Energy inference and EV charging ETA utilities (SoC-based).
Project description
stroomer
Utilities for appliance inference and EV charging ETA (SoC-based).
Usage
Appliance inference
from stroomer import StroomerPredictor
p = StroomerPredictor()
# daya per unit (W)
p.set_appliances({
"Lampu": 10,
"Kipas": 50,
"TV": 100,
"Kulkas": 150,
"AC": 1000
})
# Opsional: batasi jumlah masuk akal (mis. lampu maksimal 20 unit)
p.set_max_counts({
"Lampu": 20,
"Kipas": 2,
"TV": 2,
"Kulkas": 2,
"AC": 1
})
out = p.predict(power=180) # misal terbaca 180 W total
print(out)
# Kemungkinan output:
# {
# "on": {"Lampu": 3, "Kipas": 1}, # 3*10 + 1*50 = 80 W (contoh) -> akan dicari kombinasi terdekat ke 180
# "target_power": 180.0,
# "predicted_total": 180.0,
# "relative_error": 0.0
# }
Charging ETA (SoC-based)
from stroomer import ChargingTimePredictor
eta = ChargingTimePredictor(capacity_kwh=50, target_soc=90, efficiency=0.92)
print(eta.predict(power=8000, SoC=30))
# -> {"FinishDuration":"03:14","FinishTime":"2025-08-18T13:25:00+00:00"}
Dev
pip install -U build twine pytest
pip install -e .
pytest -q
python -m build
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