-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathstatistic_mgr.py
172 lines (128 loc) · 7.88 KB
/
statistic_mgr.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
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
import appdaemon.plugins.hass.hassapi as hass
import os, configparser, datetime, calendar, time
class AccumulatingStatistic:
def __init__(self, name, accumulator_names, data_namespace):
self.data_namespace = data_namespace
self.accumulator_names = accumulator_names
self.name = name.lower()
self.last_value = 0.0
self.accumulators = {name: 0.0 for name in self.accumulator_names}
self._load_state()
def get_accumulator(self, name):
return self.accumulators.get(name, 0.0)
def reset_accumulator(self, name):
self.accumulators[name] = 0.0
def accumulate(self, value, delta_T):
increment = 0.5 * (self.last_value + value) * delta_T
self.last_value = value
for key in self.accumulator_names:
self.accumulators[key] += increment
self._dump_state()
def _dump_state(self):
self.data_namespace.publish_measurement(var_name = f"accumulating_statistic_{self.name}_last_value",
friendly_name = f"accumulating_statistic_{self.name}_last_value",
value = self.last_value,
unit = "kWh",
meas_type = "power")
for key, value in self.accumulators.items():
self.data_namespace.publish_measurement(var_name = f"accumulating_statistic_{self.name}_accumulator_{key}",
friendly_name = f"accumulating_statistic_{self.name}_accumulator_{key}",
value = value,
unit = "kWh",
meas_type = "power")
def _load_state(self):
self.last_value = self.data_namespace.get_last_from_history(f"sensor.accumulating_statistic_{self.name}_last_value")
for key in self.accumulator_names:
self.accumulators[key] = self.data_namespace.get_last_from_history(f"sensor.accumulating_statistic_{self.name}_accumulator_{key}")
class StatisticMgr(hass.Hass):
def initialize(self):
self.accumulator_names = ["hourly", "daily", "monthly"]
self.run_in(self.schedule_callbacks, 30)
def schedule_callbacks(self, kwargs):
self.global_stats = {
"energy_produced_kwh": AccumulatingStatistic("energy_produced_kwh", self.accumulator_names, data_namespace = self),
"energy_sold_kwh": AccumulatingStatistic("energy_sold_kwh", self.accumulator_names, data_namespace = self),
"energy_bought_kwh": AccumulatingStatistic("energy_bought_kwh", self.accumulator_names, data_namespace = self),
"energy_used_kwh": AccumulatingStatistic("energy_used_kwh", self.accumulator_names, data_namespace = self)
}
self.friendly_names = {
"energy_produced_kwh": "Produzierte Energie",
"energy_sold_kwh": "Verkaufte Energie",
"energy_bought_kwh": "Gekaufte Energie",
"energy_used_kwh": "Verbrauchte Energie",
}
self.integration_interval_sec = 4.0
self.run_every(self.update_statistics, "now", self.integration_interval_sec)
self.run_every(self.publish_measurements, "now", self.integration_interval_sec)
self.run_hourly(self.make_and_publish_snapshots_hourly, datetime.time(0, 0, 0))
self.run_daily(self.make_and_publish_snapshots_daily, datetime.time(23, 59, 59))
self.run_daily(self.make_and_publish_snapshots_monthly, datetime.time(23, 59, 59))
def update_statistics(self, kwargs):
sampling_interval_hr = self.integration_interval_sec / 3600.0
self.global_stats["energy_produced_kwh"].accumulate(abs(self.read_measurement("global_pv_power")), sampling_interval_hr)
self.global_stats["energy_used_kwh"].accumulate(abs(self.read_measurement("global_load_power")), sampling_interval_hr)
grid_power = self.read_measurement("global_grid_power")
if grid_power > 0.0:
self.global_stats["energy_sold_kwh"].accumulate(abs(grid_power), sampling_interval_hr)
else:
self.global_stats["energy_bought_kwh"].accumulate(abs(grid_power), sampling_interval_hr)
def make_and_publish_snapshots_hourly(self, kwargs):
self.publish_as_statistic("hourly", reset_accumulator = True)
def make_and_publish_snapshots_daily(self, kwargs):
self.publish_as_statistic("daily", reset_accumulator = True)
def make_and_publish_snapshots_monthly(self, kwargs):
def is_last_day_of_month():
day = datetime.datetime.now().day
month = datetime.datetime.now().month
year = datetime.datetime.now().year
last_day = calendar.monthrange(year, month)[1]
return day == last_day
if is_last_day_of_month():
self.publish_as_statistic("monthly", reset_accumulator = True)
def publish_measurements(self, kwargs):
self.publish_as_measurement("daily", reset_accumulator = False)
self.publish_as_measurement("monthly", reset_accumulator = False)
def publish_as_statistic(self, accumulator_name, reset_accumulator = False):
for name, stat in self.global_stats.items():
self.publish_statistic(var_name = name + f"_{accumulator_name}",
friendly_name = self.friendly_names[name],
value = self.stat_format(stat.get_accumulator(accumulator_name)),
unit = "kWh",
meas_type = "power",
state_class = "measurement")
if reset_accumulator:
stat.reset_accumulator(accumulator_name)
def publish_as_measurement(self, accumulator_name, reset_accumulator = False):
for name, stat in self.global_stats.items():
self.publish_measurement(var_name = name + f"_{accumulator_name}",
friendly_name = self.friendly_names[name],
value = self.disp_format(stat.get_accumulator(accumulator_name)),
unit = "kWh",
meas_type = "power")
if reset_accumulator:
stat.reset_accumulator(accumulator_name)
def get_last_from_history(self, name):
start_time = datetime.datetime.now() - datetime.timedelta(days = 1)
data = self.get_history(entity_id = name, start_time = start_time)[0]
return float(data[-1]["state"])
def read_measurement(self, name):
raw_value = self.get_entity(f"sensor.{name}").get_state(attribute = "state")
return float(raw_value) if raw_value else 0.0
def publish_statistic(self, var_name, friendly_name, value, unit, meas_type, state_class):
self.set_state(f"statistic.{var_name}",
state = value,
attributes = {"friendly_name": friendly_name,
"unit_of_measurement": unit,
"state_class": state_class,
"device_class": meas_type})
def publish_measurement(self, var_name, friendly_name, value, unit, meas_type):
self.set_state(f"sensor.{var_name}",
state = value,
attributes = {"friendly_name": friendly_name,
"unit_of_measurement": unit,
"state_class": "measurement",
"device_class": meas_type})
def disp_format(self, val):
return round(val, 2)
def stat_format(self, val):
return round(val, 4)