main-Copy1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.9/site-packages/diffcp/cones.py:7: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.\n",
      "  if StrictVersion(scs.__version__) >= StrictVersion('3.0.0'):\n"
     ]
    }
   ],
   "source": [
    "# Run this again after editing submodules so Colab uses the updated versions\n",
    "from citylearn import  CityLearn\n",
    "from pathlib import Path\n",
    "from agent_final import Agent\n",
    "import numpy as np                                                                                                                                                                                      \n",
    "import torch\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time taken to add RBC pretrained model (sec): 15.295\n"
     ]
    }
   ],
   "source": [
    "# Load environment\n",
    "climate_zone = 1\n",
    "end_time = 8759 # total number of hours to train for\n",
    "cost_analysis = 1 # analyze costs every x hours\n",
    "checkpoint = 24 * 7 # save parameters every x hours\n",
    "\n",
    "params = {'data_path':Path(\"data/Climate_Zone_\"+str(climate_zone)), \n",
    "        'building_attributes':'building_attributes.json', \n",
    "        'weather_file':'weather_data.csv', \n",
    "        'solar_profile':'solar_generation_1kW.csv', \n",
    "        'carbon_intensity':'carbon_intensity.csv',\n",
    "        'building_ids':[\"Building_\"+str(i) for i in [1,2,3,4,5,6,7,8,9]],\n",
    "        'buildings_states_actions':'buildings_state_action_space.json', \n",
    "        'simulation_period': (0, end_time), \n",
    "        'cost_function': ['ramping','1-load_factor','average_daily_peak','peak_demand','net_electricity_consumption','carbon_emissions'], \n",
    "        'central_agent': False,\n",
    "        'cost_analysis' : cost_analysis,\n",
    "        'save_memory': False }\n",
    "\n",
    "# Contain the lower and upper bounds of the states and actions, to be provided to the agent to normalize the variables between 0 and 1.\n",
    "env = CityLearn(**params)\n",
    "env.pretrain_baseline_model((0, end_time))\n",
    "\n",
    "observations_spaces, actions_spaces = env.get_state_action_spaces()\n",
    "\n",
    "# Provides information on Building type, Climate Zone, Annual DHW demand, Annual Cooling Demand, Annual Electricity Demand, Solar Capacity, and correllations among buildings\n",
    "building_info = env.get_building_information()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 8759\t0.9646747113342953"
     ]
    }
   ],
   "source": [
    "params_agent = {'building_ids':[\"Building_\"+str(i) for i in [1,2,3,4,5,6,7,8,9]],\n",
    "                 'buildings_states_actions':'buildings_state_action_space.json', \n",
    "                 'building_info':building_info,\n",
    "                 'observation_spaces':observations_spaces, \n",
    "                 'action_spaces':actions_spaces}\n",
    "\n",
    "# Instantiating the control agent(s)\n",
    "agents = Agent(**params_agent)\n",
    "\n",
    "state = env.reset()\n",
    "rewards = []\n",
    "done = False\n",
    "\n",
    "action, coordination_vars = agents.select_action(state)    \n",
    "while not done:\n",
    "    next_state, reward, done, _ = env.step(action)\n",
    "    action_next, coordination_vars_next = agents.select_action(next_state)\n",
    "    agents.add_to_buffer(state, action, reward, next_state, done, coordination_vars, coordination_vars_next)\n",
    "    coordination_vars = coordination_vars_next\n",
    "    state = next_state\n",
    "    action = action_next\n",
    "    \n",
    "    rewards.append(reward)\n",
    "    \n",
    "    try:\n",
    "        print(f\"\\r {env.time_step}\\t{env.costs_periodic[-1]['total']}\", end=\"\")\n",
    "    except:\n",
    "        print(f\"\\r {env.time_step}\", end=\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "({'ramping': 0.8334678,\n",
       "  '1-load_factor': 1.009951287773328,\n",
       "  'average_daily_peak': 0.98590493,\n",
       "  'peak_demand': 0.9535845,\n",
       "  'net_electricity_consumption': 1.0021087,\n",
       "  'carbon_emissions': 1.0026032,\n",
       "  'total': 0.964603393320752,\n",
       "  'coordination_score': 0.945727123386432},\n",
       " <citylearn.CityLearn at 0x16ca52520>)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env.cost((0, end_time))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [],
   "source": [
    "rewards = np.array(rewards)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-66989084.0"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rewards[23:].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1b107f9a0>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "total = [x[\"total\"] for x in env.costs_periodic]\n",
    "plt.plot(total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'ramping': 0.9699096557151906,\n",
       " 'c_score': [0.9699096557151906,\n",
       "  0.9788221142227707,\n",
       "  0.979309698213766,\n",
       "  1.1282838948296476],\n",
       " '1-load_factor': 0.9788221142227707,\n",
       " 'average_daily_peak': 0.979309698213766,\n",
       " 'peak_demand': 1.1282838948296476,\n",
       " 'net_electricity_consumption': 0.9917744744336325,\n",
       " 'carbon_emissions': 1.0026032,\n",
       " 'total': 1.008450501778488,\n",
       " 'coordination_score': 1.0140813407453437}"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env.cost_detailed_view()['Building_9']['cost']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Percent improvement over ZOiRL at timestep 100: 42.49906\n",
      "\n",
      "Costs:\n",
      "iAC\tZOiRL\n",
      "0.9678 1.6831\n"
     ]
    }
   ],
   "source": [
    "t = 100\n",
    "val = 0.9678\n",
    "\n",
    "prct = 100 * (total[t]-val)/total[t]\n",
    "print(f\"Percent improvement over ZOiRL at timestep {t}:\", round(prct, 5))\n",
    "print(\"\\nCosts:\\niAC\\tZOiRL\")\n",
    "print(val, round(total[t], 5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.save(\"ZOiRL_cost_curve.npy\", np.array(total).astype('float'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([7303, 7654, 7655, 7656, 7657, 7658, 7659, 7660, 7661, 7662, 7663,\n",
       "       7664, 7665, 7666, 7667, 7668, 7669, 7670, 7671, 7672, 7673, 7674,\n",
       "       7675, 7676, 7677, 7678, 7679, 7680, 7681, 7682, 7683, 7684, 7685,\n",
       "       7686, 7687, 7688, 7689, 7690, 7691, 7692, 7693, 7694, 7695, 7696,\n",
       "       7697, 7698, 7699, 7700, 7701, 7702, 7703, 7704, 7705, 7706, 7707,\n",
       "       7708, 7709, 7710, 7711, 7712, 7713, 7714, 7715, 7716, 7717, 7718,\n",
       "       7719, 7720, 7721, 7722, 7723, 7724, 7725, 7726, 7727, 7728, 7729,\n",
       "       7730, 7731, 7732, 7733, 7734, 7735, 7736, 7737, 7738, 7739, 7740,\n",
       "       7741, 7742, 7743, 7744, 7745, 7746, 7747, 7748, 7749, 7750, 7751,\n",
       "       7752, 7753, 7754, 7755, 7756, 7757, 7758, 7759, 7760, 7761, 7762,\n",
       "       7763, 7764, 7765, 7766, 7767, 7768, 7769, 7770, 7771, 7772, 7773,\n",
       "       7774, 7775, 7776, 7777, 7778, 7779, 7780, 7781, 7782])"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.where(np.round(total, 3) == 0.971)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = np.array(rewards).sum(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = [-13305841.  ,  -1528339.1 ,   -198965.83,  -2546601.5 ,\n",
    "         -839678.8 ,   -735418.1 ,  -2175609.8 ,  -1733047.5 ,\n",
    "        -1797031.2 ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.bar(range(9), b/t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(range(9), np.array(rewards)[670:1000].sum(0), label=\"ZOiRL\")\n",
    "plt.plot(range(9), np.array([-16319.555, -15670.224, -15415.637, -15499.423, -16534.404,\n",
    "       -16515.965, -16483.883, -16411.252, -16348.079]), label='iAC')\n",
    "plt.legend()\n",
    "plt.xlabel(\"Building #\")\n",
    "plt.ylabel(\"Total Reward\")\n",
    "plt.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = np.array(rewards)[670:1000].sum(0)\n",
    "b = np.array([-16319.555, -15670.224, -15415.637, -15499.423, -16534.404,\n",
    "       -16515.965, -16483.883, -16411.252, -16348.079])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import defaultdict\n",
    "table = defaultdict(list)\n",
    "\n",
    "for x in env.costs_periodic:\n",
    "    for k, v in x.items():\n",
    "        table[k].append(v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(table['total'][:len(iAC)], label=\"ZOiRL\", c='k')\n",
    "plt.plot(iAC_table['total'], label='iAC', c='r')\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.legend()\n",
    "plt.xlabel(\"Day\")\n",
    "plt.ylabel(\"Cost\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "marlisa = np.load(\"marlisa_data.npy\", allow_pickle=True)\n",
    "marlisa_table = defaultdict(list)\n",
    "\n",
    "for x in marlisa:\n",
    "    for k, v in x.items():\n",
    "        marlisa_table[k].append(v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "iAC = np.load(\"data_dump_iAC_citylearn.npy\", allow_pickle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "iAC_table = defaultdict(list)\n",
    "\n",
    "for x in iAC:\n",
    "    for k, v in x.items():\n",
    "        iAC_table[k].append(v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TD3\n",
    "ramping = [1.6408246, 1.4672998, 1.3830278, 1.4102416, 1.3850541, 1.3373524, 1.2857156, 1.2383511, 1.2096213, 1.1981359, 1.2008797, 1.1899372, 1.1858847, 1.1842233, 1.1686779, 1.1558695, 1.1514367, 1.1568676, 1.1571136, 1.148671, 1.1397798, 1.1324131, 1.131419, 1.1319308, 1.1334032, 1.134596, 1.1304994, 1.1278232, 1.1204554, 1.1152571, 1.1163068, 1.1155102, 1.1163634, 1.1146011, 1.1070217, 1.1024026, 1.0954634, 1.0954148, 1.0952126, 1.0978539, 1.100697, 1.0970919, 1.0931375, 1.0908266, 1.0901895, 1.0895677, 1.0922472, 1.0910561, 1.0896846, 1.0875734, 1.0857042, 1.0876977, 1.0873407, 1.0891107, 1.0907421, 1.0915874, 1.0906432, 1.0892891, 1.089237, 1.0931611, 1.0940537, 1.0948043, 1.0912731, 1.0913295, 1.0903126, 1.0903635, 1.0937033, 1.0942866, 1.0944316, 1.0946215, 1.0973945, 1.1002713, 1.100023, 1.1039792, 1.1051707, 1.1057757, 1.1061488, 1.1079739, 1.1078157, 1.1087136, 1.1130307, 1.1133378, 1.112504, 1.1148671, 1.1178775, 1.1193519, 1.1182108, 1.121588, 1.121665, 1.1220908, 1.1218873, 1.1208982, 1.1248231, 1.1270224, 1.129939, 1.130632, 1.1301627, 1.1309204, 1.1326156, 1.1350209, 1.1387016, 1.1423805, 1.1426716, 1.1421475, 1.1418895, 1.1420102, 1.1436352, 1.1452799, 1.1475186, 1.1457891, 1.1457397, 1.1446786, 1.144607, 1.1479313, 1.1503305, 1.1515608, 1.1502663, 1.1489729, 1.1471792, 1.1464882, 1.1484064, 1.1485231, 1.1493578, 1.1477966, 1.1487696, 1.1487213, 1.1487787, 1.1499672, 1.1504023, 1.1529696, 1.1519735, 1.151791, 1.151225, 1.1516937, 1.1544129, 1.1563408, 1.1583738, 1.1579839, 1.1590598, 1.1599132, 1.1627249, 1.1634243, 1.166161, 1.1679602, 1.166444, 1.1675959, 1.167341, 1.166951, 1.1670514, 1.1679454, 1.1698384, 1.1706797, 1.1705751, 1.170086, 1.171258, 1.1728595, 1.173028, 1.1749095, 1.1752468, 1.1740024, 1.1742121, 1.1737752, 1.1755046, 1.176316, 1.1778072, 1.1780703, 1.1792399, 1.1790025, 1.179197, 1.1808813, 1.1816906, 1.1821355, 1.1824687, 1.1813176, 1.1796254, 1.1810279, 1.1834228, 1.1836236, 1.1845435, 1.1861641, 1.1865599, 1.186062, 1.1863283, 1.1881816, 1.1886065, 1.1900438, 1.1898905, 1.1910397, 1.1905824, 1.1920193, 1.1945692, 1.1955645, 1.1965659, 1.1968961, 1.197513, 1.1966634, 1.1964326, 1.1983043, 1.1981975, 1.1985868, 1.199487, 1.1989886, 1.1986393, 1.1998259, 1.2015804, 1.2012684, 1.2019242, 1.2009636, 1.2012843, 1.2015798, 1.202334, 1.204067, 1.2047348, 1.2057117, 1.205853, 1.206182, 1.2057185, 1.2064009, 1.2075093, 1.2078366, 1.2085127, 1.2082269, 1.208193, 1.2078946, 1.2085502, 1.2096473, 1.2112484, 1.2116241, 1.2118125, 1.2117379, 1.2113214, 1.2127008, 1.213278, 1.2140453, 1.2146288, 1.214214, 1.214431, 1.2152172, 1.2159121, 1.2171816, 1.217759, 1.2182151, 1.218859, 1.2186732, 1.2189596, 1.2195908, 1.2209265, 1.221305, 1.2226617, 1.2232609, 1.2235489, 1.223478, 1.2239377, 1.2235742, 1.2232022, 1.2236648, 1.2232147, 1.2234566, 1.2231122, 1.2234848, 1.2242987, 1.2241443, 1.2245752, 1.225133, 1.2260598, 1.2262121, 1.2268368, 1.2275792, 1.2265584, 1.2276646, 1.227458, 1.2272872, 1.2268953, 1.2263064, 1.2264593, 1.2268816, 1.2276297, 1.2273965, 1.2272995, 1.227658, 1.2276592, 1.2284667, 1.2289966, 1.2298193, 1.2293501, 1.2292686, 1.2283844, 1.2280169, 1.2288016, 1.2289052, 1.2293184, 1.2295146, 1.2295331, 1.2298973, 1.2300771, 1.2303493, 1.2305806, 1.2309597, 1.2306145, 1.230985, 1.2309587, 1.2305667, 1.230897, 1.2313548, 1.2306999, 1.2306103, 1.2304888, 1.2306621, 1.2303252, 1.2301345, 1.2302856, 1.2307357, 1.2296064, 1.2291185, 1.2287303, 1.2280276, 1.227931, 1.2275819, 1.2270509, 1.2266374, 1.2261204, 1.2258537, 1.2246544, 1.223896, 1.2239709, 1.2235272, 1.2222168, 1.2213695, 1.2209129, 1.2203488, 1.2201588, 1.2196429, 1.2189369, 1.218543, 1.2176169, 1.2166579, 1.2162201, 1.2154132, 1.2146187, 1.2144132, 1.2145897, 1.2137747, 1.2132587, 1.2126861, 1.2118379, 1.2115669, 1.2112164, 1.2111018, 1.2109988, 1.2109033, 1.2106153, 1.2100203, 1.2092547, 1.2093625, 1.2095809, 1.2092957, 1.2086278, 1.2084969, 1.2080028, 1.2073747, 1.2071042, 1.2068822, 1.2065532, 1.205801]\n",
    "load_factor = [0.8871146196529502, 0.969647028884587, 1.0086387485428618, 1.0822452787112709, 1.0783466760101132, 1.074393847581331, 1.0762324734191242, 1.0751104800575186, 1.0780890578042175, 1.1056943464737388, 1.112949574868301, 1.1129904204365335, 1.1129944360323685, 1.1215404477096051, 1.1161062307628846, 1.111653329070037, 1.1099625147623708, 1.1158830139644673, 1.1181880784433478, 1.1191000499747734, 1.148039412133053, 1.1456831419058393, 1.1448496523597609, 1.1442721012974706, 1.1424063308700814, 1.1606730969831327, 1.1552354295208778, 1.1554123661239553, 1.15487787162458, 1.158031344770131, 1.147950230235671, 1.2281138094216681, 1.2182272948007113, 1.201069942595552, 1.1920537123709427, 1.1780666206802177, 1.1808582661446043, 1.181839393708981, 1.1814330428515079, 1.1825965494270183, 1.1825035379728985, 1.1814911466032383, 1.1756406297660285, 1.1747254389800994, 1.173457122928126, 1.1758384779937383, 1.1738298815291666, 1.174904232697012, 1.1724498383106485, 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    "average_daily_peak = [0.9400095, 1.0354282, 1.0718305, 1.0800471, 1.0849262, 1.1083254, 1.111899, 1.1072242, 1.1123571, 1.1134901, 1.1128566, 1.1176682, 1.1243738, 1.1231899, 1.1083543, 1.1084613, 1.110266, 1.1129931, 1.1170506, 1.122493, 1.1247315, 1.1142285, 1.1216669, 1.120724, 1.1220434, 1.1286198, 1.1280712, 1.1305441, 1.1230278, 1.125453, 1.1287407, 1.131326, 1.1340225, 1.1371638, 1.1353765, 1.1328917, 1.1320479, 1.1323929, 1.1334873, 1.1338288, 1.1345761, 1.1336886, 1.1315106, 1.133701, 1.1328374, 1.1336366, 1.1338359, 1.1350365, 1.1342554, 1.1330384, 1.1322564, 1.1335125, 1.1332718, 1.1344901, 1.1371017, 1.1386689, 1.137135, 1.1398379, 1.1392436, 1.1392267, 1.1417547, 1.1427143, 1.1424918, 1.1420124, 1.1429459, 1.143512, 1.1436726, 1.1440121, 1.1472744, 1.1498653, 1.1497228, 1.1500657, 1.1490607, 1.1526269, 1.1547619, 1.158355, 1.162047, 1.1642016, 1.1648513, 1.1644206, 1.1659368, 1.1665677, 1.1692307, 1.1725712, 1.1717588, 1.1745259, 1.1738076, 1.1771408, 1.1785772, 1.17962, 1.1801449, 1.1785488, 1.1785719, 1.1790739, 1.1814364, 1.1818694, 1.1838009, 1.1870126, 1.1883523, 1.188896, 1.1911432, 1.191766, 1.1928097, 1.1925534, 1.1937101, 1.1920216, 1.1916375, 1.1925082, 1.1924317, 1.1911278, 1.1923212, 1.194612, 1.195164, 1.1967038, 1.1973648, 1.1983778, 1.1979642, 1.1984657, 1.198066, 1.197404, 1.197434, 1.196098, 1.1978481, 1.198079, 1.1992394, 1.2003248, 1.201801, 1.2016076, 1.2006035, 1.2002383, 1.2002584, 1.2004585, 1.2010841, 1.2012599, 1.202512, 1.2033051, 1.2044649, 1.2056586, 1.2067279, 1.2074528, 1.2078211, 1.2073028, 1.2079216, 1.2079023, 1.2070076, 1.2060983, 1.2068474, 1.2079912, 1.2071953, 1.2070754, 1.2080591, 1.208863, 1.2087649, 1.2096714, 1.2106082, 1.2106853, 1.2102793, 1.2110145, 1.211734, 1.210519, 1.211466, 1.2115738, 1.2121019, 1.2113197, 1.2111319, 1.211346, 1.211117, 1.2119294, 1.2122788, 1.2114669, 1.2100894, 1.2089456, 1.208158, 1.2068075, 1.2056139, 1.206512, 1.206789, 1.207038, 1.2072458, 1.2077658, 1.2078657, 1.2084702, 1.2092657, 1.2091206, 1.2089775, 1.2084725, 1.2081647, 1.2083544, 1.208157, 1.2088783, 1.2091974, 1.2093054, 1.2085636, 1.2086644, 1.2092994, 1.2088624, 1.2088145, 1.2081668, 1.2071869, 1.2062191, 1.2060562, 1.2048059, 1.2036703, 1.2033426, 1.2032683, 1.2028226, 1.202839, 1.2019634, 1.2017245, 1.2017932, 1.2025559, 1.2027116, 1.2028546, 1.2027991, 1.2021697, 1.2028234, 1.202791, 1.202822, 1.2028805, 1.203299, 1.2034049, 1.2037349, 1.2037873, 1.2039505, 1.2036631, 1.2038176, 1.2038064, 1.2037479, 1.2037042, 1.2026299, 1.2022882, 1.2022877, 1.201587, 1.2019511, 1.2019783, 1.2017374, 1.2013696, 1.2016199, 1.2015798, 1.2016139, 1.2013338, 1.2009896, 1.2008448, 1.2009203, 1.2010581, 1.2008905, 1.2012111, 1.2010969, 1.2012968, 1.2015039, 1.2016338, 1.2021174, 1.2024736, 1.202386, 1.2025607, 1.2027295, 1.2026515, 1.2024677, 1.202831, 1.2032305, 1.2035048, 1.203771, 1.2035055, 1.203707, 1.2036246, 1.2039821, 1.20443, 1.2047645, 1.204512, 1.2046967, 1.2050964, 1.2049185, 1.2049766, 1.2050167, 1.2047724, 1.2054305, 1.2061385, 1.2067186, 1.2071602, 1.2078441, 1.2083713, 1.2084215, 1.2088743, 1.2091068, 1.2090726, 1.2088643, 1.2091322, 1.2097367, 1.2101824, 1.210687, 1.2112176, 1.2114754, 1.2117769, 1.2123795, 1.212632, 1.2124976, 1.2126896, 1.2124698, 1.2119893, 1.2123507, 1.2124388, 1.2124875, 1.2121559, 1.2118663, 1.2117324, 1.2118235, 1.211965, 1.2118101, 1.2114412, 1.2115318, 1.2114977, 1.2117792, 1.2123351, 1.2121052, 1.2122126, 1.2119514, 1.2121704, 1.2123375, 1.2123003, 1.2127194, 1.213339, 1.2133589, 1.213059, 1.2132133, 1.2132351, 1.2132896, 1.2129523, 1.2129598, 1.2130017, 1.2125965, 1.2126638, 1.2126313, 1.2124914, 1.2124462, 1.2123497, 1.2122135, 1.2116172, 1.2116512, 1.2114655, 1.2113701, 1.2113502, 1.2115264, 1.2114125, 1.2111092, 1.2109264, 1.2109075, 1.2107892, 1.210909, 1.2114897, 1.2115808, 1.2110505, 1.2112877, 1.2112435, 1.211591, 1.2114258, 1.2116232, 1.2115344, 1.211102, 1.2108195, 1.2105843, 1.2104819, 1.2103043, 1.2102988, 1.2101653]\n",
    "peak_demand = [0.9400095, 0.98322135, 1.0147727, 1.0683142, 1.0683142, 1.0683142, 1.0683142, 1.0683142, 1.0683142, 1.088352, 1.0963398, 1.0963398, 1.0963398, 1.1020509, 1.1020509, 1.1020509, 1.1020509, 1.1048108, 1.1048108, 1.1048108, 1.13965, 1.13965, 1.13965, 1.13965, 1.13965, 1.1690027, 1.1665319, 1.1665319, 1.1665319, 1.1665319, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2007141, 1.2170405, 1.2170405, 1.2170405, 1.2527634, 1.2527634, 1.2527634, 1.2527634, 1.2527634, 1.2057023, 1.2057023, 1.2057023, 1.2057023, 1.2057023, 1.2057023, 1.2057023, 1.2057023, 1.2057023, 1.2057023, 1.2057023, 1.2057023, 1.2057023, 1.2057023, 1.2057023, 1.2057023, 1.2925627, 1.2925627, 1.2925627, 1.2925627, 1.2925627, 1.2925627, 1.2925627, 1.2925627, 1.2925627, 1.2925627, 1.3002841, 1.29142, 1.29142, 1.29142, 1.2911264, 1.2911264, 1.2911264, 1.2911264, 1.2911264, 1.3313316, 1.3313316, 1.3240355, 1.3240355, 1.3240355, 1.3240355, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3385035, 1.3309718, 1.3309718, 1.3309718, 1.3309718, 1.3309718, 1.3309718, 1.3309718, 1.3309718, 1.3309718, 1.3309718, 1.3309718, 1.3309718, 1.3309718, 1.3309718, 1.3310755, 1.2941571, 1.2941571, 1.2765002, 1.2765002, 1.2765002, 1.2765002, 1.1481986, 1.1631354, 1.1631354, 1.1631354, 1.1631354, 1.1631354, 1.1631354, 1.1631354, 1.1631354, 1.1631354, 1.1631354, 1.1631354, 1.1631354, 1.1631354, 1.1494998, 1.1494998, 1.1494998, 1.1636958, 1.147486, 1.147486, 1.147486, 1.147486, 1.147486, 1.147486, 1.1494554, 1.1301887, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.132118, 1.0920223, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.0984584, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154, 1.1078154]\n",
    "net_electricity_consumption = [1.0244666, 1.0034143, 1.0039369, 0.99915016, 0.9973158, 0.9969881, 0.9947349, 0.99194777, 0.9905309, 0.9884002, 0.98820615, 0.9874182, 0.98710465, 0.98614866, 0.9838895, 0.982044, 0.9830501, 0.9832143, 0.98386383, 0.98434424, 0.98469687, 0.98519754, 0.986463, 0.9858029, 0.9861977, 0.9880799, 0.9876084, 0.9877142, 0.9874703, 0.9874979, 0.98852324, 0.98844206, 0.98839355, 0.9890601, 0.98832834, 0.9878669, 0.9875374, 0.9877527, 0.9873977, 0.9870546, 0.98714334, 0.9869522, 0.9861726, 0.98654544, 0.9863819, 0.98588705, 0.9863141, 0.98663306, 0.98642063, 0.9860313, 0.9863597, 0.9867849, 0.9863936, 0.98674655, 0.98743737, 0.98786247, 0.98747647, 0.98832434, 0.9884531, 0.9883714, 0.98865056, 0.98876786, 0.988515, 0.98828775, 0.9882188, 0.9885384, 0.9882808, 0.988042, 0.9882839, 0.9883811, 0.9882268, 0.98838425, 0.9882469, 0.98864037, 0.98888034, 0.98945516, 0.9897055, 0.9900518, 0.98995036, 0.98996323, 0.99029595, 0.9901087, 0.9906338, 0.9909353, 0.9907321, 0.9910393, 0.99095476, 0.9914255, 0.99147385, 0.9916963, 0.991505, 0.9913298, 0.9912924, 0.9914531, 0.9919664, 0.99210674, 0.99250126, 0.99250644, 0.99278086, 0.9929013, 0.9931526, 0.99333006, 0.99338746, 0.9934719, 0.9933976, 0.9932051, 0.99319065, 0.9932533, 0.9931699, 0.99338275, 0.9936135, 0.99371785, 0.993826, 0.9940515, 0.9942616, 0.9943472, 0.9944558, 0.99455374, 0.9944147, 0.99428034, 0.99437964, 0.99433875, 0.99462014, 0.9945371, 0.9947478, 0.99501747, 0.99512607, 0.99508727, 0.99510527, 0.9951919, 0.99527156, 0.99535465, 0.9953464, 0.9953435, 0.9955749, 0.99568796, 0.99575543, 0.9959886, 0.99615043, 0.9961984, 0.9961849, 0.99628985, 0.9963706, 0.9965011, 0.99653965, 0.9965324, 0.9967882, 0.996845, 0.9967283, 0.99672014, 0.9968837, 0.99702287, 0.997024, 0.9971392, 0.99722767, 0.99734515, 0.99728435, 0.9972973, 0.9973835, 0.9973707, 0.99747986, 0.99746877, 0.9975468, 0.9975964, 0.99766743, 0.99763346, 0.99768645, 0.99776226, 0.99781036, 0.9978658, 0.99782336, 0.99788034, 0.99786115, 0.99783593, 0.9978086, 0.9978767, 0.9979077, 0.99789673, 0.9979045, 0.99790543, 0.9979322, 0.9980733, 0.9981358, 0.9981385, 0.9980825, 0.9980975, 0.99812466, 0.9981718, 0.9981649, 0.99821573, 0.9983348, 0.9983473, 0.9983859, 0.99840736, 0.99841917, 0.9983921, 0.9983472, 0.9983547, 0.9983665, 0.9983556, 0.9983371, 0.9983464, 0.9983773, 0.9983969, 0.9984745, 0.99843234, 0.99842125, 0.99841523, 0.9984914, 0.9985189, 0.9985027, 0.99860203, 0.99861825, 0.9986481, 0.99861014, 0.9986216, 0.9986239, 0.9986273, 0.9986153, 0.9986406, 0.99860895, 0.9986755, 0.9987103, 0.99866927, 0.99863935, 0.9986789, 0.99866, 0.9986832, 0.9986938, 0.9986812, 0.9986651, 0.9986984, 0.9986541, 0.998669, 0.9986618, 0.9986514, 0.99865437, 0.9986846, 0.9986795, 0.9986825, 0.9986605, 0.9986605, 0.99867076, 0.99871093, 0.99874365, 0.99871916, 0.9987659, 0.99873674, 0.99869883, 0.9986571, 0.99870175, 0.9986741, 0.9987383, 0.99873704, 0.9986897, 0.9986937, 0.9987706, 0.9987349, 0.99877065, 0.9987851, 0.99876624, 0.9988069, 0.99873424, 0.99878466, 0.99877197, 0.9987391, 0.99871856, 0.9986973, 0.99868923, 0.9986625, 0.9986595, 0.9986485, 0.99857086, 0.99854493, 0.99850166, 0.99852574, 0.9985896, 0.99859977, 0.9986766, 0.99867064, 0.9987026, 0.99866617, 0.9986832, 0.9986908, 0.99867564, 0.99865496, 0.9986784, 0.99869424, 0.99869883, 0.9987687, 0.99877304, 0.9987644, 0.9988258, 0.99880415, 0.9987984, 0.9988127, 0.99880433, 0.9987203, 0.99868, 0.9987133, 0.9986882, 0.9987122, 0.99865305, 0.9986359, 0.9985746, 0.99855083, 0.99854684, 0.9985355, 0.9985097, 0.9984987, 0.9985181, 0.99858797, 0.9986465, 0.9986694, 0.99864453, 0.9986185, 0.9986201, 0.9985725, 0.99851906, 0.99856013, 0.9986119, 0.9986043, 0.9985733, 0.9985677, 0.998541, 0.9985596, 0.99855286, 0.998472, 0.99851644, 0.99850047, 0.9985143, 0.99847674, 0.99842274, 0.9983965, 0.9983829, 0.99832946, 0.99833405, 0.99830765, 0.9982689, 0.9982066, 0.99819845, 0.9982055, 0.9981502, 0.998106, 0.99806136, 0.9980539, 0.9980026, 0.9980192, 0.9980611, 0.998098, 0.9980627, 0.9980994, 0.99807125, 0.99810773, 0.998048, 0.9980865, 0.99806046, 0.9979915, 0.99790406, 0.9978745, 0.9978092, 0.9977632, 0.9978, 0.99775416]\n",
    "carbon_emissions = [1.0393919, 1.0209594, 1.0145211, 1.0100087, 1.0124696, 1.0112706, 1.0074295, 1.0048945, 1.0022217, 0.9998433, 0.99970406, 0.99884963, 0.99944276, 0.99658644, 0.99409384, 0.99173915, 0.99269116, 0.99335825, 0.99308914, 0.9938515, 0.9948874, 0.9956314, 0.9969661, 0.99589825, 0.99655694, 0.9983593, 0.99826694, 0.9980757, 0.99728817, 0.997159, 0.9988942, 0.99905515, 0.9995777, 0.9998683, 0.9986484, 0.9982313, 0.9976712, 0.99750865, 0.996961, 0.99623394, 0.99597526, 0.995448, 0.9944964, 0.9949265, 0.9948387, 0.994167, 0.9951196, 0.9959074, 0.9958346, 0.995745, 0.9965012, 0.9963802, 0.9964548, 0.99713564, 0.9978289, 0.9981776, 0.9981129, 0.9988153, 0.99881625, 0.99896276, 0.9996031, 0.99957645, 0.99916404, 0.998858, 0.9986954, 0.9990134, 0.9986905, 0.9983672, 0.99856937, 0.9987428, 0.9989188, 0.9988819, 0.999104, 0.99938655, 0.99932325, 0.9996901, 1.0000018, 1.0007315, 1.0005136, 1.0008351, 1.0013218, 1.0011718, 1.0016906, 1.0020746, 1.0018817, 1.0023339, 1.0020536, 1.0026177, 1.0025043, 1.0030307, 1.0028522, 1.0027242, 1.0027283, 1.0029882, 1.0032971, 1.0032336, 1.0032967, 1.0031902, 1.0032777, 1.0035964, 1.0038645, 1.0039634, 1.0039359, 1.0038651, 1.0037626, 1.0036284, 1.0038462, 1.0037547, 1.0036901, 1.0039067, 1.0041971, 1.004162, 1.0042719, 1.0045038, 1.0045277, 1.0046319, 1.0046431, 1.0045795, 1.0042326, 1.0041519, 1.0040619, 1.0038404, 1.0041195, 1.004173, 1.0045241, 1.0047493, 1.0047685, 1.0046184, 1.004606, 1.0047337, 1.0047283, 1.0048151, 1.0047792, 1.0046382, 1.0047661, 1.004954, 1.0052242, 1.0053074, 1.0055323, 1.0056053, 1.005609, 1.0056868, 1.0056598, 1.0057262, 1.005711, 1.0055757, 1.0057187, 1.0055697, 1.0052453, 1.0050557, 1.0051161, 1.0052024, 1.0052081, 1.0052844, 1.0054022, 1.005516, 1.0053588, 1.0052326, 1.005291, 1.0052372, 1.0052961, 1.005254, 1.0053722, 1.0053465, 1.0053024, 1.0053496, 1.0053794, 1.0054449, 1.005445, 1.0055064, 1.0053632, 1.0053353, 1.0052578, 1.0052432, 1.0051392, 1.00524, 1.0052168, 1.0051913, 1.0052024, 1.005191, 1.0052078, 1.0054154, 1.005463, 1.0053744, 1.0053134, 1.0053296, 1.0053599, 1.0053475, 1.0053211, 1.0053461, 1.0054308, 1.0053897, 1.0053488, 1.0053369, 1.0053307, 1.0052382, 1.0051408, 1.0051666, 1.0051569, 1.0051017, 1.0050873, 1.0050689, 1.0050502, 1.0050333, 1.0050827, 1.0050316, 1.0050178, 1.0049896, 1.0050102, 1.0049949, 1.0050004, 1.0050834, 1.0050659, 1.0050583, 1.0049942, 1.0049787, 1.0049672, 1.0049746, 1.0049648, 1.0049671, 1.0048778, 1.0049237, 1.004897, 1.004787, 1.0047241, 1.0047711, 1.004767, 1.0047541, 1.0047463, 1.0046839, 1.0046383, 1.0046388, 1.0045793, 1.004582, 1.0045769, 1.0045468, 1.0045294, 1.0045147, 1.0044769, 1.004461, 1.004414, 1.004379, 1.0043788, 1.0044299, 1.0044475, 1.0043887, 1.0044034, 1.0043337, 1.0042403, 1.0041701, 1.0041789, 1.0041529, 1.00423, 1.0041885, 1.0040544, 1.0040882, 1.0041279, 1.0040625, 1.0040543, 1.0040512, 1.0039997, 1.0040135, 1.0039178, 1.0039358, 1.0038826, 1.0038517, 1.0038681, 1.0038264, 1.0037999, 1.0037434, 1.0037361, 1.0037127, 1.0036576, 1.0036404, 1.0035912, 1.0035874, 1.0036477, 1.0036969, 1.0037723, 1.0037978, 1.0038415, 1.0038332, 1.003864, 1.0039014, 1.0038227, 1.0037396, 1.0037712, 1.003811, 1.0038929, 1.0039998, 1.0040122, 1.0040038, 1.0040951, 1.0040886, 1.0041039, 1.0041276, 1.0041504, 1.0041052, 1.004105, 1.0041755, 1.0041715, 1.0042077, 1.0041796, 1.0041736, 1.004116, 1.0041039, 1.0041393, 1.004111, 1.004075, 1.0040566, 1.0040525, 1.0040896, 1.0041279, 1.0041994, 1.0042554, 1.0042403, 1.004256, 1.0041919, 1.0041527, 1.0041862, 1.0042417, 1.0042365, 1.0042502, 1.0042672, 1.0042356, 1.0042592, 1.0042219, 1.0041466, 1.0041801, 1.004199, 1.0042138, 1.0041991, 1.0041984, 1.0042332, 1.0042659, 1.0041939, 1.004222, 1.0041677, 1.0041587, 1.0040935, 1.0040706, 1.0040618, 1.0040095, 1.0039624, 1.0039105, 1.003908, 1.0038748, 1.0039107, 1.0039988, 1.0040467, 1.0040023, 1.0040364, 1.0039942, 1.0040282, 1.0039778, 1.0040537, 1.0040085, 1.0039698, 1.0038913, 1.0039062, 1.0038646, 1.0037935, 1.0038497, 1.0038215]\n",
    "total = [1.0786361035550949, 1.0799949939893292, 1.0827879567416283, 1.1083344786843465, 1.1044044483113435, 1.0994407301142124, 1.0907209648632366, 1.0809736866974147, 1.0768557178865545, 1.0823192948841593, 1.0851559613943795, 1.0838671913923499, 1.084356679453915, 1.0856233251267526, 1.0788621028397845, 1.0753030138659738, 1.0749095499059043, 1.0778544988942544, 1.079019348142347, 1.078878458314845, 1.0886308139615843, 1.0854672843149593, 1.0868358116972023, 1.0863796735871434, 1.0867095931315571, 1.0965551019612005, 1.0943688562482825, 1.094350249148954, 1.0916085955752186, 1.0916550469109423, 1.0968548376573704, 1.1105269048823816, 1.1095497488508674, 1.1070795751526383, 1.1036904471278661, 1.1000288795739177, 1.0990487003419593, 1.0992704200193633, 1.099200968549332, 1.0997136497445967, 1.1002682353567412, 1.0992310317775185, 1.0969453531897135, 1.0969065227709165, 1.0964031170506539, 1.0966351298686638, 1.0970101524580664, 1.0973752701960762, 1.096559861940946, 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   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# A2C\n",
    "_ramping = [1.369717, 1.3420751, 1.3939757, 1.411141, 1.4516006, 1.4395472, 1.4229735, 1.3979692, 1.3893974, 1.397881, 1.389001, 1.3808893, 1.390566, 1.4113431, 1.4094769, 1.3952775, 1.4026531, 1.4070055, 1.4143319, 1.4089644, 1.4021394, 1.4022406, 1.4009254, 1.3983068, 1.3992499, 1.401486, 1.4108796, 1.4128451, 1.4108775, 1.4076574, 1.4150286, 1.4122593, 1.4173226, 1.416426, 1.408824, 1.4017704, 1.3935379, 1.3916534, 1.3900603, 1.3976164, 1.4041483, 1.4022892, 1.3970654, 1.3957001, 1.397954, 1.3994961, 1.4033525, 1.4058073, 1.4068187, 1.4047105, 1.4010484, 1.4067733, 1.4088998, 1.4124067, 1.4113863, 1.4130583, 1.4141774, 1.4105883, 1.415697, 1.4209045, 1.4235041, 1.4268612, 1.424514, 1.4279474, 1.4277792, 1.428212, 1.4337246, 1.4333789, 1.4345936, 1.438314, 1.4446701, 1.451052, 1.4527187, 1.4576384, 1.4596558, 1.4619565, 1.4648391, 1.469795, 1.4676124, 1.4643853, 1.4665663, 1.4653505, 1.4678259, 1.4715866, 1.4730239, 1.4734948, 1.4726039, 1.4771013, 1.4737624, 1.4752878, 1.4759905, 1.4775628, 1.480332, 1.4818423, 1.4881785, 1.4903601, 1.4886007, 1.4907917, 1.4928375, 1.4979846, 1.5007856, 1.5031296, 1.5010839, 1.5022836, 1.501674, 1.5012709, 1.503382, 1.5055734, 1.5097111, 1.5088534, 1.5097864, 1.5086375, 1.5097866, 1.5136974, 1.516363, 1.5177644, 1.5170267, 1.5158045, 1.5153123, 1.5160507, 1.5174643, 1.5193338, 1.520611, 1.5187743, 1.5224758, 1.5244063, 1.5238299, 1.5270776, 1.5272417, 1.5288721, 1.528399, 1.5284612, 1.5273292, 1.5281914, 1.5315831, 1.5333291, 1.5346028, 1.533226, 1.5347471, 1.53455, 1.5366154, 1.5377382, 1.5412608, 1.5442266, 1.5442722, 1.5437006, 1.5440341, 1.5423496, 1.5429292, 1.5449749, 1.5470505, 1.548779, 1.5481858, 1.5488162, 1.5520731, 1.5519063, 1.5511923, 1.5540063, 1.5545776, 1.5517452, 1.5524234, 1.5519422, 1.5542966, 1.5545902, 1.5568767, 1.5577339, 1.557545, 1.5579696, 1.5578604, 1.5582466, 1.558401, 1.5583832, 1.5588874, 1.5571638, 1.5528586, 1.5537953, 1.5553633, 1.5554291, 1.5572816, 1.5592474, 1.5601829, 1.560243, 1.5608097, 1.5626302, 1.5635383, 1.5637808, 1.5632126, 1.5628074, 1.5618623, 1.5646584, 1.5680652, 1.5693033, 1.5699071, 1.5682861, 1.5702605, 1.5702455, 1.569346, 1.5702103, 1.5684577, 1.5696988, 1.5706282, 1.5694121, 1.5678957, 1.5686997, 1.5701498, 1.5703013, 1.5705838, 1.5680611, 1.5680968, 1.5684279, 1.5702507, 1.5725274, 1.5736728, 1.5739232, 1.5740604, 1.5739981, 1.5734537, 1.5745504, 1.5768248, 1.5775832, 1.5773585, 1.5767019, 1.5764875, 1.5767924, 1.5777957, 1.5793629, 1.579969, 1.5795355, 1.5795746, 1.5786561, 1.5776141, 1.5798873, 1.5808668, 1.5826612, 1.5832882, 1.5829828, 1.5828255, 1.5846775, 1.5854667, 1.585082, 1.5855441, 1.5857571, 1.5858604, 1.5847762, 1.5848095, 1.5865177, 1.5887814, 1.5888699, 1.590881, 1.5906044, 1.5902447, 1.5902886, 1.5908821, 1.5906646, 1.590858, 1.5912836, 1.5896382, 1.5889478, 1.5891645, 1.5901737, 1.5906501, 1.5907922, 1.5914053, 1.5917184, 1.5920446, 1.5920486, 1.5935495, 1.5930276, 1.5912533, 1.5920053, 1.5919602, 1.5916269, 1.5917697, 1.5914636, 1.5920258, 1.5927587, 1.5935581, 1.593113, 1.5927485, 1.59196, 1.5920055, 1.5924219, 1.5920494, 1.592269, 1.5913997, 1.5909222, 1.5894253, 1.5888629, 1.5891343, 1.5887568, 1.5895187, 1.5895973, 1.5896682, 1.5902097, 1.5903, 1.5902293, 1.5904298, 1.5911489, 1.590516, 1.590792, 1.5910434, 1.590485, 1.5908198, 1.5912179, 1.5903252, 1.5900009, 1.5900817, 1.5899186, 1.5888519, 1.5883182, 1.5885336, 1.5891873, 1.5879065, 1.5874054, 1.5870199, 1.5863172, 1.5862012, 1.5856866, 1.5852923, 1.5847635, 1.5835042, 1.5826471, 1.5815686, 1.5798097, 1.5796568, 1.5789872, 1.5770924, 1.5753103, 1.5743304, 1.572916, 1.5721786, 1.5713897, 1.5705473, 1.5697645, 1.5678717, 1.5663682, 1.5652287, 1.5641462, 1.5632067, 1.5632524, 1.5632981, 1.5623416, 1.5622364, 1.5614742, 1.5604676, 1.5597976, 1.5592893, 1.5589805, 1.5588233, 1.558543, 1.5584147, 1.5574204, 1.5561101, 1.5566726, 1.5570128, 1.5572249, 1.5563823, 1.5563201, 1.5554138, 1.555616, 1.555241, 1.5552077, 1.5552188, 1.5544193]\n",
    "_load_factor = [0.8751932032117297, 0.9469971333973691, 1.0067894094935037, 1.0931730845791106, 1.086941254216624, 1.0828286689154978, 1.0841040394494583, 1.0830288265646382, 1.0936824413438209, 1.1530808173614555, 1.153786839143937, 1.1539301658944798, 1.1538019293900523, 1.159007829105434, 1.1518283508678764, 1.1453726544437606, 1.143570639869973, 1.1532325164233723, 1.156150820369526, 1.1691800178764686, 1.179875953666888, 1.1769940635402745, 1.175978739718299, 1.1752014497417558, 1.1727446034487672, 1.1897996158000266, 1.1773983407666386, 1.177574382939808, 1.1771012081960484, 1.1805964975773613, 1.160142340204778, 1.2578237702947022, 1.2434935112902652, 1.2255848138840442, 1.2130559984385834, 1.1979527740345253, 1.2005870341034401, 1.2021229630918173, 1.2012151596412008, 1.2020908183499468, 1.2026017401011964, 1.201392403756403, 1.194903575518858, 1.1937512918156055, 1.1924992268601637, 1.1947375039450756, 1.192851561543468, 1.1941077046434931, 1.1913694407980309, 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    "_average_daily_peak = [0.93807155, 1.0393068, 1.0871208, 1.097127, 1.1002107, 1.1129249, 1.1164688, 1.1183248, 1.1304773, 1.1334538, 1.1315291, 1.1351043, 1.1431801, 1.1407558, 1.1286538, 1.1256142, 1.1263049, 1.1274549, 1.1330333, 1.1413381, 1.1403117, 1.1308007, 1.1366587, 1.1345958, 1.1349128, 1.1423497, 1.14296, 1.146743, 1.1423547, 1.1444095, 1.1463126, 1.147949, 1.1519686, 1.1548071, 1.1532052, 1.1500278, 1.1490848, 1.1493653, 1.1501204, 1.1512734, 1.1534963, 1.1539183, 1.1510766, 1.1520393, 1.151222, 1.1529557, 1.1529002, 1.1547298, 1.1533093, 1.152726, 1.1519258, 1.1545957, 1.1564986, 1.1562276, 1.1563573, 1.1578482, 1.156682, 1.1571552, 1.1585711, 1.1587666, 1.1613662, 1.1631036, 1.1623411, 1.161822, 1.1634382, 1.1638777, 1.1641977, 1.1640717, 1.1675103, 1.17029, 1.1701355, 1.1714206, 1.170404, 1.1743397, 1.1763855, 1.1800447, 1.1838675, 1.1855483, 1.185717, 1.185396, 1.1868504, 1.1872383, 1.1905432, 1.1942726, 1.1939399, 1.1961372, 1.1975155, 1.2000186, 1.2010678, 1.2025241, 1.2032337, 1.2020338, 1.2019008, 1.202213, 1.2047485, 1.2058536, 1.207505, 1.2102839, 1.2123265, 1.2140203, 1.2156403, 1.2164563, 1.2167342, 1.2173023, 1.2185222, 1.2170813, 1.217188, 1.2181069, 1.2173674, 1.2161442, 1.2185454, 1.2208221, 1.221185, 1.2226894, 1.2234542, 1.2245033, 1.2245257, 1.2255565, 1.2257154, 1.2251344, 1.2245902, 1.2237622, 1.2257888, 1.2264369, 1.2280335, 1.2297904, 1.2308733, 1.2310134, 1.2294791, 1.2291298, 1.2295911, 1.2297175, 1.2305896, 1.2316718, 1.23318, 1.2338634, 1.23535, 1.2364992, 1.2375259, 1.2385805, 1.2386142, 1.238863, 1.2398067, 1.240158, 1.2400742, 1.2394257, 1.2407639, 1.2416196, 1.2410231, 1.2408233, 1.2421823, 1.2432475, 1.2429609, 1.2441525, 1.2451065, 1.2451601, 1.2444475, 1.2453625, 1.2460799, 1.2447708, 1.2456944, 1.2460716, 1.246501, 1.2453096, 1.245153, 1.245689, 1.2451062, 1.2462068, 1.2469265, 1.2456778, 1.2442905, 1.243163, 1.2421459, 1.2408544, 1.2398272, 1.2406313, 1.241055, 1.2412561, 1.2415298, 1.2419662, 1.2419257, 1.2423886, 1.2430378, 1.2428119, 1.2427595, 1.2419828, 1.2414606, 1.24124, 1.2408133, 1.241446, 1.24187, 1.2422289, 1.240975, 1.2409217, 1.2413938, 1.2409918, 1.2404821, 1.2396863, 1.2384169, 1.2374412, 1.2375246, 1.2361244, 1.2348517, 1.2343987, 1.2344615, 1.2341228, 1.2339895, 1.232851, 1.2327116, 1.2330756, 1.2338233, 1.234007, 1.2341012, 1.2337818, 1.2330194, 1.2334409, 1.2335793, 1.233518, 1.2337172, 1.2341068, 1.2342303, 1.2343616, 1.2342145, 1.2342881, 1.2341195, 1.2343159, 1.2343327, 1.2341086, 1.2339906, 1.2330321, 1.2325256, 1.2325633, 1.2319027, 1.2323581, 1.2322615, 1.232091, 1.2316706, 1.2320215, 1.2319951, 1.2318622, 1.2314003, 1.2309606, 1.2306418, 1.2307426, 1.2306855, 1.2305666, 1.2310145, 1.2309128, 1.231194, 1.2313731, 1.2314616, 1.2320557, 1.2325064, 1.2326838, 1.2329789, 1.2332574, 1.2330358, 1.232787, 1.2330414, 1.2334645, 1.2338918, 1.2339282, 1.2336974, 1.2337614, 1.2335893, 1.2337735, 1.2343113, 1.2344712, 1.2342148, 1.234491, 1.2348144, 1.2348967, 1.2351692, 1.2351292, 1.2349375, 1.2353834, 1.2361317, 1.2366294, 1.2369907, 1.2376122, 1.2379894, 1.2378554, 1.2380661, 1.2380822, 1.2380563, 1.2379841, 1.238273, 1.2389069, 1.2392746, 1.2396233, 1.2401199, 1.2403629, 1.2406111, 1.2410895, 1.241262, 1.2411375, 1.2412765, 1.2410183, 1.2404431, 1.2407472, 1.2408131, 1.2407955, 1.2405208, 1.240122, 1.2401035, 1.2401407, 1.2402239, 1.2401044, 1.2397617, 1.2397207, 1.2396386, 1.239904, 1.2402893, 1.2401407, 1.2402953, 1.2400706, 1.2401162, 1.240225, 1.2401022, 1.2403575, 1.2407758, 1.2407185, 1.2405272, 1.2403892, 1.2404573, 1.2405587, 1.240127, 1.2399926, 1.2399546, 1.2394688, 1.2393925, 1.2391526, 1.2390013, 1.238828, 1.2385417, 1.2384398, 1.2378843, 1.2378045, 1.2374947, 1.2374196, 1.2373862, 1.2374039, 1.2372334, 1.236863, 1.2367567, 1.2366561, 1.2365308, 1.2365419, 1.2369637, 1.2369671, 1.2364001, 1.2364962, 1.2364262, 1.2367076, 1.2365731, 1.2368002, 1.236698, 1.2363392, 1.2360457, 1.2358372, 1.2356405, 1.2354858, 1.2354735, 1.2352674]\n",
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    "_net_electricity_consumption = [1.0296738, 1.0014929, 1.0040551, 1.000263, 0.9998964, 0.999293, 0.9980358, 0.9950068, 0.99410313, 0.99282146, 0.9931716, 0.99186754, 0.9915112, 0.99143636, 0.9895782, 0.98861915, 0.98941284, 0.98948467, 0.99042135, 0.99075115, 0.99141407, 0.99206764, 0.9937102, 0.9929195, 0.993684, 0.9952696, 0.99485755, 0.99493897, 0.99447536, 0.99460757, 0.9956988, 0.99554217, 0.9955489, 0.99610865, 0.99581796, 0.99539113, 0.9950906, 0.9950552, 0.9947909, 0.9945684, 0.9945584, 0.99438596, 0.9936906, 0.9942407, 0.9939164, 0.9936351, 0.9937987, 0.9940698, 0.9939077, 0.99379903, 0.9941164, 0.9946608, 0.9942539, 0.9946134, 0.9952694, 0.99577504, 0.99535906, 0.996221, 0.9962671, 0.9962803, 0.99648225, 0.99649155, 0.9962333, 0.99600255, 0.9960595, 0.99624836, 0.99602276, 0.99592066, 0.9960588, 0.9962351, 0.9961218, 0.9962973, 0.99630237, 0.99670696, 0.99699485, 0.9975708, 0.9978105, 0.9981197, 0.9980537, 0.99799484, 0.99826306, 0.99810916, 0.9986077, 0.99891424, 0.9986336, 0.99893105, 0.99897635, 0.9993134, 0.99931026, 0.99948937, 0.9992836, 0.99907726, 0.99911696, 0.9993978, 0.99967945, 0.9999036, 1.0001503, 1.0002748, 1.0004443, 1.0005546, 1.0007566, 1.0008227, 1.000895, 1.0009462, 1.0008929, 1.000661, 1.0006592, 1.0007275, 1.0007747, 1.0010558, 1.0013163, 1.0015025, 1.0016079, 1.0017527, 1.0019703, 1.002099, 1.0021731, 1.0021865, 1.0021374, 1.0020263, 1.0021286, 1.0021465, 1.0023267, 1.0022771, 1.0024884, 1.0026183, 1.0027252, 1.0026885, 1.0027207, 1.0027453, 1.0028416, 1.0028702, 1.0028291, 1.0028944, 1.0030481, 1.0030973, 1.0032747, 1.0033494, 1.0034326, 1.0034409, 1.0034071, 1.0033876, 1.0034884, 1.0035981, 1.0035758, 1.0036008, 1.0037509, 1.0037669, 1.0036151, 1.0036021, 1.0037618, 1.0038029, 1.0038644, 1.0039982, 1.0039752, 1.0040679, 1.0039902, 1.0040058, 1.0040066, 1.0040375, 1.0040476, 1.0040239, 1.0040593, 1.004063, 1.0041037, 1.0040319, 1.0040421, 1.0040739, 1.0041189, 1.004052, 1.0039945, 1.0039316, 1.0039392, 1.0039048, 1.0038501, 1.0038214, 1.0038618, 1.0038123, 1.0038286, 1.0038226, 1.0038277, 1.003925, 1.0039518, 1.0039389, 1.0038596, 1.0038173, 1.0038254, 1.0038402, 1.0038552, 1.0038884, 1.0039359, 1.0039098, 1.0039308, 1.0039601, 1.0039481, 1.0038893, 1.003837, 1.0038377, 1.0038154, 1.0037601, 1.003755, 1.003729, 1.0037093, 1.0037313, 1.0037647, 1.0037063, 1.0036539, 1.0036707, 1.0036764, 1.0037166, 1.0037186, 1.0037807, 1.0037861, 1.0037899, 1.0037506, 1.0037208, 1.0037211, 1.0037328, 1.003698, 1.0037119, 1.0037053, 1.0037557, 1.0037594, 1.0037109, 1.0036598, 1.0036855, 1.0036814, 1.003711, 1.0036576, 1.0036381, 1.0036132, 1.003611, 1.0035539, 1.0035499, 1.0035771, 1.0035156, 1.0035336, 1.0035272, 1.0035357, 1.0035374, 1.0034757, 1.0034925, 1.0034559, 1.0034864, 1.0035311, 1.0035362, 1.0035193, 1.0034878, 1.0034242, 1.003396, 1.0034289, 1.0034199, 1.0034508, 1.0034556, 1.0034301, 1.0034466, 1.0034703, 1.0034573, 1.0035018, 1.0035061, 1.0034832, 1.0034956, 1.0034425, 1.0034733, 1.003454, 1.003389, 1.0033718, 1.0033371, 1.0033319, 1.0033125, 1.0033026, 1.003278, 1.0032558, 1.003226, 1.0031846, 1.0032128, 1.0032765, 1.0032867, 1.0033382, 1.0033625, 1.0033807, 1.0033456, 1.0033523, 1.0033542, 1.0033314, 1.0033289, 1.0033395, 1.0033704, 1.0033562, 1.0033935, 1.0034015, 1.0033871, 1.0034451, 1.0034574, 1.003442, 1.0034479, 1.0034406, 1.0034013, 1.0033718, 1.0033953, 1.003382, 1.0034022, 1.003355, 1.003332, 1.0032595, 1.0032356, 1.0032343, 1.0032277, 1.003194, 1.0032111, 1.0032386, 1.003297, 1.003331, 1.0033582, 1.0033334, 1.0033143, 1.0033177, 1.0032778, 1.0032463, 1.003291, 1.0033219, 1.003317, 1.0032808, 1.0032804, 1.0032574, 1.003259, 1.0032675, 1.0031955, 1.0032153, 1.0032178, 1.00323, 1.0032073, 1.0031538, 1.0031171, 1.0030997, 1.0030549, 1.0030509, 1.0030231, 1.0029817, 1.0029402, 1.0029198, 1.0029211, 1.0028859, 1.0028309, 1.0027899, 1.0027874, 1.002725, 1.0027732, 1.0028114, 1.0028296, 1.0028229, 1.0028448, 1.0028479, 1.0028787, 1.0028211, 1.0028634, 1.0028378, 1.0027701, 1.0027015, 1.0026736, 1.00261, 1.0025762, 1.0026013, 1.0025666]\n",
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# PPO\n",
    "__ramping = [1.6539496, 1.6215539, 1.4729891, 1.487669, 1.5073891, 1.4754175, 1.4558959, 1.4460686, 1.4322392, 1.4488796, 1.4334496, 1.4267592, 1.4272798, 1.4510454, 1.4394888, 1.4169626, 1.4146806, 1.4335523, 1.4445678, 1.444983, 1.4483225, 1.4462965, 1.444343, 1.4402866, 1.4376218, 1.4440765, 1.4429239, 1.4462178, 1.4484092, 1.4453657, 1.4454309, 1.447191, 1.4547143, 1.4551029, 1.4457337, 1.439164, 1.4324862, 1.4353424, 1.4309344, 1.4398786, 1.4426435, 1.4386404, 1.4313607, 1.4246788, 1.4279308, 1.4303501, 1.4376278, 1.4418042, 1.4393555, 1.4393182, 1.4378829, 1.4447287, 1.4478514, 1.4498048, 1.4506545, 1.4547307, 1.4530656, 1.4470754, 1.4529864, 1.456723, 1.4602273, 1.4635937, 1.4635918, 1.4698906, 1.4717579, 1.4736512, 1.4791985, 1.4776335, 1.478018, 1.4798073, 1.4841928, 1.488813, 1.4906547, 1.4934734, 1.4972714, 1.4989218, 1.5002025, 1.5021168, 1.500705, 1.4970788, 1.4986635, 1.5000594, 1.5015442, 1.5022651, 1.5031525, 1.506267, 1.5048852, 1.5108584, 1.5081216, 1.508028, 1.5077074, 1.5109158, 1.5141869, 1.5168774, 1.5209976, 1.5231609, 1.5228252, 1.5238261, 1.5262783, 1.5293317, 1.5331658, 1.5369799, 1.5362757, 1.5375866, 1.5374826, 1.5377465, 1.542193, 1.5448139, 1.5472298, 1.5473596, 1.548387, 1.5490415, 1.5496182, 1.5562166, 1.5574996, 1.5599241, 1.5590489, 1.557466, 1.554586, 1.5533915, 1.5551182, 1.5575728, 1.559792, 1.5582293, 1.5613934, 1.5636891, 1.5625707, 1.5661235, 1.5666666, 1.5695412, 1.5697204, 1.5698177, 1.5695915, 1.5697112, 1.5738941, 1.5761113, 1.5777277, 1.5781368, 1.5808719, 1.5808318, 1.5814288, 1.5837139, 1.586329, 1.5885817, 1.5883045, 1.5874164, 1.5874662, 1.5874469, 1.5892012, 1.590654, 1.5933083, 1.5951422, 1.5946506, 1.5954907, 1.596947, 1.5973701, 1.5977051, 1.6006557, 1.6016524, 1.5998758, 1.5989647, 1.5986109, 1.5998266, 1.6013861, 1.6042757, 1.6050096, 1.6051496, 1.6051912, 1.6062139, 1.6067942, 1.6061342, 1.6071672, 1.6074116, 1.605546, 1.6019975, 1.6022662, 1.6049049, 1.6052024, 1.6069076, 1.609236, 1.6105053, 1.6110585, 1.6115472, 1.6140075, 1.615611, 1.6167612, 1.6169313, 1.6180401, 1.6166832, 1.6191822, 1.6236156, 1.6251187, 1.6260643, 1.6250232, 1.6256856, 1.6255224, 1.6258721, 1.6281074, 1.6266752, 1.6260884, 1.6268034, 1.6256771, 1.6241711, 1.6256644, 1.628071, 1.6283429, 1.6289414, 1.6264064, 1.6269826, 1.6273, 1.628792, 1.632277, 1.6335512, 1.6348372, 1.6346124, 1.635254, 1.6350684, 1.6358855, 1.638061, 1.6394432, 1.639575, 1.6380697, 1.6388037, 1.639062, 1.6403672, 1.6421709, 1.6430788, 1.6435183, 1.6430247, 1.6426325, 1.6424272, 1.64412, 1.6461669, 1.6484759, 1.649254, 1.6481483, 1.6487238, 1.6498814, 1.6513377, 1.6510408, 1.6516958, 1.6519902, 1.6522534, 1.6508915, 1.6503986, 1.6531754, 1.6553221, 1.6553609, 1.6572192, 1.6572528, 1.6576676, 1.6580217, 1.6589473, 1.6583381, 1.6587331, 1.6599538, 1.658808, 1.65738, 1.6574833, 1.6584926, 1.6593809, 1.6587718, 1.659275, 1.6602877, 1.6604125, 1.6602677, 1.6610106, 1.6602763, 1.6592206, 1.6605976, 1.6603746, 1.6605715, 1.6608734, 1.6607982, 1.6611161, 1.6622052, 1.6628063, 1.6622186, 1.6618228, 1.6617893, 1.6621028, 1.6633712, 1.6640205, 1.6647041, 1.6650512, 1.6641594, 1.6633551, 1.6634928, 1.6639826, 1.663752, 1.6646144, 1.664431, 1.6649473, 1.6658441, 1.6662873, 1.666731, 1.6665826, 1.6673738, 1.6664124, 1.6670619, 1.667491, 1.6670955, 1.6680939, 1.6688617, 1.668013, 1.6677794, 1.6674068, 1.6674898, 1.66626, 1.665986, 1.6665887, 1.6668544, 1.6660752, 1.6652687, 1.6647213, 1.6639149, 1.6640452, 1.6637502, 1.662742, 1.661905, 1.6605103, 1.6602633, 1.6590041, 1.6574283, 1.6574019, 1.656551, 1.6553087, 1.6538641, 1.652671, 1.6516491, 1.6508515, 1.6501873, 1.6493826, 1.6485505, 1.6467508, 1.645417, 1.6448433, 1.6435238, 1.643155, 1.6433477, 1.6434062, 1.6419197, 1.6416688, 1.6414613, 1.6405139, 1.6404684, 1.6399121, 1.63916, 1.6390524, 1.6385152, 1.6387148, 1.6375517, 1.6360714, 1.6362731, 1.63658, 1.6364489, 1.6356832, 1.6355511, 1.635118, 1.6345029, 1.633901, 1.6338671, 1.6333319, 1.6323395, 1.4992709, 1.3547331, 1.3786024, 1.3949308, 1.4233401, 1.4444593, 1.4273053, 1.4111134, 1.4013666, 1.4166424, 1.4177809, 1.4139721, 1.423122, 1.4337331, 1.430159, 1.4084423, 1.4134717, 1.4145664, 1.4236255, 1.4231094, 1.4293338, 1.4298898, 1.4313234, 1.4384668, 1.4308989, 1.4333053, 1.4394814, 1.4369445, 1.4350404, 1.42702, 1.4297988, 1.4321418, 1.4376745, 1.4379928, 1.4267738, 1.4193809, 1.4111363, 1.4174409, 1.4122741, 1.4205979, 1.4200909, 1.423089, 1.424669, 1.4172212, 1.4204853, 1.4234751, 1.4295865, 1.42923, 1.4316899, 1.4313576, 1.4259596, 1.4296046, 1.4315298, 1.4376643, 1.4372294, 1.4400322, 1.436067, 1.4332339, 1.4374223, 1.4403315, 1.4440883]\n",
    "__load_factor = [0.8785975605076968, 0.982376926451328, 1.0068391535794583, 1.078297115135653, 1.070702494318247, 1.0694130974022495, 1.0815726434384973, 1.0800074048303578, 1.0819457440563873, 1.1215160647441649, 1.1215840341556915, 1.1211402630429204, 1.1211621575729012, 1.1591206617734957, 1.1511787311688437, 1.1450637341515015, 1.1435158982508968, 1.1641494754261474, 1.1675303537348019, 1.1690594839443502, 1.1740641177308304, 1.1710722581145654, 1.1765267782844304, 1.1757505239613244, 1.173624712618495, 1.175931503622196, 1.1888135935813269, 1.189382035551093, 1.188557842511061, 1.192281454029495, 1.14709027430536, 1.2575843537485871, 1.2424413017094298, 1.2244528265752952, 1.2131621979547682, 1.1989341055428662, 1.2015822288240003, 1.2026070346052165, 1.2021135635743743, 1.2032797649126052, 1.202964907602489, 1.2018099639058064, 1.1957401297852495, 1.1943864416109498, 1.1935341944598064, 1.1956433479026103, 1.1936956978903894, 1.1945915918686891, 1.1921711947604117, 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   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TRPO\n",
    "___ramping = [1.5922731, 1.533359, 1.4705952, 1.4812102, 1.4769565, 1.492065, 1.4723318, 1.4433342, 1.4183062, 1.4173042, 1.405954, 1.4110308, 1.4067049, 1.4194286, 1.4147837, 1.3906193, 1.38789, 1.4000683, 1.398555, 1.400795, 1.4096189, 1.4167702, 1.4174708, 1.4174607, 1.4230547, 1.426447, 1.428035, 1.4267739, 1.4245557, 1.4203303, 1.427863, 1.4260858, 1.4323639, 1.4307113, 1.421339, 1.4140115, 1.4078863, 1.4100626, 1.4053907, 1.4128714, 1.4158049, 1.4181789, 1.4100623, 1.4032289, 1.4036491, 1.4045777, 1.4087361, 1.4066358, 1.4060804, 1.408358, 1.4079418, 1.415773, 1.418355, 1.4216611, 1.4233096, 1.4267726, 1.4246633, 1.421575, 1.4278469, 1.4308274, 1.4333396, 1.4349155, 1.4335732, 1.4373709, 1.4414428, 1.4402654, 1.4449836, 1.4472808, 1.4482994, 1.4514229, 1.4558388, 1.4588525, 1.45924, 1.466532, 1.4673815, 1.4685817, 1.4710945, 1.4745041, 1.4735144, 1.4713596, 1.4769602, 1.4775118, 1.4781225, 1.4809906, 1.4817915, 1.4839028, 1.4846292, 1.4890186, 1.4860417, 1.4853171, 1.4848136, 1.4856762, 1.4886163, 1.4924598, 1.4968679, 1.4974205, 1.496308, 1.4968991, 1.5019268, 1.5074078, 1.5119355, 1.5151693, 1.5151724, 1.5149279, 1.5155202, 1.5164407, 1.5213641, 1.5238688, 1.5274558, 1.5264499, 1.5269673, 1.5264215, 1.5285919, 1.533136, 1.5342585, 1.5344074, 1.5331439, 1.5321112, 1.5304265, 1.528417, 1.5300963, 1.5308307, 1.5328969, 1.5303737, 1.5329971, 1.5339484, 1.5334725, 1.5371308, 1.538634, 1.5404191, 1.5417603, 1.5427783, 1.5415416, 1.5413154, 1.5450119, 1.5474948, 1.5502555, 1.5515474, 1.5537138, 1.5541772, 1.5558017, 1.5567782, 1.5592923, 1.5630801, 1.5628066, 1.5625796, 1.5624582, 1.5615427, 1.5630119, 1.5647327, 1.5689545, 1.56943, 1.5691191, 1.5703251, 1.5728393, 1.5755918, 1.5764825, 1.5790796, 1.5809366, 1.579688, 1.5798861, 1.5800303, 1.5816622, 1.5834008, 1.5847812, 1.5871406, 1.5877081, 1.5878884, 1.587915, 1.5888001, 1.5886543, 1.5891035, 1.5903667, 1.5880243, 1.5849502, 1.5862213, 1.5893177, 1.5901666, 1.5918187, 1.594341, 1.5953144, 1.5945247, 1.5947568, 1.5971465, 1.5995429, 1.6008368, 1.6006472, 1.6017585, 1.601014, 1.6032377, 1.6067247, 1.6079562, 1.6096375, 1.6091138, 1.6109973, 1.6107646, 1.6113074, 1.6122695, 1.6109574, 1.6106229, 1.6117041, 1.6100143, 1.6087617, 1.6096377, 1.61132, 1.6115544, 1.6119463, 1.6097246, 1.6109669, 1.6122366, 1.6140568, 1.6172202, 1.6189867, 1.6195326, 1.6193862, 1.6200031, 1.6201408, 1.6216152, 1.6235168, 1.6251998, 1.625578, 1.625813, 1.6248384, 1.624224, 1.6255835, 1.6274595, 1.628482, 1.6292874, 1.6292225, 1.6290468, 1.6278074, 1.629564, 1.6309993, 1.6325994, 1.6331667, 1.6332433, 1.6333511, 1.6350307, 1.636251, 1.6362782, 1.6373167, 1.6376827, 1.6385381, 1.6378288, 1.6378177, 1.6400092, 1.6423486, 1.6426032, 1.6445459, 1.6445359, 1.6443241, 1.6452018, 1.6462663, 1.646412, 1.6471044, 1.6473273, 1.6458786, 1.6453481, 1.644621, 1.6463047, 1.6471349, 1.647438, 1.6486659, 1.6493485, 1.6502616, 1.6510407, 1.6519156, 1.6518303, 1.6503011, 1.651468, 1.6510165, 1.6509222, 1.6515064, 1.6516855, 1.6520199, 1.6525053, 1.6535685, 1.6534573, 1.6532665, 1.6529278, 1.6532679, 1.653862, 1.6540849, 1.6553808, 1.6551116, 1.6549016, 1.654618, 1.654419, 1.6553265, 1.6561561, 1.6565077, 1.6568024, 1.6566066, 1.6565675, 1.6574343, 1.6578863, 1.6580883, 1.658946, 1.6580045, 1.6585808, 1.6591715, 1.6590298, 1.6606593, 1.6610305, 1.6597878, 1.6589224, 1.659132, 1.6599611, 1.6594489, 1.6592151, 1.6600181, 1.6605389, 1.659479, 1.6594586, 1.6590519, 1.6573751, 1.6567401, 1.6566544, 1.65589, 1.6554085, 1.654424, 1.6546837, 1.6540453, 1.6524662, 1.6523962, 1.6517586, 1.6506011, 1.6492903, 1.6480026, 1.6466153, 1.6455828, 1.6443228, 1.6438862, 1.6435902, 1.642268, 1.6411092, 1.6405718, 1.639586, 1.638638, 1.6388724, 1.6392905, 1.6375334, 1.6373491, 1.636955, 1.6355641, 1.635077, 1.6348279, 1.6346226, 1.6342814, 1.6338944, 1.6344712, 1.6332116, 1.6321788, 1.6329658, 1.6334008, 1.6331973, 1.6325864, 1.6327065, 1.6320716, 1.6312901, 1.6310663, 1.6306901, 1.6301286, 1.6295385, 1.5588202, 1.3926573, 1.3475053, 1.383853, 1.4139996, 1.3934369, 1.3768406, 1.3745018, 1.375573, 1.4043885, 1.4030973, 1.4076655, 1.4208158, 1.4355412, 1.4361254, 1.414011, 1.4137428, 1.4189967, 1.4217345]\n",
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "{'ramping': __ramping[-1],\n",
    " '1-load_factor': __load_factor[-1],\n",
    " 'average_daily_peak': __average_daily_peak[-1],\n",
    " 'peak_demand': __peak_demand[-1],\n",
    " 'net_electricity_consumption': __net_electricity_consumption[-1],\n",
    " 'carbon_emissions': __carbon_emissions[-1],\n",
    " 'total': __total[-1],\n",
    " 'coordination_score': __coordination_score[-1]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(2, 4, figsize=(15,5), sharex=True, sharey=False)\n",
    "\n",
    "m = len(iAC_table[\"total\"])\n",
    "\n",
    "\n",
    "# ramping\n",
    "ax[0, 0].set_title(\"Ramping\")\n",
    "ax[0, 0].plot(iAC_table[\"ramping\"], 'r', label=\"iAC (ours)\")\n",
    "ax[0, 0].plot(marlisa_table[\"ramping\"][-m:], color='brown', label=\"MARLISA\")\n",
    "ax[0, 0].plot(_ramping[:m], 'b', label=\"A2C\")\n",
    "ax[0, 0].plot(__ramping[:m], color='orange', label=\"PPO\")\n",
    "ax[0, 0].plot(___ramping[:m], color='pink', label=\"TRPO\")\n",
    "ax[0, 0].plot(ramping[:m], 'g', label=\"TD3\")\n",
    "ax[0, 0].plot(np.ones(m), 'k--', label=\"RBC\")\n",
    "\n",
    "# load factor\n",
    "ax[0, 1].set_title(\"1-Load Factor\")\n",
    "ax[0, 1].plot(iAC_table[\"1-load_factor\"], 'r', label=\"iAC\")\n",
    "ax[0, 1].plot(marlisa_table[\"1-load_factor\"][365 - m:], color='brown', label=\"MARLISA\")\n",
    "ax[0, 1].plot(_load_factor[:m], 'b', label=\"A2C\")\n",
    "ax[0, 1].plot(__load_factor[:m], color='orange', label=\"PPO\")\n",
    "ax[0, 1].plot(___load_factor[:m], color='pink', label=\"TRPO\")\n",
    "ax[0, 1].plot(load_factor[:m], 'g', label=\"TD3\")\n",
    "ax[0, 1].plot(np.ones(m), 'k--', label=\"RBC\")\n",
    "\n",
    "# average daily peak\n",
    "ax[0, 2].set_title(\"Average Daily Peak\")\n",
    "ax[0, 2].plot(iAC_table[\"average_daily_peak\"], 'r', label=\"iAC\")\n",
    "ax[0, 2].plot(marlisa_table[\"average_daily_peak\"][365 - m:], color='brown', label=\"MARLISA\")\n",
    "ax[0, 2].plot(_average_daily_peak[:m], 'b', label=\"A2C\")\n",
    "ax[0, 2].plot(__average_daily_peak[:m], color='orange', label=\"PPO\")\n",
    "ax[0, 2].plot(___average_daily_peak[:m], color='pink', label=\"TRPO\")\n",
    "ax[0, 2].plot(average_daily_peak[:m], 'g', label=\"TD3\")\n",
    "ax[0, 2].plot(np.ones(m), 'k--', label=\"RBC\")\n",
    "\n",
    "# Peak Demand\n",
    "ax[0, 3].set_title(\"Peak Demand\")\n",
    "ax[0, 3].plot(iAC_table[\"peak_demand\"], 'r', label=\"iAC\")\n",
    "ax[0, 3].plot(marlisa_table[\"peak_demand\"][365 - m:], color='brown', label=\"MARLISA\")\n",
    "ax[0, 3].plot(_peak_demand[:m], 'b', label=\"A2C\")\n",
    "ax[0, 3].plot(__peak_demand[:m], color='orange', label=\"PPO\")\n",
    "ax[0, 3].plot(___peak_demand[:m], color=\"pink\", label=\"TRPO\")\n",
    "ax[0, 3].plot(peak_demand[:m], 'g', label=\"TD3\")\n",
    "ax[0, 3].plot(np.ones(m), 'k--', label=\"RBC\")\n",
    "\n",
    "# Net Electricity Consumption\n",
    "ax[1, 0].set_title(\"Net Electricity Consumption\")\n",
    "ax[1, 0].plot(iAC_table[\"net_electricity_consumption\"], 'r', label=\"iAC\")\n",
    "ax[1, 0].plot(marlisa_table[\"net_electricity_consumption\"][365 - m:], color='brown', label=\"MARLISA\")\n",
    "ax[1, 0].plot(_net_electricity_consumption[:m], 'b', label=\"A2C\")\n",
    "ax[1, 0].plot(__net_electricity_consumption[:m], color='orange', label=\"PPO\")\n",
    "ax[1, 0].plot(___net_electricity_consumption[:m], color=\"pink\", label=\"TRPO\")\n",
    "ax[1, 0].plot(net_electricity_consumption[:m], 'g', label=\"TD3\")\n",
    "ax[1, 0].plot(np.ones(m), 'k--', label=\"RBC\")\n",
    "\n",
    "# Carbon Emmissions\n",
    "ax[1, 1].set_title(\"Carbon Emissions\")\n",
    "ax[1, 1].plot(iAC_table[\"carbon_emissions\"], 'r', label=\"iAC\")\n",
    "ax[1, 1].plot(marlisa_table[\"carbon_emissions\"][365 - m:], color='brown', label=\"MARLISA\")\n",
    "ax[1, 1].plot(_carbon_emissions[:m], 'b', label=\"A2C\")\n",
    "ax[1, 1].plot(__carbon_emissions[:m], color='orange', label=\"PPO\")\n",
    "ax[1, 1].plot(___carbon_emissions[:m], color=\"pink\", label=\"TRPO\")\n",
    "ax[1, 1].plot(carbon_emissions[:m], 'g', label=\"TD3\")\n",
    "ax[1, 1].plot(np.ones(m), 'k--', label=\"RBC\")\n",
    "\n",
    "# Total\n",
    "ax[1, 2].set_title(\"Total Cost\")\n",
    "ax[1, 2].plot(iAC_table[\"total\"], 'r', label=\"iAC\")\n",
    "ax[1, 2].plot(marlisa_table[\"total\"][365 - m:], color='brown', label=\"MARLISA\")\n",
    "ax[1, 2].plot(_total[:m], 'b', label=\"A2C\")\n",
    "ax[1, 2].plot(__total[:m], color='orange', label=\"PPO\")\n",
    "ax[1, 2].plot(___total[:m], color=\"pink\", label=\"TRPO\")\n",
    "ax[1, 2].plot(total[:m], 'g', label=\"TD3\")\n",
    "ax[1, 2].plot(np.ones(m), 'k--', label=\"RBC\")\n",
    "\n",
    "# Coordination Score\n",
    "ax[1, 3].set_title(\"Coordination Score\")\n",
    "ax[1, 3].plot(iAC_table[\"coordination_score\"], 'r', label=\"iAC\")\n",
    "ax[1, 3].plot(marlisa_table[\"coordination_score\"][365 - m:], color='brown', label=\"MARLISA\")\n",
    "ax[1, 3].plot(_coordination_score[:m], 'b', label=\"A2C\")\n",
    "ax[1, 3].plot(__coordination_score[:m], color='orange', label=\"PPO\")\n",
    "ax[1, 3].plot(___coordination_score[:m], color=\"pink\", label=\"TRPO\")\n",
    "ax[1, 3].plot(coordination_score[:m], 'g', label=\"TD3\")\n",
    "ax[1, 3].plot(np.ones(m), 'k--', label=\"RBC\")\n",
    "\n",
    "# legend and axis\n",
    "handles, labels = ax[0, 0].get_legend_handles_labels()\n",
    "fig.legend(handles, labels, loc='center right', ncol=1)\n",
    "fig.text(0.5, 0.03, 'Day', ha='center', va='center')\n",
    "fig.text(0.08, 0.5, 'Cost', ha='center', va='center', rotation='vertical')\n",
    "\n",
    "plt.subplots_adjust(wspace=0.3, hspace=0.27)\n",
    "\n",
    "plt.show()"
   ]
  }
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