000  -0.00000  -0.00000  2.021687  
11.89872  -41.2436  10.96391  0.000000  0.000000  0.000000  0.000000  0.000000  1.026408  -3.48064  1.732883  -0.00000  -0.00000  -0.00000  
-0.00000  10.85918  -16.5320  5.672834  0.000000  0.000000  0.000000  0.000000  -0.00000  2.299646  -2.40340  1.904805  -0.00000  -0.00000  
-0.00000  -0.00000  5.935842  -34.0350  10.20710  0.000000  0.000000  17.89215  -0.00000  -0.00000  0.758361  -2.59667  0.986777  -0.00000  
-0.00000  -0.00000  -0.00000  10.15415  -23.4438  13.28969  0.000000  0.000000  -0.00000  -0.00000  -0.00000  1.432382  -3.69272  4.261856  
6.223731  -0.00000  -0.00000  -0.00000  13.66215  -36.5208  16.63497  0.000000  0.387795  -0.00000  -0.00000  -0.00000  2.850435  -4.87107  
-0.00000  -0.00000  -0.00000  -0.00000  -0.00000  16.63497  -16.6349  -0.00000  -0.00000  -0.00000  -0.00000  -0.00000  -0.00000  -1.63045  
-0.00000  -0.00000  -0.00000  17.89215  -0.00000  -0.00000  0.000000  -17.8921  -0.00000  -0.00000  -0.00000  -0.85018  -0.00000  -0.00000  
3.784782  -1.76309  0.000000  0.000000  0.000000  -2.02168  0.000000  0.000000  -16.7134  11.81205  0.000000  0.000000  0.000000  5.898982  
-1.02640  3.480961  -1.73288  0.000000  0.000000  0.000000  0.000000  0.000000  11.89872  -41.2444  10.96391  0.000000  0.000000  0.000000  
0.000000  -2.29964  4.204452  -1.90480  0.000000  0.000000  0.000000  0.000000  -0.00000  10.85918  -15.9332  5.672834  0.000000  0.000000  
0.000000  0.000000  -0.75836  2.595327  -0.98677  0.000000  0.000000  -0.85018  -0.00000  -0.00000  5.935842  -34.0364  10.20710  0.000000  
0.000000  0.000000  0.000000  -1.43238  5.694238  -4.26185  0.000000  0.000000  -0.00000  -0.00000  -0.00000  10.15415  -22.7447  13.28969  
-0.38779  0.000000  0.000000  0.000000  -2.85043  4.868688  -1.63045  0.000000  6.223731  -0.00000  -0.00000  -0.00000  13.66215  -36.5251  
方程组求解结果：
0.000061  
0.000028  
0.000047  
0.000162  
0.000151  
0.000182  
0.000196  
0.000169  
0.000176  
0.000092  
0.000121  
0.000083  
0.000133  
0.000141  
更新之后的电压幅值为：
0.996184  1.025787  1.012166  1.030965  1.011461  1.027196  1.025000  1.025000  1.040000  
相角为：
-0.07036  -0.03926  -0.06525  0.033068  0.011198  0.063488  0.161176  0.080544  0.000000  


-----------------------------------------------------------------------------------------------------------------------------------
迭代次数：4      
功率不平衡量为：
0.000000  
0.000000  
0.000000  
-0.00000  
0.000000  
-0.00000  
-0.00000  
-0.00000  
-0.00000  
-0.00000  
-0.00000  
-0.00000  
-0.00000  
-0.00000  
迭代完成，更新次数为：3      
最大误差为：0.00000

7. Summary

• (1) function of the parameters passed python very good use, can learn a learning;
• (2) numpy very strong (~ feel then let matlab);
• (3) a feeling similar provision can be dedicated packet matpower the python, expected ~;
• (4) as a whole is not difficult, but some details need a little pondering what;

Note: You can also download the code

Disclaimer: This article is a blogger original article, shall not be reproduced without the bloggers allowed.