working on load profiling simulation

.gitignore

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+venv/
+*.pyc

LoadProfile.py

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+import numpy as np
+from Utilities.Time import generate_timestrings
+
+
+def get_no_of_peaks(peak_bounds):
+    peak_occurences = np.random.randint(peak_bounds["min"], peak_bounds["max"], 1)
+    return peak_occurences
+
+
+def generate_peak_info(c, dt):
+    no_of_peaks = get_no_of_peaks(c["site_info"]["no_of_peaks"])
+    operating_hours = generate_timestrings(
+        c["site_info"]["operating hours"]["start"],
+        c["site_info"]["operating hours"]["end"],
+        dt,
+    )
+    peak_times = np.random.choice(operating_hours, no_of_peaks, replace=False)
+
+    print(f"Peak times: {peak_times}")
+    return peak_times
+
+
+def get_load_profile(c, dt):
+    return generate_peak_info(c, dt)

Utilities/Time.py

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+import time
+from datetime import datetime, timedelta
+
+
+def get_current_time():
+    """Returns the current time in seconds since the epoch."""
+    return time.time()
+
+
+def generate_timestrings(start_time_str, end_time_str, dt):
+    """Generates a list of timestamps from start_time to end_time, which are strings such
+    as 19:00."""
+
+    timestamps = []
+    current_time = datetime.strptime(start_time_str, "%H:%M")
+    end_time = datetime.strptime(end_time_str, "%H:%M")
+    while current_time <= end_time:
+        timestamps.append(current_time)
+        current_time += timedelta(seconds=dt)
+    timestrings = [dt.strftime("%H:%M") for dt in timestamps]
+    return timestrings

YAMLs/config.yml

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+sim_time:
+  time_step_minutes: 1
+  batch_process_hours: 24 # compute load profile of 24 hours at a time
+  duration_days: 60
+
+paths:
+  site_info: YAMLs/site_info.yaml

YAMLs/site_info.yaml

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+# site consumption info to simulate load profile with
+
+sites:
+  - name: Aetas Damansara
+    daily_consumption_kWh: 308
+    maximum_demand_kW: 145
+    location: 3.132000, 101.623000
+  - name: Alora
+    daily_consumption_kWh: 432
+    maximum_demand_kW: 203
+    location: 2.997419, 101.589894
+  - name: Alira
+    daily_consumption_kWh: 449
+    maximum_demand_kW: 211
+    location: 3.057000, 101.582000
+  - name: Amika
+    daily_consumption_kWh: 533
+    maximum_demand_kW: 251
+    location: 3.048500, 101.634000
+  - name: Lakeside Sanderling
+    daily_consumption_kWh: 736
+    maximum_demand_kW: 346
+    location: 3.040300, 101.610100
+operating hours:
+  start: "07:00"
+  end: "19:00"
+time zone: Asia/Kuala_Lumpur
+no_of_peaks:
+  min: 30
+  max: 100
+peak_duration:
+  unit: minutes
+  min: 0.5
+  max: 2

main.py

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+import yaml
+from Utilities.Time import get_current_time
+from LoadProfile import get_load_profile
+
+# read config file
+c = yaml.safe_load(open("YAMLs/config.yml"))
+
+## simulation time setup
+# get current time
+c["sim_start_time"] = get_current_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
+
+# load site info
+c["site_info"] = yaml.safe_load(open(c["paths"]["site_info"]))
+
+# generate load profiles
+get_load_profile(c, dt)

requirements.txt

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+numpy==2.3.1
+pandas==2.3.1
+python-dateutil==2.9.0.post0
+pytz==2025.2
+six==1.17.0
+tzdata==2025.2