merge campus-decarb (#2)

* streamlit cloud hack

* path hack print

* add logger

* streamlit hack

* add supabase dev

* add power plants

* add power plants and fix seeding and migrations

* create npm scripts

.gitignore

@@ -157,3 +157,5 @@ cython_debug/
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
+
+node_modules/

.vscode/settings.json

@@ -1,12 +1,18 @@
 {
   "[python]": {
-    "editor.defaultFormatter": "ms-python.black-formatter",
-    "editor.formatOnSave": true,
     "editor.codeActionsOnSave": {
       "source.organizeImports": "explicit"
-    }
+    },
+    "editor.defaultFormatter": "ms-python.black-formatter",
+    "editor.formatOnSave": true
   },
-  "isort.args": ["--profile", "black"],
+  "isort.args": [
+    "--profile",
+    "black"
+  ],
   "jupyter.notebookFileRoot": "${workspaceFolder}",
-  "python.envFile": "${workspaceFolder}/.env"
+  "python.envFile": "${workspaceFolder}/.env",
+  "terminal.integrated.env.windows": {
+    "PYTHONPATH": "${workspaceFolder}"
+  }
 }

README.md

@@ -2,3 +2,11 @@
 Materials for MIT Campus Decarbonization Study
 
 ![Technology Overview](./figures/technology-overview.drawio.png)
+
+## Setup
+
+1. Install npm, conda (maybe docker)
+2. npm i
+3. npm run conda-setup
+4. npx supabase init (?? maybe) && npx supabase login && npx supabase link
+5. npm run db-refresh

data/seed.py

@@ -0,0 +1,112 @@
+import math
+
+import numpy as np
+import pandas as pd
+from sqlmodel import Session
+
+from lib.models import (
+    Building,
+    BuildingSimulationResult,
+    DemandScenario,
+    DemandScenarioBuilding,
+    DesignVector,
+    PowerPlant,
+    PowerPlantScenario,
+    engine,
+)
+
+df = pd.read_csv("data/mit_buildings_info.csv")
+results_df = pd.read_hdf("data/5out.hdf", key="results")
+with Session(engine) as session:
+    ds = DemandScenario(
+        name="Test Data Scenario", description="Test Data Scenario", year_available=2030
+    )
+    dv = DesignVector(name="Test Design Vector")
+    bsrs = []
+
+    for i, row in df.iterrows():
+        building = Building(
+            name=row["BUILDING_NAME_LONG"],
+            building_number=row["BUILDING_NUMBER"],
+            group_level_1=row["BUILDING_GROUP_LEVEL1"],
+            usage=row["CLUSTER_NUM"],
+            gfa=(
+                row["EXT_GROSS_AREA"] if not math.isnan(row["EXT_GROSS_AREA"]) else None
+            ),
+            height=(
+                row["BUILDING_HEIGHT"]
+                if not math.isnan(row["BUILDING_HEIGHT"])
+                else None
+            ),
+            year=(
+                row["YEAR_CONST_BEGAN"]
+                if not math.isnan(row["YEAR_CONST_BEGAN"])
+                else None
+            ),
+        )
+        bsr = BuildingSimulationResult(
+            demand_scenario_building=DemandScenarioBuilding(
+                building=building, demand_scenario=ds, design_vector=dv
+            ),
+            heating=results_df[
+                f"Zone Ideal Loads Supply Air Total Heating Energy"
+            ].values.tolist(),
+            cooling=results_df[
+                f"Zone Ideal Loads Supply Air Total Cooling Energy"
+            ].values.tolist(),
+            lighting=results_df[f"Zone Lights Electricity Energy"].values.tolist(),
+            equipment=results_df[
+                f"Zone Electric Equipment Electricity Energy"
+            ].values.tolist(),
+        )
+        bsrs.append(bsr)
+    session.add_all(bsrs)
+
+    pv = PowerPlant(
+        name="Photovoltaics",
+        description="Photovoltaic Panels on the roof",
+        nominal_capacity=100,
+        nominal_cost=0.01,
+        nominal_emissions_factor=0,
+    )
+    grid = PowerPlant(
+        name="Grid",
+        description="The municipal power grid",
+        nominal_capacity=99999,
+        nominal_cost=0.24,
+        nominal_emissions_factor=23,
+    )
+    cup = PowerPlant(
+        name="CUP",
+        description="The campus combined utility plant",
+        nominal_capacity=40000,  # 40 MW
+        nominal_cost=0.01,
+        nominal_emissions_factor=0,
+    )
+    session.add_all([pv, grid, cup])
+
+    t = np.linspace(0, 365 * 2 * np.pi, 8761)
+    t = t[:-1]
+    ts = pd.date_range(start="2020-01-01", end="2020-12-31", freq="h")[:-1]
+    y = np.sin(t - 2 * np.pi / 3).clip(0, 1) * ((-np.cos(t / 365) + 1) / 4 + 0.5)
+
+    pv_50 = PowerPlantScenario(
+        power_plant=pv,
+        name="50% PV Coverage",
+        description="50% of the available roof space is covered in PV panels",
+        year_available=2030,
+        capacities=y * 500,
+        emissions_factors=np.zeros(8760),
+        cost_factors=np.zeros(8760),
+    )
+    pv_70 = PowerPlantScenario(
+        power_plant=pv,
+        name="75% PV Coverage",
+        description="75% of the available roof space is covered in PV panels",
+        year_available=2040,
+        capacities=y * 75,
+        emissions_factors=np.zeros(8760),
+        cost_factors=np.zeros(8760),
+    )
+    session.add_all([pv_50, pv_70])
+    session.commit()

environment.yml

@@ -0,0 +1,6 @@
+name: mit-campus-decarbonization
+dependencies:
+  - python=3.9
+  - pip
+  - pip:
+    - -r requirements.txt