{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "542f0b2d-0afa-4816-977c-17e9862ff957",
   "metadata": {},
   "source": [
    "# PV+Storage Example with Subhourly Inputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "eacbe96a-a39e-444d-92ab-0bf7a5ddfde1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import time\n",
    "import os\n",
    "from generation_models import (BatteryParams, PVSystemDesign, PVGenerationModel, DCExternalGenerationModel,\n",
    "                               PVStorageModel, MultiStorageInputs, SingleAxisTracking, TableCapDegradationModel,\n",
    "                               DARTPrices, StorageCoupling, TermUnits, SolarResource, SolarResourceTimeSeries,\n",
    "                               DCProductionProfile)\n",
    "from tyba_client.client import Client\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e90a5e2f-15af-4ef5-a34c-fcf3bb94d4cb",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "PAT = os.environ[\"TYBA_PAT\"]\n",
    "client = Client(PAT, host=os.getenv(\"HOST\", \"https://dev.tybaenergy.com\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "816cfd76-7fae-462b-a783-7bf7e8813b98",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Example 1: Subhourly irradiance and prices"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69624ab0-7e13-4aa6-b2ea-025a787d6672",
   "metadata": {},
   "source": [
    "### Build model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "710a3263-e012-4e56-acba-0fa3d30eb3c9",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "solar_resource = SolarResource(\n",
    "    typical=False,\n",
    "    latitude=40.0,\n",
    "    longitude=-80.0,\n",
    "    time_zone_offset=-7.0,\n",
    "    elevation=354,\n",
    "    monthly_albedo=12 * [0.6],\n",
    "    data=SolarResourceTimeSeries(\n",
    "        **pd.read_csv(\"tgy-30min-06-01-to-06-07.csv\").to_dict(orient=\"list\")\n",
    "    )\n",
    ")\n",
    "\n",
    "pv = PVGenerationModel(\n",
    "    project_term=168,\n",
    "    project_term_units=TermUnits.hours,\n",
    "    time_interval_mins=30,\n",
    "    solar_resource=solar_resource,\n",
    "    inverter=\"Delta Electronics: M80U_XXX [480V]\",\n",
    "    pv_module=\"Boviet Solar Technology Co._ Ltd. BVM6612M-315\",\n",
    "    system_design=PVSystemDesign(\n",
    "        dc_capacity=2000.0,\n",
    "        ac_capacity=1500.0,\n",
    "        poi_limit=15000.0,\n",
    "        gcr=0.38,\n",
    "        tracking=SingleAxisTracking(rotation_limit=45.0,\n",
    "                                    backtrack=True)\n",
    "    ),\n",
    "    array_degradation_mode=None\n",
    ")\n",
    "\n",
    "battery = BatteryParams(\n",
    "                power_capacity=2000.0,\n",
    "                energy_capacity=4000.0,\n",
    "                charge_efficiency=0.93,\n",
    "                discharge_efficiency=0.93,\n",
    "                capacity_degradation_model=TableCapDegradationModel(annual_capacity_derates=[1.0, 0.]),\n",
    "                term=1\n",
    ")\n",
    "\n",
    "storage_inputs = MultiStorageInputs(batteries=[battery])\n",
    "\n",
    "prices = DARTPrices(\n",
    "    rtm=np.random.random(336).tolist(),\n",
    "    dam=np.random.random(168).tolist()\n",
    ")\n",
    "\n",
    "import_limit = (-np.random.random(336) * 2000).tolist()\n",
    "\n",
    "model = PVStorageModel(\n",
    "    energy_prices=prices,\n",
    "    time_interval_mins=30,\n",
    "    import_limit=import_limit,\n",
    "    storage_inputs=storage_inputs,\n",
    "    storage_coupling=StorageCoupling.dc,\n",
    "    pv_inputs=pv,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb7503df-7bb3-4315-b614-58f01ed64e6a",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Run model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "4af04b8b-dd56-48cd-920b-07e2298d0dc7",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "res = client.schedule(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "9b7d5af8-1832-42fe-ace7-eeb490b1770b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "id_ = res.json()[\"id\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f5285c4c-e6e0-4f81-9517-d6b4f5545d3c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "res = client.wait_on_result_v1(id_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "a74d6862-a178-4a40-9886-a433c2963e02",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "197144.83167240454"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res[\"hourly\"][\"poi\"][\"power_kW\"].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "288cee36-43b7-4c79-97ed-f410d07e1ced",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Example 2: Subhourly external generation and prices"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b98d1bc2-21ef-48fb-bbbd-b2a152f79322",
   "metadata": {},
   "source": [
    "### Build model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "dc2d88a8-f79a-451d-807c-549b8b4c1ca1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "pv = DCExternalGenerationModel(\n",
    "    project_term=24,\n",
    "    project_term_units=TermUnits.hours,\n",
    "    time_interval_mins=15,\n",
    "    system_design=model.pv_inputs.system_design,\n",
    "    inverter=model.pv_inputs.inverter,\n",
    "    production_override=DCProductionProfile(\n",
    "        **(pd.read_csv(\"dc-external-generation-15min-06-01.csv\").\n",
    "           rename(columns={\"array_dc_power\": \"power\", \"array_dc_voltage\": \"voltage\"}).\n",
    "           to_dict(orient=\"list\"))\n",
    "    )\n",
    ")\n",
    "\n",
    "prices = DARTPrices(\n",
    "    rtm=np.random.random(96).tolist(),\n",
    "    dam=np.random.random(24).tolist()\n",
    ")\n",
    "\n",
    "import_limit = (-np.random.random(96) * 2000).tolist()\n",
    "\n",
    "model = PVStorageModel(\n",
    "    energy_prices=prices,\n",
    "    time_interval_mins=15,\n",
    "    import_limit=import_limit,\n",
    "    storage_inputs=storage_inputs,\n",
    "    storage_coupling=StorageCoupling.dc,\n",
    "    pv_inputs=pv,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c283e678-39ba-4c81-94b2-91fed031de81",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Run model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "61580bdc-fdbf-4332-9ea2-6d2855794284",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "res = client.schedule(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "507d31e2-3ee0-481c-8420-0a7d2e297167",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "id_ = res.json()[\"id\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "6361166b-b665-47fe-9ae9-ddae52433c4b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "res = client.wait_on_result_v1(id_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "17966f93-d451-4fdd-817e-6fd5f5f4196c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "88357.40427243654"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res[\"hourly\"][\"poi\"][\"power_kW\"].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c3a0329-2413-49c8-b001-b51fdd20c64b",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Example 3: Hourly irradiance and subhourly prices"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acd8d19b-ac4d-479f-b389-fb42aa4ce3bd",
   "metadata": {},
   "source": [
    "### Build model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "9552b2ca-9e19-4bfa-a699-40613a21795b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "irradiance_30min = pd.read_csv(\"tgy-30min-06-01-to-06-07.csv\")\n",
    "irradiance_30min.index = pd.date_range(start=\"1990-06-01T00:00:00\", periods=336, freq=\"30T\")\n",
    "irradiance_hourly = irradiance_30min.resample(\"H\").mean()\n",
    "\n",
    "solar_resource = SolarResource(\n",
    "    typical=False,\n",
    "    latitude=40.0,\n",
    "    longitude=-80.0,\n",
    "    time_zone_offset=-7.0,\n",
    "    elevation=354,\n",
    "    monthly_albedo=12 * [0.6],\n",
    "    data=SolarResourceTimeSeries(\n",
    "        **irradiance_hourly.to_dict(orient=\"list\")\n",
    "    )\n",
    ")\n",
    "\n",
    "pv = PVGenerationModel(\n",
    "    project_term=168,\n",
    "    project_term_units=TermUnits.hours,\n",
    "    time_interval_mins=60,  # this is where we indicate that it is an hourly solar resource\n",
    "    solar_resource=solar_resource,\n",
    "    inverter=\"Delta Electronics: M80U_XXX [480V]\",\n",
    "    pv_module=\"Boviet Solar Technology Co._ Ltd. BVM6612M-315\",\n",
    "    system_design=PVSystemDesign(\n",
    "        dc_capacity=2000.0,\n",
    "        ac_capacity=1500.0,\n",
    "        poi_limit=15000.0,\n",
    "        gcr=0.38,\n",
    "        tracking=SingleAxisTracking(rotation_limit=45.0,\n",
    "                                    backtrack=True)\n",
    "    ),\n",
    "    array_degradation_mode=None\n",
    ")\n",
    "\n",
    "prices = DARTPrices(\n",
    "    rtm=np.random.random(672).tolist(),\n",
    "    dam=np.random.random(168).tolist()\n",
    ")\n",
    "\n",
    "import_limit = (-np.random.random(672) * 2000).tolist()\n",
    "\n",
    "model = PVStorageModel(\n",
    "    energy_prices=prices,\n",
    "    time_interval_mins=15,  # this is where we indicate that our prices are subhourly\n",
    "    import_limit=import_limit,\n",
    "    storage_inputs=storage_inputs,\n",
    "    storage_coupling=StorageCoupling.dc,\n",
    "    pv_inputs=pv,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a9213da-8cac-48f5-ab30-c4ac25d6ba01",
   "metadata": {},
   "source": [
    "### Run model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "bb9b1a17-f37d-482b-8375-1fc3d46143ae",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "res = client.schedule(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "fa55d6c1-70c8-46b4-8374-35b1cf585f3a",
   "metadata": {},
   "outputs": [],
   "source": [
    "_id = res.json()[\"id\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "afdc8ab8-9f65-4883-8c8d-d7c60bd225e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "res = client.wait_on_result_v1(id_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "6f6d546d-ca7b-4896-b8d6-4924bb2714c4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "88357.40427243654"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res[\"hourly\"][\"poi\"][\"power_kW\"].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d934ff56-63f9-4031-b612-a542c3b278a1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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