-
Notifications
You must be signed in to change notification settings - Fork 19
/
Copy pathtest_heat_pump.py
130 lines (101 loc) · 3.05 KB
/
test_heat_pump.py
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
120
121
122
123
124
125
126
127
128
129
130
# -*- coding: utf-8 -*-
"""
Info
----
In this testfile the basic functionalities of the HeatPump class are tested.
Run each time you make changes on an existing function.
Adjust if a new function is added or
parameters in an existing function are changed.
"""
from vpplib.user_profile import UserProfile
from vpplib.environment import Environment
from vpplib.heat_pump import HeatPump
import matplotlib.pyplot as plt
# Values for environment
start = "2015-01-01 00:00:00"
end = "2015-12-31 23:45:00"
year = "2015"
time_freq = "15 min"
timestamp_int = 48
timestamp_str = "2015-12-07 12:00:00"
timebase = 15
latitude = 50.941357
longitude = 6.958307
# Values for user_profile
yearly_thermal_energy_demand = 12500
building_type = "DE_HEF33"
t_0 = 40
# Values for Heatpump
el_power = 5 # kW electric
th_power = 8 # kW thermal
heat_pump_type = "Air"
heat_sys_temp = 60
ramp_up_time = 1 / 15 # timesteps
ramp_down_time = 1 / 15 # timesteps
min_runtime = 1 # timesteps
min_stop_time = 2 # timesteps
environment = Environment(
timebase=timebase,
start=start,
end=end,
year=year,
time_freq=time_freq,
surpress_output_globally=False
)
environment.get_dwd_mean_temp_hours(lat=latitude,lon=longitude)
environment.get_dwd_mean_temp_days(lat=latitude,lon=longitude)
user_profile = UserProfile(
identifier=None,
latitude=None,
longitude=None,
thermal_energy_demand_yearly=yearly_thermal_energy_demand,
mean_temp_days=environment.mean_temp_days,
mean_temp_hours=environment.mean_temp_hours,
mean_temp_quarter_hours=environment.mean_temp_hours.resample("15 Min").interpolate(),
building_type=building_type,
comfort_factor=None,
t_0=t_0,
)
def test_get_thermal_energy_demand(user_profile):
user_profile.get_thermal_energy_demand()
user_profile.thermal_energy_demand.plot()
plt.show()
test_get_thermal_energy_demand(user_profile)
hp = HeatPump(
identifier="hp1",
unit="kW",
environment=environment,
user_profile=user_profile,
el_power=el_power,
th_power=th_power,
heat_pump_type=heat_pump_type,
heat_sys_temp=heat_sys_temp,
ramp_up_time=ramp_up_time,
ramp_down_time=ramp_down_time,
min_runtime=min_runtime,
min_stop_time=min_stop_time,
)
def test_get_cop(hp):
print("get_cop:")
hp.get_cop()
hp.cop.plot(figsize=(16, 9))
plt.show()
def test_prepare_timeseries(hp):
print("prepareTimeseries:")
hp.prepare_time_series()
hp.timeseries.plot(figsize=(16, 9))
plt.show()
def test_value_for_timestamp(hp, timestamp):
print("value_for_timestamp:")
demand = hp.value_for_timestamp(timestamp)
print("El. Demand: ", demand, "\n")
def test_observations_for_timestamp(hp, timestamp):
print("observations_for_timestamp:")
observation = hp.observations_for_timestamp(timestamp)
print(observation, "\n")
test_get_cop(hp)
test_prepare_timeseries(hp)
test_value_for_timestamp(hp, timestamp_int)
test_observations_for_timestamp(hp, timestamp_int)
test_value_for_timestamp(hp, timestamp_str)
test_observations_for_timestamp(hp, timestamp_str)