Merge branch 'master' into gh-pages-custom

.travis.yml

@@ -72,6 +72,9 @@ jobs:
   - python: 3.9
     install: pip install --upgrade pip && pip install pandas==1.2.5 numpy==1.20.2 requests==2.25.1
     script: cd testing && make build_jm_image && make test_twozone_apartment_hydronic
+  - python: 3.9
+    install: pip install --upgrade pip && pip install pandas==1.2.5 numpy==1.20.2 requests==2.25.1
+    script: cd testing && travis_wait 90 make test_multizone_office_simple_hydronic_no_compile
   - python: 3.9
     install: pip install --upgrade pip && pip install pandas==1.2.5 numpy==1.20.2 requests==2.25.1
     script: cd testing && make build_jm_image && travis_wait 90 make test_multizone_office_simple_air ARG="-s test_peak_heat_day,test_typical_heat_day"

contributors.md

@@ -7,6 +7,8 @@ Thank you to all who have provided guidance on the development of this software.
 - Dave Biagioni, National Renewable Energy Laboratory
 - David Blum, Lawrence Berkeley National Laboratory
 - Yan Chen, Pacific Northwest National Laboratory
+- Roel De Coninck, dnergy
+- Iago Cupeiro Figueroa, Cupeiro Sinte, dnergy
 - Konstantin Filonenko, University of Southern Denmark
 - Gauthier-Clerc Francois, Pure Control
 - Valentin Gavan, ENGIE
@@ -18,6 +20,7 @@ Thank you to all who have provided guidance on the development of this software.
 - Nicholas Long, National Renewable Energy Laboratory
 - Xing Lu, Pacific Northwest National Laboratory
 - Robert Lutes, Pacific Northwest National Laboratory
+- Bart Merema, dnergy
 - Kefei Mo, Pacific Northwest National Laboratory
 - Erik Paulson, Independent
 - Matt Robinson, University of Colorado - Boulder

data/find_days.py

@@ -15,9 +15,12 @@
 import pandas as pd
 import os
 import numpy as np
+from matplotlib import pyplot as plt
 
 def find_days(heat, cool, data='simulate', img_name='boptest_bestest_air',
-              plot = False, peak_cool_restriction_hour=None):
+              plot=False, cooling_negative=False, peak_cool_restriction_hour=None,
+              cool_day_low_limit=14, cool_day_high_limit=358,
+              heat_day_low_limit=14, heat_day_high_limit=358):
     '''Find the start and final times for the test case scenarios.
 
     Parameters
@@ -34,17 +37,38 @@ def find_days(heat, cool, data='simulate', img_name='boptest_bestest_air',
         to generate the data.
         `path_to_data.csv` indicates path to .csv file with the yearly
         simulation data.
+        Default is `simulate`.
     img_name: string
         Image name of the container where the simulation is to be
-        performed.
-    plot: boolean
-        Set to True to show an overview of the days found
+        performed.  Used only if data=`simulate`.
+    plot: boolean, optional
+        Set to True to show an overview of the days found.
+        Default is False
+    cooling_negative: boolean, optional
+        Set to True if cooling heat flow data is negative in simulation or data file.
+        Default is False.
     peak_cool_restriction_hour: integer, optional
         Hour if want peak cooling loads to only be considered equal to or after the hour
         each day.  This can be useful to avoid including hours with peak
         cooling loads due to morning start up, which may lead to the
         same peak load for many different days.  None will have no restrictions.
         Default is None.
+    cool_day_low_limit: integer, optional
+        Day below which should not be considered for cooling.
+        Must be >= 14.
+        Default = 14.
+    cool_day_high_limit: integer, optional
+        Day below which should not be considered for cooling.
+        Must be <= 358.
+        Default = 358.
+    heat_day_low_limit: integer, optional
+        Day below which should not be considered for heating.
+        Must be >= 14.
+        Default = 14.
+    heat_day_high_limit: integer, optional
+        Day below which should not be considered for heating.
+        Must be <= 358.
+        Default = 358.
 
     Returns
     -------
@@ -89,18 +113,20 @@ def find_days(heat, cool, data='simulate', img_name='boptest_bestest_air',
 
     # Load data
     df_raw.index = pd.TimedeltaIndex(df_raw.index.values, unit='s')
+    if cooling_negative:
+        df_raw[cool] = -df_raw[cool]
     df = df_raw.resample('15T').mean()
     df.dropna(axis=0, inplace=True)
     # Since assume two-week test period with one-week warmup,
     # edges of year are not available to choose from
     df_available =  df.loc[pd.Timedelta(days=14):pd.Timedelta(days=365-7)]
-    df_available_cool = df[cool].loc[pd.Timedelta(days=14):pd.Timedelta(days=365-7)]
+    df_available_cool = df[cool].loc[pd.Timedelta(days=cool_day_low_limit):pd.Timedelta(days=cool_day_high_limit)]
     df_cool = df[cool]
     if peak_cool_restriction_hour is not None:
         # Limit available cooling hours to those after restriction
         df_available_cool = df_available_cool[df_available_cool.index.seconds/3600>=peak_cool_restriction_hour]
         df_cool = df_cool[df_cool.index.seconds/3600>=peak_cool_restriction_hour]
-    df_available_heat = df[heat].loc[pd.Timedelta(days=14):pd.Timedelta(days=365-7)]
+    df_available_heat = df[heat].loc[pd.Timedelta(days=heat_day_low_limit):pd.Timedelta(days=heat_day_high_limit)]
     df_heat = df[heat]
 
 
@@ -153,28 +179,28 @@ def find_days(heat, cool, data='simulate', img_name='boptest_bestest_air',
         if heat is not None:
             plt.figure()
             plt.title('Heating load')
-            plt.plot(time_days, df[heat])
+            plt.plot(time_days, df_heat)
             plt.xlabel('Day of the year')
             plt.ylabel('[W]')
             plt.axvline(x=peak_heat_day, color='r', label='Peak')
-            plt.axhline(y=df[heat].max(), color='r', label='_nolegend_')
+            plt.axhline(y=df_available_heat.max(), color='r', label='_nolegend_')
             plt.axvline(x=typical_heat_day, color='r', linestyle='--', label='Typical')
             plt.axhline(y=median_heat, color='r', linestyle='--', label='_nolegend_')
             plt.legend()
-            plt.show()
 
         if cool is not None:
             plt.figure()
             plt.title('Cooling load')
-            plt.plot(time_days, df[cool])
+            plt.plot(time_days, df_cool)
             plt.xlabel('Day of the year')
             plt.ylabel('[W]')
             plt.axvline(x=peak_cool_day, color='r', label='Peak')
-            plt.axhline(y=df[cool].max(), color='r', label='_nolegend_')
+            plt.axhline(y=df_available_cool.max(), color='r', label='_nolegend_')
             plt.axvline(x=typical_cool_day, color='r', linestyle='--', label='Typical')
             plt.axhline(y=median_cool, color='r', linestyle='--', label='_nolegend_')
             plt.legend()
-            plt.show()
+
+        plt.show()
 
     return days
 

parsing/parser.py

@@ -19,7 +19,12 @@
 from data.data_manager import Data_Manager
 import warnings
 
-def parse_instances(model_path, file_name):
+if 'MODELICAPATH' in os.environ:
+    modelicapath=os.environ['MODELICAPATH']
+else:
+    modelicapath=os.path.abspath('.')
+
+def parse_instances(model_path, file_name, tool='JModelica'):
     '''Parse the signal exchange block class instances using fmu xml.
 
     Parameters
@@ -29,6 +34,9 @@ def parse_instances(model_path, file_name):
     file_name : list
         Path(s) to modelica file and required libraries not on MODELICAPATH.
         Passed to file_name parameter of pymodelica.compile_fmu() in JModelica.
+    tool : str, optional
+        FMU compilation tool. "JModelica" or "OCT" supported.
+        Default is "JModelica".
 
     Returns
     -------
@@ -42,7 +50,12 @@ def parse_instances(model_path, file_name):
     '''
 
     # Compile fmu
-    fmu_path = compile_fmu(model_path, file_name, jvm_args="-Xmx8g", target='cs')
+    if tool == 'JModelica':
+        fmu_path = compile_fmu(model_path, file_name, jvm_args="-Xmx8g", target='cs')
+    elif tool == 'OCT':
+        fmu_path = compile_fmu(model_path, file_name, modelicapath=modelicapath, jvm_args="-Xmx8g", target='cs')
+    else:
+        raise ValueError('Tool {0} unknown.'.format(tool))
     # Load fmu
     fmu = load_fmu(fmu_path)
     # Check version
@@ -105,7 +118,7 @@ def parse_instances(model_path, file_name):
 
     return instances, signals
 
-def write_wrapper(model_path, file_name, instances):
+def write_wrapper(model_path, file_name, instances, tool='JModelica'):
     '''Write the wrapper modelica model and export as fmu
 
     Parameters
@@ -118,6 +131,9 @@ def write_wrapper(model_path, file_name, instances):
     instances : dict
         Dictionary of overwrite and read block class instance lists.
         {'Overwrite': [str], 'Read': [str]}
+    tool : str, optional
+        FMU compilation tool. "JModelica" or "OCT" supported.
+        Default is "JModelica".
 
     Returns
     -------
@@ -179,18 +195,28 @@ def write_wrapper(model_path, file_name, instances):
             # End file -- with hard line ending
             f.write('end wrapped;\n')
         # Export as fmu
-        fmu_path = compile_fmu('wrapped', [wrapped_path]+file_name, jvm_args="-Xmx8g", target='cs')
+        if tool == 'JModelica':
+            fmu_path = compile_fmu('wrapped', [wrapped_path]+file_name, jvm_args="-Xmx8g", target='cs')
+        elif tool == 'OCT':
+            fmu_path = compile_fmu('wrapped', [wrapped_path]+file_name, modelicapath=modelicapath, jvm_args="-Xmx8g", target='cs')
+        else:
+            raise ValueError('Tool {0} unknown.'.format(tool))
     # If there are not, write and export wrapper model
     else:
         # Warn user
         warnings.warn('No signal exchange block instances found in model.  Exporting model as is.')
         # Compile fmu
-        fmu_path = compile_fmu(model_path, file_name, jvm_args="-Xmx8g", target='cs')
+        if tool == 'JModelica':
+            fmu_path = compile_fmu(model_path, file_name, jvm_args="-Xmx8g", target='cs')
+        elif tool == 'OCT':
+            fmu_path = compile_fmu(model_path, file_name, modelicapath=modelicapath, jvm_args="-Xmx8g", target='cs')
+        else:
+            raise ValueError('Tool {0} unknown.'.format(tool))
         wrapped_path = None
 
     return fmu_path, wrapped_path
 
-def export_fmu(model_path, file_name):
+def export_fmu(model_path, file_name, tool='JModelica'):
     '''Parse signal exchange blocks and export boptest fmu and kpi json.
 
     Parameters
@@ -200,6 +226,9 @@ def export_fmu(model_path, file_name):
     file_name : list
         Path(s) to modelica file and required libraries not on MODELICAPATH.
         Passed to file_name parameter of pymodelica.compile_fmu() in JModelica.
+    tool : str, optional
+        FMU compilation tool. "JModelica" or "OCT" supported.
+        Default is "JModelica".
 
     Returns
     -------
@@ -211,9 +240,9 @@ def export_fmu(model_path, file_name):
     '''
 
     # Get signal exchange instances and kpi signals
-    instances, signals = parse_instances(model_path, file_name)
+    instances, signals = parse_instances(model_path, file_name, tool)
     # Write wrapper and export as fmu
-    fmu_path, _ = write_wrapper(model_path, file_name, instances)
+    fmu_path, _ = write_wrapper(model_path, file_name, instances, tool)
     # Write kpi json
     kpi_path = os.path.join(os.getcwd(), 'kpis.json')
     with open(kpi_path, 'w') as f:

releasenotes.md

@@ -13,6 +13,16 @@ Released on xx/xx/xxxx.
 - Specify version of scipy to 1.13.0 in test case Dockerfile.  This is for [#657](https://github.com/ibpsa/project1-boptest/issues/657).
 - Remove javascript controller example.  This is for [#664](https://github.com/ibpsa/project1-boptest/issues/664).
 - Add a new directory ``/baselines``, containing baseline testing scripts and associated KPI results for the baseline controllers of all the testcases. This is for [#495](https://github.com/ibpsa/project1-boptest/issues/495).
+- Add support to ``parsing/parser.py`` for test case compilation using [Modelon's OPTIMICA Compiler Toolkit (OCT)](https://help.modelon.com/latest/reference/oct/).  The parser can take arguments ``'JModelica'`` or ``'OCT'``, with ``'JModelica'`` as default.  A user still requires access to an OCT license and software on their set up.  This is for [#675](https://github.com/ibpsa/project1-boptest/issues/675).
+
+**The following new test cases have been added:**
+
+- ``multizone_office_simple_hydronic``, a 2-zone typical office building in Brussels, Belgium, served by fan-coil units for space heating and cooling, air handling units for space ventilation, an air-source heat pump for hot water production, and an air-cooled chiller for chilled water production. FMU compiled by [OCT](https://help.modelon.com/latest/reference/oct/).  This is for [#465](https://github.com/ibpsa/project1-boptest/issues/465).
+
+
+**The following changes are backwards-compatible, but might change benchmark results:**
+
+- Fix calculation of computational time ratio (``time_rat``) in the case of a test where the test case was initialized after a test or simulation (use of ``/advance``) had already been done using the same test case deployment (i.e. the docker container had not been shutdown first and newly deployed).  The wait time between the last ``/advance`` before the new initialization and first ``/advance`` of the new initialization was incorrectly incorporated into the calculation as a control step and has been fixed, resulting in a lower computational time ratio.  The extent of impact depends on wait time between tests and control step and number of steps taken in the new test.  This is for [#673](https://github.com/ibpsa/project1-boptest/issues/673).
 
 ## BOPTEST v0.6.0
 

testcase.py

@@ -417,7 +417,10 @@ def initialize(self, start_time, warmup_period, end_time=np.inf):
         self.fmu.reset()
         # Reset simulation data storage
         self.__initilize_data()
+        # Reset computational time ratio timer
         self.elapsed_control_time_ratio = np.array([])
+        if hasattr(self, 'tic_time'):
+            delattr(self,'tic_time')
         # Check if the inputs are valid
         try:
             start_time = float(start_time)

testcases/README.md

@@ -10,7 +10,8 @@ This directory contains test cases for BOPTEST.  A summary of available test cas
 | ``bestest_air``| BESTEST Case 900 room model with idealized fan coil unit.|**Electricity Prices**: <br />``'constant'``, <br />``'dynamic'``, <br />``'highly_dynamic'``<br />**Time Periods**:<br />``'peak_heat_day'``, <br />``'typical_heat_day'``, <br />``'peak_cool_day'``, <br />``'typical_cool_day'``, <br />``'mix_day'``|
 | ``bestest_hydronic``| BESTEST Case 900 room model with gas boiler and radiator.|**Electricity Prices**: <br />``'constant'``, <br />``'dynamic'``, <br />``'highly_dynamic'``<br />**Time Periods**: <br />``'peak_heat_day'``, <br />``'typical_heat_day'``|
 | ``bestest_hydronic_heat_pump``| BESTEST Case 900 room model, scaled by four in floor area, that uses a heat pump as heating production system and floor heating as heating emission system.|**Electricity Prices**: <br />``'constant'``, <br />``'dynamic'``, <br />``'highly_dynamic'``<br />**Time Periods**: <br />``'peak_heat_day'``, <br />``'typical_heat_day'``|
-| ``twozone_apartment_hydronic``| Low energy consumption two room aparment in Milan. Only heating is considered. The generation system is a heat pump and the emission system is floor heating. |**Electricity Prices**: <br />``'constant'``, <br />``'dynamic'``, <br />``'highly_dynamic'``<br />**Time Periods**: <br />``'peak_heat_day'``, <br />``'typical_heat_day'``|
-| ``multizone_residential_hydronic``| Multi-zone residential hydronic model with gas boiler, radiators, and ideal cooling system. |**Electricity Prices**: <br />``'constant'``, <br />``'dynamic'``, <br />``'highly_dynamic'``<br />**Time Periods**: <br />``'peak_heat_day'``, <br />``'typical_heat_day'``|
+| ``twozone_apartment_hydronic``| Low energy consumption 2 zone apartment in Milan. Only heating is considered. The generation system is a heat pump and the emission system is floor heating. |**Electricity Prices**: <br />``'constant'``, <br />``'dynamic'``, <br />``'highly_dynamic'``<br />**Time Periods**: <br />``'peak_heat_day'``, <br />``'typical_heat_day'``|
+| ``multizone_residential_hydronic``| Multi-zone (8 zones) residential hydronic model with gas boiler, radiators, and ideal cooling system. |**Electricity Prices**: <br />``'constant'``, <br />``'dynamic'``, <br />``'highly_dynamic'``<br />**Time Periods**: <br />``'peak_heat_day'``, <br />``'typical_heat_day'``|
 | ``singlezone_commercial_hydronic``| Single-zone commercial building model representing a university building with district heating source, zone radiator, occupancy based on real data, and air handling unit providing fresh air with CO2 control and heat recovery. |**Electricity Prices**: <br />``'constant'``, <br />``'dynamic'``, <br />``'highly_dynamic'``<br />**Time Periods**: <br />``'peak_heat_day'``, <br />``'typical_heat_day'``|
-| ``multizone_office_simple_air`` | Multi-zone commercial building model based on U.S. DOE medium office building with single-duct VAV with terminal reheat, air-cooled chiller, and air-to-water heat pump.|**Electricity Prices**: <br />``'constant'``, <br />``'dynamic'``, <br />``'highly_dynamic'``<br />**Time Periods**:<br />``'peak_heat_day'``, <br />``'typical_heat_day'``, <br />``'peak_cool_day'``, <br />``'typical_cool_day'``, <br />``'mix_day'``|
+| ``multizone_office_simple_hydronic`` | Multi-zone (2 zones) commercial office building model with fan coil units for space heating and cooling, air handling units for ventilation, with air-to-water heat pump and air-cooled chilled.|**Electricity Prices**: <br />``'constant'``, <br />``'dynamic'``, <br />``'highly_dynamic'``<br />**Time Periods**:<br />``'peak_heat_day'``, <br />``'typical_heat_day'``, <br />``'peak_cool_day'``, <br />``'typical_cool_day'``, <br />``'mix_day'``|
+| ``multizone_office_simple_air`` | Multi-zone (5 zones) commercial building model based on U.S. DOE medium office building with single-duct VAV with terminal reheat, air-cooled chiller, and air-to-water heat pump.|**Electricity Prices**: <br />``'constant'``, <br />``'dynamic'``, <br />``'highly_dynamic'``<br />**Time Periods**:<br />``'peak_heat_day'``, <br />``'typical_heat_day'``, <br />``'peak_cool_day'``, <br />``'typical_cool_day'``, <br />``'mix_day'``|