Add csv post process for time series variables

CHANGELOG.md

@@ -6,6 +6,7 @@
 - Added capability to have transport models that require user input parameters
 - Add geologic hydrogen surface processing converter
 - Add baseclass for caching functionality
+- Added postprocessing function to save timeseries
 - Minor reorg for profast tools
 - Removed hydrogen tank cost and performance models that were unused
 

docs/user_guide/postprocessing_results.md

@@ -88,3 +88,87 @@ print(model.prob.get_val("electrolyzer.total_hydrogen_produced", units='kg'))
 This will print the total hydrogen produced by the electrolyzer in kg.
 The `get_val` method is used to access the value of the variable in the `prob` object.
 The `units` argument is used to specify the units of the value to be returned.
+
+### Saving outputs
+
+The time series outputs can be saved to a csv output using the `save_case_timeseries_as_csv` function. If no variables are specified, then the function saves all time series variables in the simulation. Otherwise, the specified variables are saved.
+
+The `vars_to_save` argument supports three different input formats:
+
+1. **List of variable names** - saves variables with their default units
+2. **Dictionary with units** - keys are variable names, values are the desired units
+3. **Dictionary with options** - keys are variable names, values are dictionaries with `"units"` and/or `"alternative_name"` keys
+
+#### Example 1: Save all timeseries data
+
+```python
+from h2integrate.core.h2integrate_model import H2IntegrateModel
+from h2integrate.postprocess.sql_timeseries_to_csv import save_case_timeseries_as_csv
+
+# Create and run a H2Integrate model
+model = H2IntegrateModel("top_level_config.yaml")
+model.run()
+model.post_process()
+
+# Save all timeseries data to a csv file
+timeseries_data = save_case_timeseries_as_csv(model.recorder_path)
+```
+
+#### Example 2: Specify variables as a list
+
+When providing a list of variable names, the function uses the default units for each variable.
+
+```python
+# Get a subset of timeseries data using a list of variable names
+output_vars = [
+    "electrolyzer.hydrogen_out",
+    "hopp.electricity_out",
+    "ammonia.ammonia_out",
+    "h2_storage.hydrogen_out",
+]
+
+# Don't save subset of timeseries to a csv file using save_to_file=False
+timeseries_data = save_case_timeseries_as_csv(
+    model.recorder_path, vars_to_save=output_vars, save_to_file=False
+)
+```
+
+#### Example 3: Specify variables with custom units
+
+When providing a dictionary with variable names as keys and unit strings as values, the function converts each variable to the specified units.
+
+```python
+# Specify variables with custom units
+vars_with_units = {
+    "ammonia.hydrogen_in": "kg/h",
+    "h2_storage.hydrogen_in": "kg/h",
+    "electrolyzer.electricity_in": "kW",
+}
+
+timeseries_data = save_case_timeseries_as_csv(
+    model.recorder_path, vars_to_save=vars_with_units, save_to_file=False
+)
+```
+
+#### Example 4: Specify variables with alternative column names
+
+When providing a dictionary with variable names as keys and dictionaries as values, you can specify both custom units and alternative column names for the output DataFrame.
+
+```python
+# Specify variables with alternative names and/or units
+vars_with_options = {
+    "electrolyzer.hydrogen_out": {"alternative_name": "Electrolyzer Hydrogen Output"},
+    "hopp.electricity_out": {"units": "kW", "alternative_name": "Plant Electricity Output"},
+    "ammonia.ammonia_out": {"alternative_name": None},  # Uses default variable name
+    "h2_storage.hydrogen_out": {"alternative_name": "H2 Storage Hydrogen Output"},
+}
+
+timeseries_data = save_case_timeseries_as_csv(
+    model.recorder_path, vars_to_save=vars_with_options, save_to_file=False
+)
+# Resulting columns: "Electrolyzer Hydrogen Output (kg/h)", "Plant Electricity Output (kW)", etc.
+```
+
+```{note}
+The `electricity_base_unit` argument (default: `"MW"`) controls the units used for electricity-based variables when no specific units are provided. Valid options are `"W"`, `"kW"`, `"MW"`, or `"GW"`.
+```

examples/02_texas_ammonia/driver_config.yaml

@@ -3,3 +3,20 @@ description: "This analysis runs a hybrid plant to match the first example in H2
 
 general:
   folder_output: outputs
+
+recorder:
+  # required inputs
+  flag: True #record outputs
+  file: "cases.sql" #this file will be written to the folder `outputs`
+
+  # optional but recommended inputs
+  overwrite_recorder: True #If True, do not create a unique recorder file for subsequent runs. Defaults to False.
+  recorder_attachment: "model" #"driver" or "model", defaults to "model". Use "driver" if running a parallel simulation.
+  includes: ["*"] #include everything
+  excludes: ["*resource_data*"] #exclude resource data
+
+  # below are optional and defaulted to the OpenMDAO default
+  # record_inputs: True #defaults to True
+  # record_outputs: True #defaults to True
+  # record_residuals: True #defaults to True
+  # options_excludes: #this is only used if recorder_attachment is "model"

examples/02_texas_ammonia/run_texas_ammonia_plant.py

@@ -1,16 +1,35 @@
 import numpy as np
 
 from h2integrate.core.h2integrate_model import H2IntegrateModel
+from h2integrate.postprocess.sql_timeseries_to_csv import save_case_timeseries_as_csv
 
 
 # Create a H2Integrate model
 model = H2IntegrateModel("02_texas_ammonia.yaml")
+
 # Set battery demand profile to electrolyzer capacity
 # TODO: Update with demand module once it is developed
 demand_profile = np.ones(8760) * 640.0
 model.setup()
 model.prob.set_val("battery.electricity_demand", demand_profile, units="MW")
+
 # Run the model
 model.run()
 
 model.post_process()
+
+# Save all timeseries data to a csv file
+timeseries_data = save_case_timeseries_as_csv(model.recorder_path)
+
+# Get a subset of timeseries data
+vars_to_save = [
+    "electrolyzer.hydrogen_out",
+    "hopp.electricity_out",
+    "ammonia.ammonia_out",
+    "h2_storage.hydrogen_out",
+]
+
+# Don't save subset of timeseries to a csv file using save_to_file=False
+timeseries_data = save_case_timeseries_as_csv(
+    model.recorder_path, vars_to_save=vars_to_save, save_to_file=False
+)

h2integrate/core/pose_optimization.py

@@ -448,8 +448,8 @@ def set_recorders(self, opt_prob):
                 for current optimization problem
 
         Returns:
-            opt_prob (openmdao problem instance): openmdao problem instance for
-                current optimization problem edited to include a set up recorder
+            recorder_path (Path or None): Path to the recorder file if recorder is enabled,
+                None otherwise
         """
         folder_output = self.config["general"]["folder_output"]
 
@@ -525,7 +525,7 @@ def set_recorders(self, opt_prob):
                 opt_prob.model.recording_options["excludes"] = self.config["recorder"].get(
                     "excludes", ["*resource_data"]
                 )
-                return
+                return recorder_path
 
             if recorder_attachment == "driver":
                 recorder_options += [
@@ -550,6 +550,7 @@ def set_recorders(self, opt_prob):
                     "excludes", ["*resource_data"]
                 )
             return recorder_path
+
         return None
 
     def set_restart(self, opt_prob):