1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
|
#!/usr/bin/python3
# Copyright (C) 2016 EDF
# All Rights Reserved
# This code is published under the GNU Lesser General Public License (GNU LGPL)
import numpy as np
import math
import StOptReg as reg
import StOptGrids
import StOptGlobal
import Simulators as sim
import Optimizers as opt
import Utils
import dp.DynamicProgrammingByRegressionHighLevel as dyn
import dp.SimulateRegressionControlHighLevel as srt
import unittest
import importlib
accuracyClose = 0.5
def testGasStorage():
# test MPI
moduleMpi4Py=importlib.util.find_spec('mpi4py')
if (moduleMpi4Py is not None):
from mpi4py import MPI
# storage
###############
maxLevelStorage = 360000
injectionRateStorage = 60000
withdrawalRateStorage = 45000
injectionCostStorage = 0.35
withdrawalCostStorage = 0.35
switchingCostStorage = 4.
maturity = 1.
nstep = 10
# define a a time grid
timeGrid = StOptGrids.OneDimRegularSpaceGrid(0., maturity / nstep, nstep)
futValues = []
# periodicity factor
iPeriod = 52
for i in range(nstep + 1):
futValues.append(50. + 20 * math.sin((math.pi * i * iPeriod) / nstep))
# define the future curve
futureGrid = Utils.FutureCurve(timeGrid, futValues)
# one dimensional factors
nDim = 1
sigma = np.zeros(nDim) + 0.94
mr = np.zeros(nDim) + 0.29
# number of simulations
nbsimulOpt = 20000
# grid
#####
nGrid = 40
lowValues = np.zeros(1, dtype = float)
step = np.zeros(1, dtype = float) + maxLevelStorage / nGrid
nbStep = np.zeros(1, dtype = np.int32) + nGrid
grid = StOptGrids.RegularSpaceGrid(lowValues, step, nbStep)
# no actualization
rate=0.
# a backward simulator
######################
bForward = False
backSimulator = sim.MeanRevertingSimulator(futureGrid, sigma, mr, rate,maturity, nstep, nbsimulOpt, bForward)
# optimizer
############
storage = opt.OptimizeGasStorageSwitchingCostMeanReverting(injectionRateStorage, withdrawalRateStorage, injectionCostStorage, withdrawalCostStorage, switchingCostStorage)
# regressor
##########
nMesh = 4
nbMesh = np.zeros(1, dtype = np.int32) + nMesh
regressor = reg.LocalLinearRegression(nbMesh)
# final value
vFunction = Utils.ZeroPayOff()
# initial values
initialStock = np.zeros(1) + maxLevelStorage
initialRegime = 0 # here do nothing (no injection, no withdrawal)
# Optimize
###########
fileToDump = "CondExpGasSwiCostHL"
# link the simulations to the optimizer
storage.setSimulator(backSimulator)
valueOptim = dyn.DynamicProgrammingByRegressionHighLevel(grid, storage, regressor, vFunction, initialStock, initialRegime, fileToDump)
print("valOP", valueOptim)
nbsimulSim = 40000
bForward = True
forSimulator2 = sim.MeanRevertingSimulator(futureGrid, sigma, mr, rate,maturity, nstep, nbsimulSim, bForward)
storage.setSimulator(forSimulator2)
valSimu2 = srt.SimulateRegressionControl(grid, storage, vFunction, initialStock, initialRegime, fileToDump)
print("valSimu2", valSimu2, "valOptim", valueOptim)
class testGasStorageSwitchCostTest(unittest.TestCase):
def test_gasStorageSwitchCostHighLevel(self):
testGasStorage()
if __name__ == '__main__':
unittest.main()
|
