452 lines
184 KiB
Plaintext
452 lines
184 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"import glob\n",
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"import shutil\n",
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"\n",
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"def clear_folder_make_ess_pv(folder_path):\n",
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" if os.path.isdir(folder_path):\n",
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" shutil.rmtree(folder_path)\n",
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" os.makedirs(folder_path)\n",
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" os.makedirs(os.path.join(folder_path,'ess'))\n",
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" os.makedirs(os.path.join(folder_path,'pv'))\n",
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"\n",
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"folder_path = 'plots'\n",
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"clear_folder_make_ess_pv(folder_path)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\n",
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"import seaborn as sns\n",
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"import numpy as np\n",
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"import pandas as pd\n",
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"from EnergySystem import EnergySystem\n",
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"from config import pv_config, grid_config, ess_config\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"metadata": {},
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"outputs": [],
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"source": [
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"import json\n",
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"\n",
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"print(\"Version 0.0.2\")\n",
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"\n",
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"with open('config.json', 'r') as f:\n",
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" js_data = json.load(f)\n",
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"\n",
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"data = pd.read_csv('combined_data.csv')\n",
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"time_interval = js_data[\"time_interval\"][\"numerator\"] / js_data[\"time_interval\"][\"denominator\"]\n",
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"\n",
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"pv_loss = js_data[\"pv\"][\"loss\"]\n",
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"pv_cost_per_kW = js_data[\"pv\"][\"cost_per_kW\"]\n",
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"pv_lifetime = js_data[\"pv\"][\"lifetime\"]\n",
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"\n",
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"ess_loss = js_data[\"ess\"][\"loss\"]\n",
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"ess_cost_per_kW = js_data[\"ess\"][\"cost_per_kW\"]\n",
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"ess_lifetime = js_data[\"ess\"][\"lifetime\"]\n",
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"\n",
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"grid_loss = js_data[\"grid\"][\"loss\"]\n",
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"sell_price = js_data[\"grid\"][\"sell_price\"] #kWh\n",
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"grid_capacity = js_data[\"grid\"][\"capacity\"] #kWh\n",
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"\n",
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"pv_begin = js_data[\"pv_capacities\"][\"begin\"]\n",
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"pv_end = js_data[\"pv_capacities\"][\"end\"]\n",
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"pv_groups = js_data[\"pv_capacities\"][\"groups\"]\n",
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"\n",
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"ess_begin = js_data[\"ess_capacities\"][\"begin\"]\n",
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"ess_end = js_data[\"ess_capacities\"][\"end\"]\n",
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"ess_groups = js_data[\"ess_capacities\"][\"groups\"]\n",
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"\n",
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"annot_unmet = js_data[\"annotated\"][\"unmet_prob\"]\n",
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"annot_benefit = js_data[\"annotated\"][\"benefit\"]\n",
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"annot_cost = js_data[\"annotated\"][\"cost\"]\n",
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"\n",
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"title_unmet = js_data[\"plot_title\"][\"unmet_prob\"]\n",
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"title_cost = js_data[\"plot_title\"][\"cost\"]\n",
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"title_benefit = js_data[\"plot_title\"][\"benefit\"]\n",
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"\n",
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"figure_size = (js_data[\"figure_size\"][\"length\"], js_data[\"figure_size\"][\"height\"])\n",
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"\n",
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"pv_capacities = np.linspace(pv_begin, pv_end, pv_groups)\n",
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"ess_capacities = np.linspace(ess_begin, ess_end, ess_groups)\n",
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"results = pd.DataFrame(index=pv_capacities, columns= ess_capacities)\n",
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"affords = pd.DataFrame(index=pv_capacities, columns= ess_capacities)\n",
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"costs = pd.DataFrame(index=pv_capacities, columns= ess_capacities)\n",
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"overload_cnt = pd.DataFrame(index=pv_capacities, columns= ess_capacities)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"metadata": {},
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"outputs": [],
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"source": [
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"hour_demand = []\n",
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"for index, row in data.iterrows():\n",
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" time = row['time']\n",
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" demand = row['demand']\n",
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" if time.endswith('00'):\n",
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" hour_demand.append(demand)\n",
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"plt.figure(figsize=(10,8))\n",
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"plt.plot(hour_demand)\n",
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"plt.ylabel('Demand Power / kW')\n",
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"plt.savefig('plots/demand.png')\n",
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"plt.close()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {},
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"outputs": [],
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"source": [
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"def cal_profit(es: EnergySystem, saved_money):\n",
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" profit = saved_money - es.ess.get_cost_per_year() - es.pv.get_cost_per_year()\n",
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" return profit"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"ess_capacity:5000.0\n",
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"pv_capacity:5000.0\n",
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"pv_capacity:5000.0\n",
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"pv_capacity:5000.0\n",
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"ess_capacity:27500.0\n",
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"pv_capacity:27500.0\n",
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"pv_capacity:27500.0\n",
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"pv_capacity:27500.0\n",
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"ess_capacity:50000.0\n",
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"pv_capacity:50000.0\n",
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"pv_capacity:50000.0\n",
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"pv_capacity:50000.0\n"
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]
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}
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],
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"source": [
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"for ess_capacity in ess_capacities:\n",
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" print(f\"ess_capacity:{ess_capacity}\")\n",
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" for pv_capacity in pv_capacities:\n",
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" print(f\"pv_capacity:{ess_capacity}\")\n",
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" pv = pv_config(capacity=pv_capacity, \n",
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" cost_per_kW=pv_cost_per_kW,\n",
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" lifetime=pv_lifetime, \n",
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" loss=pv_loss)\n",
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" ess = ess_config(capacity=ess_capacity, \n",
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" cost_per_kW=ess_cost_per_kW, \n",
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" lifetime=ess_lifetime, \n",
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" loss=ess_loss,\n",
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" charge_power=ess_capacity,\n",
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" discharge_power=ess_capacity)\n",
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" grid = grid_config(capacity=grid_capacity, \n",
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" grid_loss=grid_loss,\n",
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" sell_price= sell_price)\n",
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" energySystem = EnergySystem(pv_type=pv, \n",
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" ess_type=ess, \n",
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" grid_type= grid)\n",
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" benefit = energySystem.simulate(data, time_interval)\n",
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" results.loc[pv_capacity,ess_capacity] = cal_profit(energySystem, benefit)\n",
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" affords.loc[pv_capacity,ess_capacity] = energySystem.afford\n",
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" overload_cnt.loc[pv_capacity,ess_capacity] = energySystem.overload_cnt\n",
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" costs.loc[pv_capacity,ess_capacity] = energySystem.ess.capacity * energySystem.ess.cost_per_kW + energySystem.pv.capacity * energySystem.pv.cost_per_kW\n",
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" pv_generated = energySystem.day_generated\n",
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" ess_generated = energySystem.hour_stored\n",
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" ess_generated_2 = energySystem.hour_stored_2\n",
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" plt.figure(figsize=(10,8));\n",
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" plt.plot(ess_generated)\n",
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" plt.xlabel('day #')\n",
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" plt.ylabel('SoC %')\n",
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" plt.title(f'14:00 ESS SoC \\n PV cap:{pv_capacity}, ESS cap:{ess_capacity}')\n",
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" plt.savefig(f'plots/ess/1400-{pv_capacity}-{ess_capacity}.png')\n",
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" plt.close()\n",
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" plt.figure(figsize=(10,8));\n",
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" plt.plot(ess_generated_2)\n",
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" plt.xlabel('day #')\n",
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" plt.ylabel('SoC%')\n",
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" plt.title(f'08:00 ESS SoC \\n PV cap:{pv_capacity}, ESS cap:{ess_capacity}')\n",
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" plt.savefig(f'plots/ess/0800-{pv_capacity}-{ess_capacity}.png')\n",
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" plt.close()\n",
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" # print(energySystem.unmet)\n",
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" # spring_week_start = energySystem.season_start\n",
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" # spring_week_end = spring_week_start + energySystem.week_length\n",
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" # summer_week_start = energySystem.season_start + 1 * energySystem.season_step\n",
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" # summer_week_end = summer_week_start + energySystem.week_length\n",
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" # autumn_week_start = energySystem.season_start + 2 * energySystem.season_step\n",
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" # autumn_week_end = autumn_week_start + energySystem.week_length\n",
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" # winter_week_start = energySystem.season_start + 3 * energySystem.season_step\n",
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" # winter_week_end = winter_week_start+ energySystem.week_length\n",
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"\n",
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" # spring_consume_data = []\n",
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" # summer_consume_data = []\n",
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" # autumn_consume_data = []\n",
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" # winter_consume_data = []\n",
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" # for index, row in data.iterrows():\n",
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" # if index in range(spring_week_start, spring_week_end):\n",
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" # spring_consume_data.append(row['demand'])\n",
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" # elif index in range(summer_week_start, summer_week_end):\n",
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" # summer_consume_data.append(row['demand'])\n",
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" # elif index in range(autumn_week_start, autumn_week_end):\n",
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" # autumn_consume_data.append(row['demand'])\n",
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" # elif index in range(winter_week_start, winter_week_end):\n",
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" # winter_consume_data.append(row['demand'])\n",
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"\n",
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" # spring_week_time = list(range(spring_week_start, spring_week_end))\n",
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" # summer_week_time = list(range(summer_week_start, summer_week_end))\n",
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" # autumn_week_time = list(range(autumn_week_start, autumn_week_end))\n",
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" # winter_week_time = list(range(winter_week_start, winter_week_end))\n",
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"\n",
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" # spring_pv_generated = energySystem.spring_week_gen\n",
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" # summer_pv_generated = energySystem.summer_week_gen\n",
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" # autumn_pv_generated = energySystem.autumn_week_gen\n",
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" # winter_pv_generated = energySystem.winter_week_gen\n",
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"\n",
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" # spring_soc = energySystem.spring_week_soc\n",
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" # summer_soc = energySystem.summer_week_soc\n",
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" # autumn_soc = energySystem.autumn_week_soc\n",
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" # winter_soc = energySystem.winter_week_soc\n",
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"\n",
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"\n",
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" # fig, ax1 = plt.subplots()\n",
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"\n",
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" # plt.plot(spring_week_time, spring_pv_generated, label = 'pv generation')\n",
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" # plt.plot(spring_week_time, spring_consume_data, label = 'factory consume')\n",
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" # plt.ylabel('Power / kW')\n",
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" # plt.xlabel('15 min #')\n",
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" # plt.title(f'ess: {energySystem.ess.capacity/1000 } MWh pv: {energySystem.pv.capacity/1000 } MW spring week generate condition')\n",
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" # plt.legend()\n",
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" # plt.savefig(f'plots/{energySystem.ess.capacity}-{energySystem.pv.capacity}-spring.png')\n",
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" # plt.close()\n",
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"\n",
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" # plt.plot(summer_week_time, summer_pv_generated, label = 'pv generation')\n",
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" # plt.plot(summer_week_time, summer_consume_data, label = 'factory consume')\n",
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" # plt.ylabel('Power / kW')\n",
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" # plt.xlabel('15 min #')\n",
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" # plt.title(f'ess: {energySystem.ess.capacity/1000 } MWh pv: {energySystem.pv.capacity/1000 } MW summer week generate condition')\n",
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" # plt.legend()\n",
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" # plt.savefig(f'plots/{energySystem.ess.capacity}-{energySystem.pv.capacity}-summer.png')\n",
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" # plt.close()\n",
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"\n",
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" # plt.plot(autumn_week_time, autumn_pv_generated, label = 'pv generation')\n",
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" # plt.plot(autumn_week_time, autumn_consume_data, label = 'factory consume')\n",
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" # plt.ylabel('Power / kW')\n",
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" # plt.xlabel('15 min #')\n",
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" # plt.title(f'ess: {energySystem.ess.capacity/1000 } MWh pv: {energySystem.pv.capacity/1000 } MW autumn week generate condition')\n",
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" # plt.legend()\n",
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" # plt.savefig(f'plots/{energySystem.ess.capacity}-{energySystem.pv.capacity}-autumn.png')\n",
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" # plt.close()\n",
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"\n",
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" # plt.plot(winter_week_time, winter_pv_generated, label = 'pv generation')\n",
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" # plt.plot(winter_week_time, winter_consume_data, label = 'factory consume')\n",
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" # plt.ylabel('Power / kW')\n",
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" # plt.xlabel('15 min #')\n",
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" # plt.title(f'ess: {energySystem.ess.capacity/1000 } MWh pv: {energySystem.pv.capacity/1000 } MW winter week generate condition')\n",
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" # plt.legend()\n",
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" # plt.savefig(f'plots/{energySystem.ess.capacity}-{energySystem.pv.capacity}-winter.png')\n",
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" # plt.close()\n",
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"\n",
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" # plt.figure();\n",
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" # plt.plot(pv_generated)\n",
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" # plt.xlabel('day #')\n",
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" # plt.ylabel('Electricity kWh')\n",
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" # plt.title(f'PV generated pv cap:{pv_capacity}, ess cap:{ess_capacity}')\n",
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" # plt.savefig(f'plots/pv/{pv_capacity}-{ess_capacity}.png')\n",
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" # plt.close()\n",
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"\n",
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"\n",
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" # plt.show()\n",
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"\n",
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"\n",
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" \n",
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"\n",
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"# results = results.astype(float)\n",
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"\n",
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"\n",
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"# pv = pv_config(capacity=100000,cost_per_kW=200,lifetime=25,loss=0.95)\n",
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"# ess = ess_config(capacity=100000,cost_per_kW=300,lifetime=25,loss=0.95,charge_power=100000,discharge_power=100000)\n",
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"# grid = grid_config(price_schedule=price_schedule, capacity=5000, grid_loss=0.95, sell_price=0.4)\n",
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"# grid = grid_config(capacity=50000, grid_loss=0.95, sell_price=0.4)\n",
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"\n",
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"\n",
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" # print(benefit)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"metadata": {},
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"outputs": [],
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"source": [
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"def save_data(data, filename):\n",
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" data.to_csv(filename+'.csv')\n",
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" data.to_json(filename + '.json')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 2000x1800 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"import matplotlib.ticker as ticker\n",
|
|
"\n",
|
|
"if not os.path.isdir('data'):\n",
|
|
" os.makedirs('data')\n",
|
|
"\n",
|
|
"save_data(results, f'data/{pv_begin}-{pv_end}-{pv_groups}-{ess_begin}-{ess_end}-{ess_groups}-results')\n",
|
|
"save_data(costs, f'data/{pv_begin}-{pv_end}-{pv_groups}-{ess_begin}-{ess_end}-{ess_groups}-costs')\n",
|
|
"save_data(overload_cnt, f'data/{pv_begin}-{pv_end}-{pv_groups}-{ess_begin}-{ess_end}-{ess_groups}-overload_cnt')\n",
|
|
"df=results\n",
|
|
"df = df.astype(float)\n",
|
|
"df.index = df.index / 1000\n",
|
|
"df.columns = df.columns / 1000\n",
|
|
"min_value = df.min().min()\n",
|
|
"max_value = df.max().max()\n",
|
|
"max_scale = max(abs(min_value/1000), abs(max_value/1000))\n",
|
|
"plt.figure(figsize=figure_size)\n",
|
|
"cmap = sns.color_palette(\"coolwarm\", as_cmap=True)\n",
|
|
"ax = sns.heatmap(df/1000, fmt=\".1f\", cmap=cmap, vmin=-max_scale, vmax=max_scale, annot=annot_benefit)\n",
|
|
"# ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%.1f'))\n",
|
|
"plt.title(title_benefit)\n",
|
|
"plt.gca().invert_yaxis()\n",
|
|
"plt.xlabel('ESS Capacity (MWh)')\n",
|
|
"plt.ylabel('PV Capacity (MW)')\n",
|
|
"plt.savefig('plots/benefit.png')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 22,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 2000x1800 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"\n",
|
|
"\n",
|
|
"df = costs\n",
|
|
"df = df.astype(int)\n",
|
|
"df.index = df.index / 1000\n",
|
|
"df.columns = df.columns / 1000\n",
|
|
"\n",
|
|
"plt.figure(figsize=figure_size)\n",
|
|
"sns.heatmap(df/1000000, fmt=\".1f\", cmap='viridis', annot=annot_cost)\n",
|
|
"plt.title(title_cost)\n",
|
|
"plt.gca().invert_yaxis()\n",
|
|
"plt.xlabel('ESS Capacity (MWh)')\n",
|
|
"plt.ylabel('PV Capacity (MW)')\n",
|
|
"plt.savefig('plots/costs.png')\n",
|
|
"\n",
|
|
" # pv = pv_config(capacity=100000,cost_per_kW=200,lifetime=25,loss=0.95)\n",
|
|
" # ess = ess_config(capacity=100000,cost_per_kW=300,lifetime=25,loss=0.95,charge_power=100000,discharge_power=100000)\n",
|
|
" # grid = grid_config(price_schedule=price_schedule, capacity=5000, grid_loss=0.95, sell_price=0.4)\n",
|
|
" # grid = grid_config(capacity=50000, grid_loss=0.95, sell_price=0.4)\n",
|
|
"\n",
|
|
"\n",
|
|
" # print(benefit)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 23,
|
|
"metadata": {},
|
|
"outputs": [
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{
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",
|
|
"text/plain": [
|
|
"<Figure size 2000x1800 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"from matplotlib.colors import LinearSegmentedColormap\n",
|
|
"df = overload_cnt\n",
|
|
"df = df.astype(int)\n",
|
|
"df.index = df.index / 1000\n",
|
|
"df.columns = df.columns / 1000\n",
|
|
"min_value = df.min().min()\n",
|
|
"max_value = df.max().max()\n",
|
|
"max_scale = max(abs(min_value/1000), abs(max_value/1000))\n",
|
|
"\n",
|
|
"plt.figure(figsize=figure_size)\n",
|
|
"cmap = LinearSegmentedColormap.from_list(\"\", [\"white\", \"blue\"])\n",
|
|
"ax = sns.heatmap(df/(4*24*365), fmt=\".00%\", cmap=cmap, vmin=0, vmax=1, annot=annot_unmet)\n",
|
|
"cbar = ax.collections[0].colorbar\n",
|
|
"cbar.set_ticks([0, 0.25, 0.5, 0.75, 1])\n",
|
|
"cbar.set_ticklabels(['0%', '25%', '50%', '75%', '100%'])\n",
|
|
"cbar.ax.yaxis.set_major_formatter(ticker.FuncFormatter(lambda x, pos: f'{x:.0%}'))\n",
|
|
"\n",
|
|
"plt.title(title_unmet)\n",
|
|
"plt.gca().invert_yaxis()\n",
|
|
"plt.xlabel('ESS Capacity (MWh)')\n",
|
|
"plt.ylabel('PV Capacity (MW)')\n",
|
|
"plt.savefig('plots/unmet.png')"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"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": "3.11.0"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|