Use rts_gmlc data package for Double Loop (#183)

gmlc-dispatches · May 24, 2023 · e1ef58b · e1ef58b
1 parent 08c117a
commit e1ef58b
Show file tree

Hide file tree

Showing 5 changed files with 20 additions and 18 deletions.
diff --git a/...a_supercritical_plant/storage/double_loop_integrated_ultrasupercritical_power_plant.ipynb b/...a_supercritical_plant/storage/double_loop_integrated_ultrasupercritical_power_plant.ipynb
@@ -81,8 +81,7 @@
     "from prescient.simulator import Prescient\n",
     "\n",
     "# Import integrated ultra-supercritical power plant with energy storage model\n",
-    "from dispatches.case_studies.fossil_case.ultra_supercritical_plant.storage.multiperiod_double_loop_usc import MultiPeriodUsc\n",
-    "from dispatches_sample_data import rts_gmlc"
+    "from dispatches.case_studies.fossil_case.ultra_supercritical_plant.storage.multiperiod_double_loop_usc import MultiPeriodUsc"
    ]
   },
   {
@@ -1713,7 +1712,7 @@
    "metadata": {},
    "source": [
     "**IMPORTANT** Before proceeding with the rest of the notebook:\n",
-    "1. Install the `dispatches-sample-data` package by running `pip install dispatches-sample-data` in the working conda environment\n",
+    "1. Install the `rts_gmlc` data package by running `pip install dispatches-rts-gmlc-data` in the working conda environment\n",
     "\n",
     "OR\n",
     "\n",
@@ -1728,11 +1727,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# If installing the dispatches-sample-data\n",
-    "rts_gmlc_data_dir = str(rts_gmlc.source_data_path)\n",
+    "# If installing the `rts_gmlc` data package\n",
+    "from dispatches_data.api import path\n",
+    "rts_gmlc_data_dir = str(path(\"rts_gmlc\") / \"SourceData\")\n",
     "\n",
     "# If downloading the data to the local machine use the following option with appropriate path\n",
-    "# rts_gmlc_data_dir = \"/projects/gmihybridsys/dguittet/data/RTS-GMLC/RTS_Data/SourceData\"\n"
+    "# rts_gmlc_data_dir = \"/projects/gmihybridsys/dguittet/data/RTS-GMLC/RTS_Data/SourceData\""
    ]
   },
   {

diff --git a/dispatches/case_studies/nuclear_case/nuclear_flowsheet_double_loop.ipynb b/dispatches/case_studies/nuclear_case/nuclear_flowsheet_double_loop.ipynb
@@ -58,9 +58,8 @@
     "from idaes.core.solvers import get_solver\n",
     "from idaes.apps.grid_integration.model_data import ThermalGeneratorModelData\n",
     "\n",
-    "# Import Prescient and the RTS-GMLC dataset\n",
+    "# Import Prescient\n",
     "from prescient.simulator import Prescient\n",
-    "from dispatches_sample_data import rts_gmlc\n",
     "\n",
     "# Import nuclear flowsheet\n",
     "from dispatches.case_studies.nuclear_case.nuclear_flowsheet_multiperiod_class import MultiPeriodNuclear"
@@ -540,12 +539,12 @@
     "\n",
     "**IMPORTANT** Before proceeding with the rest of the notebook:\n",
     "\n",
-    "1. Install the `dispatches-sample-data` package by running `pip install dispatches-sample-data` in the terminal\n",
+    "1. Install the `rts_gmlc` data package by running `pip install dispatches-rts-gmlc-data` in the working conda environment\n",
     "\n",
     "OR\n",
     "\n",
-    "1. Download the RTS-GMLC dataset from [this repository](https://github.com/GridMod/RTS-GMLC) (or directly as a zipfile [here](https://github.com/GridMod/RTS-GMLC/archive/refs/heads/master.zip)) to your local machine\n",
-    "2. Update the value of the `rst_gmlc_data_dir` variable in the cell below to the appropriate location of the `RTS_Data/SourceData` subfolder on your local machine."
+    "1. Download the RTS-GMLC dataset from [https://github.com/GridMod/RTS-GMLC] (or directly as a zipfile here) to your local machine\n",
+    "2. Update the value of the `rst_gmlc_data_dir` variable in the cell below to the appropriate location of the `RTS_Data/SourceData` subfolder on your local machine"
    ]
   },
   {
@@ -9869,8 +9868,9 @@
     }
    ],
    "source": [
+    "from dispatches_data.api import path\n",
     "# Folder containing the RTS - GMLC data\n",
-    "rts_gmlc_data_dir = str(rts_gmlc.source_data_path)\n",
+    "rts_gmlc_data_dir = str(path(\"rts_gmlc\") / \"SourceData\")\n",
     "\n",
     "# Set Prescient options\n",
     "options = {\n",
@@ -10042,7 +10042,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.7.10 ('hybrid')",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },

diff --git a/dispatches/case_studies/renewables_case/DoubleLoopOptimization.ipynb b/dispatches/case_studies/renewables_case/DoubleLoopOptimization.ipynb
@@ -16,7 +16,7 @@
     "import pyomo.environ as pyo\n",
     "import idaes\n",
     "\n",
-    "from dispatches_sample_data import rts_gmlc\n",
+    "from dispatches_data.api import path\n",
     "from dispatches.case_studies.renewables_case.wind_battery_double_loop import MultiPeriodWindBattery\n",
     "from dispatches.case_studies.renewables_case.double_loop_utils import *\n",
     "\n",
@@ -76,6 +76,7 @@
     "import os\n",
     "\n",
     "TESTING_MODE = bool(os.environ.get(\"DISPATCHES_TESTING_MODE\", None))\n",
+    "rts_gmlc_source_data_path = path(\"rts_gmlc\") / \"SourceData\"\n",
     "\n",
     "sim_days = 7 if not TESTING_MODE else 1\n",
     "start_date = \"01-02-2020\"\n",
@@ -88,7 +89,7 @@
     "wind_generator = f\"{wind_bus}_WIND_1\"\n",
     "\n",
     "prescient_options = {\n",
-    "    \"data_path\": rts_gmlc.source_data_path,\n",
+    "    \"data_path\": str(rts_gmlc_source_data_path),\n",
     "    \"input_format\": \"rts-gmlc\",\n",
     "    \"simulate_out_of_sample\": True,\n",
     "    \"run_sced_with_persistent_forecast_errors\": True,\n",
@@ -1866,7 +1867,7 @@
     "pd.set_option('display.max_rows', None)\n",
     "plt.style.use('seaborn')\n",
     "\n",
-    "df = double_loop_outputs_for_gen(output_dir, rts_gmlc.source_data_path)\n",
+    "df = double_loop_outputs_for_gen(output_dir, rts_gmlc_source_data_path)\n",
     "prescient_df = df[df['Model'] == \"Prescient\"].copy()\n",
     "da_bidder_df = df[df['Model'] == \"DA Bidder\"].copy()\n",
     "rt_bidder_df = df[df['Model'] == \"RT Bidder\"].copy()\n",

diff --git a/dispatches/case_studies/renewables_case/run_double_loop.py b/dispatches/case_studies/renewables_case/run_double_loop.py
@@ -32,7 +32,7 @@
 from pyomo.common.fileutils import this_file_dir
 import pandas as pd
 from pathlib import Path
-from dispatches_sample_data import rts_gmlc
+from dispatches_data.api import path
 
 this_file_path = Path(this_file_dir())
 
@@ -130,7 +130,7 @@
 gen_capacity_factor = prescient_outputs_df[f"{wind_generator}-RTCF"].values.tolist()
 
 # NOTE: `rts_gmlc_data_dir` should point to a directory containing RTS-GMLC scenarios
-rts_gmlc_data_dir = rts_gmlc.source_data_path
+rts_gmlc_data_dir = path("rts_gmlc") / "SourceData"
 output_dir = Path(f"sim_{sim_id}_results")
 
 solver = pyo.SolverFactory("xpress_direct")

diff --git a/setup.py b/setup.py
@@ -121,6 +121,7 @@ class SpecialDependencies:
         "gridx-prescient>=2.2.2",
         "nrel-pysam>=3.0.1",
         "dispatches-data-packages >= 23.3.19",
+        "dispatches-rts-gmlc-data @ git+https://github.com/gmlc-dispatches/rts-gmlc-data@main",
         *SPECIAL_DEPENDENCIES
     ],
     extras_require={