39 lines
1.2 KiB
Python
39 lines
1.2 KiB
Python
import yaml
|
|
from Utilities.Time import get_start_time
|
|
from Utilities.LoadProfile import get_load_profiles
|
|
import matplotlib.pyplot as pl
|
|
import pandas as pd
|
|
|
|
# read config file
|
|
c = yaml.safe_load(open("YAMLs/config.yml"))
|
|
|
|
## simulation time setup
|
|
# get current time
|
|
c["sim_start_time"] = get_start_time()
|
|
# get time step in minutes, then convert to seconds
|
|
dt = c["sim_time"]["time_step_minutes"] * 60
|
|
# compute end time based on duration in days
|
|
duration = c["sim_time"]["duration_days"] * 24 * 60 * 60
|
|
c["sim_end_time"] = c["sim_start_time"] + duration
|
|
|
|
# batch process hours in seconds
|
|
c["sim_time"]["batch_process_seconds"] = c["sim_time"]["batch_process_hours"] * 60 * 60
|
|
|
|
# load site info
|
|
c["site_info"] = yaml.safe_load(open(c["paths"]["site_info"]))
|
|
|
|
cumulative_load_profiles = pd.DataFrame()
|
|
|
|
# loop through timesteps
|
|
for i in range(
|
|
c["sim_start_time"], c["sim_end_time"], c["sim_time"]["batch_process_seconds"]
|
|
):
|
|
|
|
# generate load profiles
|
|
load_profiles = get_load_profiles(
|
|
c, dt, c["sim_start_time"], c["sim_time"]["batch_process_seconds"]
|
|
)
|
|
|
|
# add to cumulative load profiles
|
|
cumulative_load_profiles = pd.concat([cumulative_load_profiles, load_profiles], axis=1
|