Multi-Site Example Script

REopt API Scripts/archived_v2_scripts/multi_scenario_example.ipynb

@@ -300,9 +300,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "py36",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "py36"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -314,7 +314,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.8.8"
   }
  },
  "nbformat": 4,

REopt API Scripts/inputs/site_2.json

@@ -0,0 +1 @@
+{"Site": {"latitude": 39.5611, "longitude": -107.29351, "land_acres": 10, "roof_squarefeet": 0}, "ElectricLoad": {"doe_reference_name": "Hospital", "year": 2023, "critical_load_fraction": 1, "loads_kw_is_net": 1}, "Generator": {"existing_kw": 120, "om_cost_per_kw": 16, "fuel_cost_per_gallon": 4}, "ElectricUtility": {"net_metering_limit_kw": 1000}, "ElectricTariff": {"blended_annual_energy_rate": 0.2, "blended_annual_demand_rate": 10, "wholesale_rate": 0}, "Financial": {"om_cost_escalation_rate_fraction": 0.02, "elec_cost_escalation_rate_fraction": 0.01, "generator_fuel_cost_escalation_rate_fraction": 0.01}, "PV": {"existing_kw": 50, "min_kw": 0, "array_type": 0, "installed_cost_per_kw": 2000, "tilt": 20, "azimuth": 270, "federal_itc_fraction": 0.4}, "ElectricStorage": {"min_kw": 0, "min_kwh": 0, "installed_cost_per_kw": 919.1, "installed_cost_per_kwh": 459.55, "replace_cost_per_kw": 722.15, "replace_cost_per_kwh": 321.18}, "Wind": {"max_kw": 0}}

REopt API Scripts/inputs/site_3.json

@@ -0,0 +1 @@
+{"Site": {"latitude": 40.011965, "longitude": -75.099488}, "ElectricLoad": {"doe_reference_name": "StripMall", "annual_kwh": 500000, "year": 2023, "loads_kw_is_net": false}, "Generator": {"om_cost_per_kw": false}, "ElectricUtility": {"net_metering_limit_kw": false}, "ElectricTariff": {"blended_annual_energy_rate": 0.15, "blended_annual_demand_rate": false, "wholesale_rate": false}, "PV": {"existing_kw": false, "array_type": 2, "installed_cost_per_kw": 3500}, "ElectricStorage": {"min_kw": false, "min_kwh": false, "installed_cost_per_kw": 819, "installed_cost_per_kwh": 409.5, "replace_cost_per_kw": 643.5, "replace_cost_per_kwh": 286.2}, "Wind": {"max_kw": false}}

REopt API Scripts/multiple_runs.ipynb

@@ -0,0 +1,337 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "dced6536",
+   "metadata": {},
+   "source": [
+    "# TODO: \n",
+    "- determine a good example of inputs to use in the example Excel\n",
+    "- improve the instructions in the Excel\n",
+    "- consider moving some functions to src file\n",
+    "- Improve error checking\n",
+    "- Add resilience inputs and outage time selection\n",
+    "- Could add scenario description and save the site + description\n",
+    "- Finish the output file generation with the 3 options\n",
+    "\n",
+    "# MVP: \n",
+    "- Electric only\n",
+    "- Don't worry about Google Colab (user clones Repo, modifies Excel, downloads results to local (cloned) folder)\n",
+    "- Minimal error checking "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "b43b54b7",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ImportError",
+     "evalue": "Unable to import required dependencies:\nnumpy: Error importing numpy: you should not try to import numpy from\n        its source directory; please exit the numpy source tree, and relaunch\n        your python interpreter from there.",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
+      "\u001b[31mImportError\u001b[39m                               Traceback (most recent call last)",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mpandas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mpd\u001b[39;00m\n\u001b[32m      2\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnumpy\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnp\u001b[39;00m\n\u001b[32m      3\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mjson\u001b[39;00m\n",
+      "\u001b[36mFile \u001b[39m\u001b[32m~/Library/Python/3.13/lib/python/site-packages/pandas/__init__.py:19\u001b[39m\n\u001b[32m     16\u001b[39m         _missing_dependencies.append(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m_dependency\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m_e\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m)\n\u001b[32m     18\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m _missing_dependencies:  \u001b[38;5;66;03m# pragma: no cover\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m19\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m(\n\u001b[32m     20\u001b[39m         \u001b[33m\"\u001b[39m\u001b[33mUnable to import required dependencies:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33m\"\u001b[39m + \u001b[33m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33m\"\u001b[39m.join(_missing_dependencies)\n\u001b[32m     21\u001b[39m     )\n\u001b[32m     22\u001b[39m \u001b[38;5;28;01mdel\u001b[39;00m _hard_dependencies, _dependency, _missing_dependencies\n\u001b[32m     24\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m     25\u001b[39m     \u001b[38;5;66;03m# numpy compat\u001b[39;00m\n",
+      "\u001b[31mImportError\u001b[39m: Unable to import required dependencies:\nnumpy: Error importing numpy: you should not try to import numpy from\n        its source directory; please exit the numpy source tree, and relaunch\n        your python interpreter from there."
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import json\n",
+    "import requests\n",
+    "import copy\n",
+    "import os\n",
+    "from src.post_and_poll import get_api_results\n",
+    "\n",
+    "root_url = \"https://developer.nrel.gov/api/reopt/stable\"\n",
+    "\n",
+    "API_KEY = 'DEMO_KEY'  # REPLACE WITH YOUR API KEY"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e4269b73",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# following is not necessary but silences warnings:\n",
+    "# InsecureRequestWarning: Unverified HTTPS request is being made to host 'developer.nrel.gov'. Adding certificate verification is strongly advised.\n",
+    "import urllib3\n",
+    "urllib3.disable_warnings()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8c07f411",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Specify file name: \n",
+    "data_file = \"multi_site_inputs.xlsx\"\n",
+    "\n",
+    "##############################################################################################################\n",
+    "site_data =  os.path.join(\".\", 'multi_site_inputs', data_file)\n",
+    "posts_path = os.path.join(\".\", 'inputs') # To save posts\n",
+    "outputs_path = os.path.join(\".\", 'outputs')\n",
+    "rates_path = os.path.join(\".\", 'electric_rates')\n",
+    "results_summary_path = os.path.join(\".\", 'results_summary')\n",
+    "##############################################################################################################"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "82eb329c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get Data\n",
+    "df_site = pd.read_excel(site_data, sheet_name=\"reopt_inputs\", index_col=0) \n",
+    "df_loads = pd.read_excel(site_data, sheet_name=\"interval_load\", index_col=0)  \n",
+    "df_monthly_loads = pd.read_excel(site_data, sheet_name=\"monthly_loads\", index_col=0)  "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d5093ffc",
+   "metadata": {},
+   "source": [
+    "## The code below is draft and needs a lot of improvement"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e619f318",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create posts Dict by site then scenario\n",
+    "# e.g., posts[site_name]\n",
+    "\n",
+    "posts = dict() # Dictionary for all posts by site name\n",
+    "for site in df_site: # iterate over sites\n",
+    "    post = dict()\n",
+    "    # Populate all site-specific inputs from Excel\n",
+    "    for label in df_site[site].keys():\n",
+    "        val = df_site[site][label]\n",
+    "        if not pd.isna(val): # ignore empty entries\n",
+    "            key, subkey = label.split(\" | \")\n",
+    "            if key not in post:\n",
+    "                post[key] = {}\n",
+    "            # Check if custom utility rate json is provided\n",
+    "            if subkey == \"urdb_response\":\n",
+    "                with open(os.path.join(rates_path, val), 'r') as fp:\n",
+    "                    post[key][subkey] = json.load(fp)\n",
+    "            else:\n",
+    "                post[key][subkey] = val\n",
+    "\n",
+    "    ## Add load and correct timesteps per hour ## \n",
+    "    if sum(df_loads[site]) > 0:\n",
+    "        load_profile = df_loads[site].to_list()\n",
+    "        load_profile = [float(v) for v in load_profile] \n",
+    "        post[\"ElectricLoad\"][\"loads_kw\"] = load_profile\n",
+    "\n",
+    "\n",
+    "    # Add post to dict\n",
+    "    posts[site] = copy.deepcopy(post)\n",
+    "\n",
+    "    with open(os.path.join(posts_path, site + \".json\"), 'w') as fp:\n",
+    "        json.dump(posts[site], fp)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f8da992f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "responses = []\n",
+    "\n",
+    "for site in df_site:\n",
+    "    responses.append(\n",
+    "        get_api_results(\n",
+    "            posts[site], \n",
+    "            results_file=os.path.join(outputs_path, site + '.json'),\n",
+    "            api_url=root_url, \n",
+    "            API_KEY=API_KEY\n",
+    "        )\n",
+    "    )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f710931f",
+   "metadata": {},
+   "source": [
+    "### Optionally load saved responses"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b1d98850",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "responses = []\n",
+    "\n",
+    "for site in df_site:\n",
+    "    with open(os.path.join(outputs_path, site + \".json\"), 'r') as fp:\n",
+    "        responses.append(json.load(fp))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "57f63ebb",
+   "metadata": {},
+   "source": [
+    "### Summarizing multiple scenario results\n",
+    "\n",
+    "There are two options for making a summary of multiple scenarios' resutls:\n",
+    "1. Write to a csv using a template with column headers for desired summary keys (scalar values only)\n",
+    "2. Write all inputs, outputs, and dispatch to an Excel spreadsheet\n",
+    "^^TBD\n",
+    "3. Use the `generation_results_table` endpoint to create a summary Excel\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e7cd3a5c",
+   "metadata": {},
+   "source": [
+    "#### Option 1: Use a template CSV to collect certain results"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "f78b226d",
+   "metadata": {},
+   "source": [
+    "from src.parse_api_responses_to_csv import parse_responses_to_csv_with_template\n",
+    "\n",
+    "parse_responses_to_csv_with_template(\n",
+    "    csv_template=output_template, \n",
+    "    responses=responses, \n",
+    "    output_csv=output_file, \n",
+    "    input_csv=path_to_inputs,\n",
+    "    n_custom_columns=2\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "1c77162f",
+   "metadata": {},
+   "source": [
+    "#### Option 2: Write all results out to an Excel file"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "3b11e792",
+   "metadata": {},
+   "source": [
+    "from src.parse_api_responses_to_excel import parse_api_responses_to_excel\n",
+    "\n",
+    "parse_api_responses_to_excel(responses, template=output_file_spreadsheet_template, spreadsheet=output_file_spreadsheet)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c321502f",
+   "metadata": {},
+   "source": [
+    "#### Option 3: Use Results Spreadsheet API endpoint\n",
+    "/job/generate_results_table - takes a list of run_uuid's and creates a results table spreadsheet to download in response"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6c451d7a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "run_uuids = []\n",
+    "for response in responses:\n",
+    "    run_uuids.append(response[\"run_uuid\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c6f3fa78",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Construct the URL with run_uuid[] as query parameters\n",
+    "results_url = f\"{root_url}/job/generate_results_table/?api_key={API_KEY}&table_config_name=custom_table_webtool\"\n",
+    "\n",
+    "for i, uuid in enumerate(run_uuids):\n",
+    "    results_url += f\"&run_uuid%5B{i}%5D={uuid}\"\n",
+    "\n",
+    "print(f\"Requesting custom comparison table from: {results_url}\")\n",
+    "\n",
+    "try:\n",
+    "    # Make the GET request to retrieve the final comparison table\n",
+    "    response = requests.get(results_url)\n",
+    "    response.raise_for_status()  # Raise an exception for HTTP errors\n",
+    "\n",
+    "    # Check the response and save the Excel file\n",
+    "    if response.status_code == 200:\n",
+    "        os.makedirs(results_summary_path, exist_ok=True)\n",
+    "        output_path = os.path.join(results_summary_path, f'{uuid}-results-table.xlsx')\n",
+    "        \n",
+    "        with open(output_path, \"wb\") as o:\n",
+    "            o.write(response.content)\n",
+    "        print(f\"File saved to {output_path}\")\n",
+    "    else:\n",
+    "        print(f\"Request failed with status code {response.status_code}: {response.text}\")\n",
+    "except requests.exceptions.RequestException as e:\n",
+    "    print(f\"Request failed: {e}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5a6e3fc0",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "@webio": {
+   "lastCommId": null,
+   "lastKernelId": null
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

REopt API Scripts/outputs/results_template.csv

@@ -0,0 +1 @@
+Financial | npv,PV|size_kw,Storage|size_kw,Storage|size_kwh