Update README.md

tum-ens · May 15, 2019 · eb97511 · eb97511
1 parent 21c300b
commit eb97511
Showing 1 changed file with 50 additions and 0 deletions.
diff --git a/README.md b/README.md
@@ -3,11 +3,61 @@ Bottom-up model for the simulation of heat demand profiles of urban areas
 A. Molar-Cruz @ TUM ENS
 
 Features
+--------
 •	UrbanHeatPro is a python-based bottom-up model for the simulation of heat demand profiles of urban areas.
 •	It considers both the space heating demand and hot water demand. So far, the hot water demand is calculated only for residential buildings.
 •	Characteristic values for the building stock, building thermal properties, building set-temperature and annual hot water consumption are based on statistics for Germany.
 •	DSM strategies for the reduction of heat demand such as building renovation, heat load reduction, night-set back operation, etc, are easily implemented.
 •	The size of the study area can start from one building. Buildings can be input as a shapefile or as an excel table.
 •	By default, the model operates on an hourly time steps. However, the temporal resolution is configurable.
 
+
+Requirements
+------------
+Python 3.6 if multiprocessing is used (installation with Anaconda recommended)
+Python 2.7 (installation with Anaconda recommended)
+
+
+Input file (csv)
+----------------
+Each building is described with the following information:
+  A.	Area (required)
+      Building ground floor area in m²
+  B.	Use (required)
+      Building use as integer:
+        0	Commercial
+        1	Industrial
+        2	Public
+        3	Residential
+  C.	Bid (optional)
+      Building identification number as integer
+  D.	Free_walls (required)
+      Number of walls in contact with ambient temperature. The building is assumed to be a rectangular box with four walls.
+  E.	Construction year class (optional)
+      Construction year class from TABULA Typology as integer:
+        0	<1859
+        1	1860 - 1918
+        2	1919 - 1948
+        3	1949 - 1957
+        4	1958 - 1968
+        5	1969 - 1978
+        6	1979 - 1983
+        7	1984 - 1994
+        8	1995 - 2001
+        9	2002 - 2009
+  F.	Building type (optional)
+      Building type from TABULA Typology as integer:
+        0	Single-Family House (SFH)
+        1	Terraced House (TH)
+        2	Multi-family House (MFH)
+        3	Apartment Block (AB)
+All columns are required, if no information is given, the cell value is taken as NaN.
+This input file should be located in the corresponding folder input/buildings
+
+
+Using UrbanHeatPro
+------------------
+To run the model with the given input data, change the desired information in the runme.py file and run this file in the command line:
+>> python runme.py
+
 For more details please refer to the documentation file