Merge pull request #56 from pnnl/VAV_turndown_using_average

(2nd) VAV turndown lib item development

constrain/library/__init__.py

@@ -9,6 +9,7 @@
 from .heat_rejection_fan_var_flow_controls_cells import *
 from .hot_water_reset import *
 from .vav_static_pressure_sensor_location import *
+from .vav_turndown_during_reheat import *
 from .ventilation_fan_controls import *
 from .wlhp_loop_heat_rejection_controls import *
 from .supply_air_temp_reset import *
@@ -67,6 +68,7 @@
     # "optimum_start", # missing
     # "swh_restroom_outlet_maximum_temperature_controls", # missing
     "VAVStaticPressureSensorLocation",
+    "VAVTurndownDuringReheat",
     "VentilationFanControl",
     "WLHPLoopHeatRejectionControl",
     "SupplyAirTempReset",

constrain/library/vav_turndown_during_reheat.py

@@ -0,0 +1,67 @@
+"""
+### Description
+When a VAV box is in reheat mode, the ratio of V_dot_VAV to V_dot_VAV_max should be higher than when it isn't in reheat mode
+
+### Code requirement
+
+- Code Name: ASHRAE 90.1
+- Code Year: 2016
+- Code Section: 6.5.2 Simultaneous Heating and Cooling Limitation
+- Code Subsection: 6.5.2.1 Zone Controls
+
+### Verification Approach
+- We aim to identify how VAV airflow rate varies when the VAV box is and isn't in reheat mode.
+
+### Verification logic
+```
+if (reheat_coil_flag == False).all():
+    Untested
+else:
+    V_dot_VAV_ratio = V_dot_VAV/V_dot_VAV_max
+    mean_reheat_ratio = df.loc[self.df[`reheat_coil_flag`], `V_dot_VAV_ratio`].mean()
+    mean_no_reheat_ratio = df.loc[~self.df[`reheat_coil_flag`], `V_dot_VAV_ratio`].mean()
+
+    if mean_reheat_ratio < mean_no_reheat_ratio:
+        pass
+    else:
+        fail
+```
+### Data requirements
+- reheat_coil_flag: VAV box reheat coil operation status
+- V_dot_VAV: actual VAV volume flow
+- V_dot_VAV_max: max VAV volume flow
+
+"""
+
+from constrain.checklib import RuleCheckBase
+
+
+class VAVTurndownDuringReheat(RuleCheckBase):
+    points = [
+        "reheat_coil_flag",
+        "V_dot_VAV",
+        "V_dot_VAV_max",
+    ]
+
+    def verify(self):
+        # Make sure every value in `V_dot_VAV_max` is greater than 0
+        assert (
+            self.df["V_dot_VAV_max"] > 0
+        ).all(), "Not all `V_dot_VAV_max` values are greater than 0"
+
+        # Check if the `reheat_coil_flag` column has only False values
+        if (self.df["reheat_coil_flag"] == False).all():
+            self.df["result"] = "Untested"
+        else:
+            self.df["V_dot_VAV_ratio"] = self.df["V_dot_VAV"] / self.df["V_dot_VAV_max"]
+
+            # Calculate the mean ratios for reheat and no reheat conditions
+            mean_reheat_ratio = self.df.loc[
+                self.df["reheat_coil_flag"], "V_dot_VAV_ratio"
+            ].mean()
+            mean_no_reheat_ratio = self.df.loc[
+                ~self.df["reheat_coil_flag"], "V_dot_VAV_ratio"
+            ].mean()
+            self.df["result"] = mean_reheat_ratio < mean_no_reheat_ratio
+
+        self.result = self.df["result"]

schema/library.json

@@ -1558,5 +1558,32 @@
             "        pass",
             "end"
         ]
+    },
+    "VAVTurndownDuringReheat": {
+    "library_item_id": 68,
+    "description_brief": "When a VAV box is in reheat mode, the ratio of V_dot_VAV to V_dot_VAV_max should be higher than when it isn't in reheat mode",
+    "description_index": [
+       "Section 6.5.2.1 ASHRAE 90.1-2016"
+    ],
+    "description_datapoints": {
+       "reheat_coil_flag": "VAV box reheat coil operation status",
+       "V_dot_VAV": "VAV airflow rate",
+       "V_dot_VAV_max": "VAV max airflow rate"
+    },
+    "description_verification_type": "procedure-based",
+    "assertions_type": "pass",
+    "description_assertions": [
+       "if (reheat_coil_flag == False).all():", 
+       "    Untested",
+       "else: ",
+       "  V_dot_VAV_ratio = V_dot_VAV/V_dot_VAV_max",
+       "  mean_reheat_ratio = df.loc[self.df[`reheat_coil_flag`], `V_dot_VAV_ratio`].mean()",
+       "  mean_no_reheat_ratio = df.loc[~self.df[`reheat_coil_flag`], `V_dot_VAV_ratio`].mean()",
+       "  if mean_reheat_ratio < mean_no_reheat_ratio:",
+       "    pass",
+       "  else: ",
+       "    fail",
+       "end"
+    ]
     }
 }

tests/test_vav_turndown_during_reheat.py

@@ -0,0 +1,129 @@
+import sys
+import unittest
+
+sys.path.append("./constrain")
+import datetime
+
+import pandas as pd
+from lib_unit_test_runner import *
+
+
+class TestVAVTurndown(unittest.TestCase):
+    def test_vav_turndown_during_reheat_pass(self):
+        points = [
+            "reheat_coil_flag",
+            "V_dot_VAV",
+            "V_dot_VAV_max",
+        ]
+
+        timestamp = [
+            datetime(2024, 8, 1, 12, 0, 0),
+            datetime(2024, 8, 1, 13, 0, 0),
+            datetime(2024, 8, 1, 14, 0, 0),
+            datetime(2024, 8, 1, 15, 0, 0),
+        ]
+
+        data = [
+            [True, 350, 620],
+            [True, 370, 620],
+            [False, 360, 620],
+            [False, 380, 620],
+        ]
+
+        df = pd.DataFrame(data, columns=points, index=timestamp)
+
+        verification_obj = run_test_verification_with_data(
+            "VAVTurndownDuringReheat", df
+        )
+
+        results = pd.Series(list(verification_obj.result))
+        expected_results = pd.Series(
+            [
+                True,
+                True,
+                True,
+                True,
+            ]
+        )
+        self.assertTrue(results.equals(expected_results))
+
+        binary_result = verification_obj.check_bool()
+        self.assertTrue(binary_result)
+
+    def test_vav_turndown_during_reheat_fail(self):
+        points = [
+            "reheat_coil_flag",
+            "V_dot_VAV",
+            "V_dot_VAV_max",
+        ]
+
+        timestamp = [
+            datetime(2024, 8, 1, 12, 0, 0),
+            datetime(2024, 8, 1, 13, 0, 0),
+            datetime(2024, 8, 1, 14, 0, 0),
+            datetime(2024, 8, 1, 15, 0, 0),
+        ]
+
+        data = [
+            [False, 350, 620],
+            [False, 370, 620],
+            [True, 360, 620],
+            [True, 380, 620],
+        ]
+
+        df = pd.DataFrame(data, columns=points, index=timestamp)
+
+        verification_obj = run_test_verification_with_data(
+            "VAVTurndownDuringReheat", df
+        )
+
+        results = pd.Series(list(verification_obj.result))
+        expected_results = pd.Series(
+            [
+                False,
+                False,
+                False,
+                False,
+            ]
+        )
+        self.assertTrue(results.equals(expected_results))
+
+        binary_result = verification_obj.check_bool()
+        self.assertFalse(binary_result)
+
+    def test_vav_turndown_during_reheat_untested(self):
+        points = [
+            "reheat_coil_flag",
+            "V_dot_VAV",
+            "V_dot_VAV_max",
+        ]
+
+        timestamp = [
+            datetime(2024, 8, 1, 12, 0, 0),
+            datetime(2024, 8, 1, 13, 0, 0),
+            datetime(2024, 8, 1, 14, 0, 0),
+            datetime(2024, 8, 1, 15, 0, 0),
+        ]
+
+        data = [
+            [False, 350, 620],
+            [False, 370, 620],
+            [False, 360, 620],
+            [False, 380, 620],
+        ]
+
+        df = pd.DataFrame(data, columns=points, index=timestamp)
+
+        verification_obj = run_test_verification_with_data(
+            "VAVTurndownDuringReheat", df
+        )
+        results = list(verification_obj.result)
+        expected_results = [
+            "Untested",
+            "Untested",
+            "Untested",
+            "Untested",
+        ]
+
+        self.assertEqual(results, expected_results)
+        self.assertEqual(verification_obj.check_bool(), "Untested")