Updating and cleaning the code
This commit is contained in:
Sadam93
parent
9a063edd11
commit
c5d67b9d80
142
opf_losses_v2.py
142
opf_losses_v2.py
@ -1,21 +1,15 @@
|
||||
### this code is for OPF with voltage graph
|
||||
import itertools
|
||||
|
||||
import numpy as np
|
||||
import pyomo.environ as py
|
||||
import matplotlib as plt
|
||||
import matplotlib.pyplot as plt
|
||||
import pandas as pd
|
||||
import pylab as pl
|
||||
# to ignore the warning for dividing by 0
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
from matplotlib import pyplot as plt
|
||||
from matplotlib import cm
|
||||
from pyomo.core import Objective
|
||||
|
||||
|
||||
|
||||
# to ignore the warning for dividing by 0
|
||||
np.seterr(divide='ignore', invalid='ignore')
|
||||
|
||||
############################################################First Step#############################################
|
||||
# impedance matrix
|
||||
# importing the data from the excel for the bus
|
||||
@ -46,7 +40,6 @@ for y in range(len(dataimpedence)):
|
||||
print(shunt_matrix)
|
||||
|
||||
# converting the impedance to admittance
|
||||
|
||||
yb = -1 / Imp_matrix
|
||||
yb[np.isnan(yb)] = 0
|
||||
|
||||
@ -62,8 +55,7 @@ y_offdiagonal = pyb
|
||||
y_offdiagonal_sum = np.sum(y_offdiagonal, axis=1)
|
||||
# print(y_offdiagonal_sum)
|
||||
|
||||
# now i will add the y_offdiagonal_sum with shunt_matrix_sum for diagonal matrix
|
||||
|
||||
# now adding the y_offdiagonal_sum with shunt_matrix_sum for diagonal matrix
|
||||
yii = np.add(shunt_matrix_sum, y_offdiagonal_sum) # get the diaginal matrix
|
||||
# print(yii)
|
||||
|
||||
@ -73,7 +65,6 @@ ybus = yb
|
||||
print('Y bus: ', ybus)
|
||||
|
||||
# calculating the magnitude and angle of ybus matrix
|
||||
|
||||
y_mag = abs(ybus)
|
||||
print('Y bus magnitude : ', y_mag)
|
||||
y_rad = np.angle(ybus)
|
||||
@ -92,7 +83,6 @@ print('Susseptance: ', ybus_imag)
|
||||
|
||||
|
||||
# optimal power flow
|
||||
|
||||
model = py.ConcreteModel()
|
||||
# Set
|
||||
# model.b = py.Set(initialize=[0, 1, 2, 3, 4], doc='bus')
|
||||
@ -112,20 +102,7 @@ model.qdmand = py.Param(model.b, model.t, initialize=dict(
|
||||
zip(list(itertools.product(range(1, len(databus.bus.values) + 1), range(1, len(model.t.data()) + 1))),
|
||||
np.append(datademand.reactive_power.values, len(model.t.data())))),
|
||||
doc='Reactive power demand')
|
||||
# fixed demand
|
||||
# model.pdmand = py.Param(model.b, model.t, initialize=dict(
|
||||
# zip(list(itertools.product(range(1,len(databus.bus.values)+1), range(1,len(model.t.data())+1))),
|
||||
# np.repeat(datademand.active_power1.values, len(model.t.data())))),mutable=True,
|
||||
# doc='Active power demand')
|
||||
# model.qdmand = py.Param(model.b, model.t, initialize=dict(
|
||||
# zip(list(itertools.product(range(1,len(databus.bus.values)+1), range(1,len(model.t.data())+1))),
|
||||
# np.repeat(datademand.reactive_power1.values, len(model.t.data())))),mutable=True,
|
||||
# doc='Reactive power demand')
|
||||
|
||||
|
||||
# Variable
|
||||
|
||||
# todo do we need to put some bound on the voltage and angle need to fixed it
|
||||
model.v = py.Var(model.index_i, model.t, initialize=1, bounds=(0.9, 1.07))
|
||||
model.v[1, :].fix(1.06)
|
||||
model.v[2, :].fix(1.045)
|
||||
@ -134,8 +111,6 @@ model.theta = py.Var(model.index_i, model.t, initialize=0, bounds=(-np.pi, np.pi
|
||||
model.theta[1, :].fix(0)
|
||||
|
||||
# bounds for generator active power
|
||||
|
||||
|
||||
model.plb = py.Param(model.b, initialize=dict(zip(databus.bus, datagen.pl)),
|
||||
doc='active power lower bound')
|
||||
model.pub = py.Param(model.b, initialize=dict(zip(databus.bus, datagen.pu)),
|
||||
@ -150,9 +125,8 @@ def pgenbound(model, i, t):
|
||||
model.pgen = py.Var(model.b, model.t,bounds=(0, None))
|
||||
model.pgen[4, :].fix(0)
|
||||
model.pgen[5, :].fix(0)
|
||||
# bounds for generator reactive power
|
||||
# Todo should i need to put j with each element
|
||||
|
||||
# bounds for generator reactive power
|
||||
model.qlb = py.Param(model.b, initialize=dict(zip(databus.bus, datagen.ql)), doc='reactive power lower bound')
|
||||
model.qub = py.Param(model.b, initialize=dict(zip(databus.bus, datagen.qu)), doc='reactive power upper bound')
|
||||
|
||||
@ -169,17 +143,12 @@ print('model data is ok')
|
||||
|
||||
|
||||
# Constraints
|
||||
# Todo check the error for indexing
|
||||
def active_power(model, i, t):
|
||||
return model.pgen[i, t] - model.pdmand[i, t]- sum(
|
||||
[y_mag[i - 1, j - 1] * (model.v[i, t]) * (model.v[j, t]) * py.cos(
|
||||
y_rad[i - 1, j - 1] + model.theta[j, t] - model.theta[i, t])
|
||||
for j in model.index_j]) ==0
|
||||
|
||||
|
||||
# i is not equal to j
|
||||
|
||||
|
||||
model.Const_Active_power = py.Constraint(model.index_i, model.t, rule=active_power, doc='active power injection')
|
||||
|
||||
|
||||
@ -190,24 +159,17 @@ def reactive_power(model, i, t):
|
||||
y_rad[i - 1, j - 1] + model.theta[j, t] - model.theta[i, t])
|
||||
for j in model.index_j])==0
|
||||
|
||||
|
||||
model.Const_Reactive_power = py.Constraint(model.index_i, model.t, rule=reactive_power,
|
||||
doc='Reactive power injection')
|
||||
|
||||
print('model constraint are ok')
|
||||
|
||||
# Objective Function * .25
|
||||
|
||||
|
||||
for k in model.index_i:
|
||||
for l in model.index_j:
|
||||
ybus_real[k - 1, l - 1] = (-(ybus_real[k - 1, l - 1]))
|
||||
|
||||
|
||||
def objective_rule(model):
|
||||
# for m in model.index_i:
|
||||
# for n in model.index_j:
|
||||
# if m != n:
|
||||
return sum(
|
||||
sum(0.5 * (ybus_real[m - 1, n - 1]) * ((model.v[m, l]) ** 2 + (model.v[n, l]) ** 2 - 2 * (
|
||||
(model.v[m, l]) * (model.v[n, l])) * py.cos(model.theta[n, l] - model.theta[m, l])) for m in
|
||||
@ -216,7 +178,6 @@ def objective_rule(model):
|
||||
|
||||
model.objective = py.Objective(rule=objective_rule, sense=py.minimize, doc='Definition of objective function')
|
||||
|
||||
print(' model objective is ok ')
|
||||
# Solver
|
||||
|
||||
opt = py.SolverFactory('ipopt')
|
||||
@ -224,7 +185,6 @@ result = opt.solve(model)
|
||||
model.write('model_opf.nl', io_options={'symbolic_solver_labels': True})
|
||||
|
||||
print('objective function = ', py.value(model.objective) * 100)
|
||||
# model.display()
|
||||
|
||||
if (result.solver.status == py.SolverStatus.ok) and (
|
||||
result.solver.termination_condition == py.TerminationCondition.optimal):
|
||||
@ -236,92 +196,6 @@ else:
|
||||
print('Solver Status: ', result.solver.status)
|
||||
|
||||
# ploting:
|
||||
|
||||
# pl_pgen = []
|
||||
# pl_pdem = []
|
||||
# pl_qdem = []
|
||||
#
|
||||
# pl_qgen = []
|
||||
# pl_v = [[] for j in model.b]
|
||||
# pl_theta = [[] for j in model.b]
|
||||
#
|
||||
# for ll in range(
|
||||
# len([model.pgen, model.qgen, model.v, model.theta, model.pdmand, model.qdmand])):
|
||||
# if ll == 0:
|
||||
# for i in model.pgen:
|
||||
# pl_pgen.append(py.value(model.pgen[i]))
|
||||
# if ll == 1:
|
||||
# for i in model.qgen:
|
||||
# pl_qgen.append(py.value(model.qgen[i]))
|
||||
#
|
||||
# # if ll == 2:
|
||||
# # for i in model.v:
|
||||
# # pl_v.append(py.value(model.v[i]))
|
||||
# # if ll == 3:
|
||||
# # for i in model.theta:
|
||||
# # pl_theta.append(py.value(model.theta[i]))
|
||||
# if ll == 3:
|
||||
# for i in model.pdmand:
|
||||
# pl_pdem.append(py.value(model.pdmand[i]))
|
||||
# if ll == 3:
|
||||
# for i in model.qdmand:
|
||||
# pl_qdem.append(py.value(model.qdmand[i]))
|
||||
# for j in model.b:
|
||||
# for k, v in model.v.items():
|
||||
# if k[1] == j:
|
||||
# pl_v[j -1].append(py.value(v))
|
||||
# for j in model.b:
|
||||
# for k, v in model.theta.items():
|
||||
# if k[1] == j:
|
||||
# pl_theta[j-1 ].append(py.value(v))
|
||||
# # width = 0.2
|
||||
# b = np.arange(len(model.b))
|
||||
# t = np.arange(len(model.t))
|
||||
# x = b # number of buss
|
||||
# y = t # time
|
||||
# z = pl_v # votlage
|
||||
# X, Y = np.meshgrid(y, x)
|
||||
# Z = np.reshape(z, X.shape) # Z.shape must be equal to X.shape = Y.shape
|
||||
# fig = plt.figure()
|
||||
# ax = fig.gca(projection='3d')
|
||||
# ax.plot_surface(X, Y, Z, cmap=cm.coolwarm)
|
||||
# ax.set_xlabel('time')
|
||||
# ax.set_ylabel('bus')
|
||||
# ax.set_zlabel('voltage')
|
||||
|
||||
# plt.show()
|
||||
# fig = plt.figure()
|
||||
# ax = fig.add_subplot(111, projection='3d')
|
||||
# ax.plot_surface(X, Y, Z)
|
||||
# ax.set_xlabel('time')
|
||||
# ax.set_ylabel('bus')
|
||||
# ax.set_zlabel('voltage')
|
||||
# plt.show()
|
||||
|
||||
# ax1.set_xlabel('x axis')
|
||||
# ax1.set_ylabel('y axis')
|
||||
# ax1.set_zlabel('z axis')
|
||||
# fig2, ax = plt.subplots()
|
||||
# v = ax.bar(x1, pl_v, label='voltage-bus_i')
|
||||
# ax.set_ylabel('Voltages')
|
||||
# ax.set_title('Bus')
|
||||
# ax.set_xticks(x)
|
||||
# ax.set_xticklabels(x)
|
||||
# ax.bar_label(v)
|
||||
# pl.ylabel('Voltage (PU)')
|
||||
# pl.title('Voltages of the buses')
|
||||
# fig2.tight_layout()
|
||||
# pl.show()
|
||||
|
||||
# fig2, ax = plt.subplots(2, len(b), constrained_layout=True, figsize=(10, 10))
|
||||
# for k in range(len(b)):
|
||||
# ax[0, k].bar(t, pl_v[k], color="blue")
|
||||
# ax[1, k].bar(t, pl_theta[k], color="blue")
|
||||
# ax[0, 0].set_ylabel('Voltage')
|
||||
# ax[0, k].set_title(f"Bus {k + 1}")
|
||||
# fig2.suptitle('Grid Data', fontsize=10)
|
||||
# pl.show()
|
||||
|
||||
pl_pdem = [[] for j in model.b]
|
||||
pl_pgen = [[] for j in model.b]
|
||||
time = [i for i in model.t]
|
||||
@ -366,7 +240,9 @@ t = np.arange(len(model.t))
|
||||
x = b # number of buss
|
||||
y = t # time
|
||||
z = pl_v # votlage
|
||||
#
|
||||
|
||||
|
||||
#3d voltage profile
|
||||
# X, Y = np.meshgrid(y, x)
|
||||
# Z = np.reshape(z, X.shape) # Z.shape must be equal to X.shape = Y.shape
|
||||
# fig = plt.figure()
|
||||
|
||||
Loading…
Reference in New Issue
Block a user