diff --git a/insel/insel.py b/insel/insel.py
new file mode 100644
index 0000000..0f22827
--- /dev/null
+++ b/insel/insel.py
@@ -0,0 +1,18 @@
+import os
+from pathlib import Path
+from abc import ABC
+
+
+class Insel(ABC):
+  def __init__(self, path):
+    self._path = path
+    self._results = None
+
+  def run(self):
+    paths = sorted(Path(self._path).glob('*.insel'))
+    for file in paths:
+      os.system('insel ' + str(file))
+
+  @property
+  def results(self):
+    raise NotImplementedError
diff --git a/insel/monthly_demand_calculation.py b/insel/monthly_demand_calculation.py
new file mode 100644
index 0000000..d6f4a3d
--- /dev/null
+++ b/insel/monthly_demand_calculation.py
@@ -0,0 +1,64 @@
+"""
+Monthly demand calculation using the monthly energy balance methodology based on the norm...
+SPDX - License - Identifier: LGPL - 3.0 - or -later
+Copyright © 2020 Project Author Pilar Monsalvete Alvarez de Uribarri pilar.monsalvete@concordia.ca
+"""
+
+from pathlib import Path
+import pandas as pd
+import sys
+import csv
+from insel.insel import Insel
+
+
+class MonthlyDemandCalculation(Insel):
+  def __init__(self, city, main_path, weather_format):
+    super().__init__(main_path)
+    self._city = city
+    self._weather_format = weather_format
+
+  def results(self):
+    for building in self._city.buildings:
+      file_name = building.name + '.out'
+      full_path_out = Path(self._path / file_name).resolve()
+      full_path_out.parent.mkdir(parents=True, exist_ok=True)
+      try:
+        building.heating['month'], building.cooling['month'] = self._demand(full_path_out)
+        heating_year = 0
+        for value in building.heating['month']['INSEL']:
+          if value == 'NaN':
+            value = '0'
+          heating_year += float(value)
+        yearly_heating = pd.DataFrame([heating_year], columns=['INSEL'])
+        building.heating['year'] = yearly_heating
+
+        cooling_year = 0
+        for value in building.cooling['month']['INSEL']:
+          if value == 'NaN':
+            value = '0'
+          cooling_year += float(value)
+        yearly_cooling = pd.DataFrame([cooling_year], columns=['INSEL'])
+        building.cooling['year'] = yearly_cooling
+
+      except ValueError:
+        print(sys.exc_info()[1])
+        print('Building ' + building.name + ' could not be processed')
+        continue
+
+  @staticmethod
+  def _demand(insel_outputs_path):
+    heating = []
+    cooling = []
+    with open(Path(insel_outputs_path).resolve()) as csv_file:
+      csv_reader = csv.reader(csv_file)
+      for line in csv_reader:
+        demand = str(line).replace("['", '').replace("']", '').split()
+        for i in range(0, 2):
+          if demand[i] != 'NaN':
+            aux = float(demand[i])*1000     # kWh to Wh
+            demand[i] = str(aux)
+        heating.append(demand[0])
+        cooling.append(demand[1])
+    monthly_heating = pd.DataFrame(heating, columns=['INSEL'])
+    monthly_cooling = pd.DataFrame(cooling, columns=['INSEL'])
+    return monthly_heating, monthly_cooling