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try to plot a pic
2024-05-04 09:59:27 +02:00
{
"cells": [
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"pv_capacity:0.0\n",
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"pv_capacity:19000.0\n",
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"ess_capacity:6000.0\n",
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"pv_capacity:20000.0\n",
"ess_capacity:0.0\n",
"ess_capacity:1000.0\n",
"ess_capacity:2000.0\n",
"ess_capacity:3000.0\n",
"ess_capacity:4000.0\n",
"ess_capacity:5000.0\n",
"ess_capacity:6000.0\n",
"ess_capacity:7000.0\n",
"ess_capacity:8000.0\n",
"ess_capacity:9000.0\n",
"ess_capacity:10000.0\n",
"ess_capacity:11000.0\n",
"ess_capacity:12000.0\n",
"ess_capacity:13000.0\n",
"ess_capacity:14000.0\n",
"ess_capacity:15000.0\n",
"ess_capacity:16000.0\n",
"ess_capacity:17000.0\n",
"ess_capacity:18000.0\n",
"ess_capacity:19000.0\n",
"ess_capacity:20000.0\n"
]
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"import numpy as np\n",
"import pandas as pd\n",
"from EnergySystem import EnergySystem\n",
"from config import pv_config, grid_config, ess_config\n",
"\n",
"\n",
"data = pd.read_csv('combined_data.csv')\n",
"time_interval = 15 / 60\n",
"\n",
"pv_loss = 0.98\n",
"pv_cost_per_kW = 200\n",
"pv_lifetime = 25\n",
"\n",
"ess_loss = 0.98\n",
"ess_cost_per_kW = 300\n",
"ess_lifetime = 25\n",
"\n",
"grid_loss = 0.98\n",
"sell_price = 0.4 #kWh\n",
"grid_capacity = 5000 #kWh\n",
"\n",
"pv_capacities = np.linspace(0, 20000, 5)\n",
"ess_capacities = np.linspace(0, 20000, 5)\n",
"results = pd.DataFrame(index=pv_capacities, columns = ess_capacities)\n",
"for pv_capacity in pv_capacities:\n",
" print(f\"pv_capacity:{pv_capacity}\")\n",
" for ess_capacity in ess_capacities:\n",
" print(f\"ess_capacity:{ess_capacity}\")\n",
" pv = pv_config(capacity=pv_capacity, \n",
" cost_per_kW=pv_cost_per_kW,\n",
" lifetime=pv_lifetime, \n",
" loss=pv_loss)\n",
" ess = ess_config(capacity=ess_capacity, \n",
" cost_per_kW=ess_cost_per_kW, \n",
" lifetime=ess_lifetime, \n",
" loss=ess_loss,\n",
" charge_power=ess_capacity,\n",
" discharge_power=ess_capacity)\n",
" grid = grid_config(capacity=grid_capacity, \n",
" grid_loss=grid_loss,\n",
" sell_price= sell_price)\n",
" energySystem = EnergySystem(pv_type=pv, \n",
" ess_type=ess, \n",
" grid_type= grid)\n",
" benefit = energySystem.simulate(data, time_interval)\n",
" results.loc[pv_capacity,ess_capacity] = benefit\n",
"results = results.astype(float)\n",
"\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)\n"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"df=results\n",
"df.index = df.index / 1000"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 2000x1800 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(20, 18)) # 设置图形大小\n",
"sns.heatmap(df/1000, annot=True, fmt=\".1f\", cmap='viridis')\n",
"plt.title('Benefit Heatmap Based on PV and ESS Capacities')\n",
"plt.gca().invert_yaxis()\n",
"plt.xlabel('ESS Capacity (MWh)')\n",
"plt.ylabel('PV Capacity (MW)')\n",
"plt.show()\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)"
]
}
],
"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": "3.11.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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