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simple-pv-simulator/main.ipynb

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{
"cells": [
{
"cell_type": "code",
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"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import glob\n",
"import shutil\n",
"\n",
"def clear_folder_make_ess_pv(folder_path):\n",
" shutil.rmtree(folder_path)\n",
" os.makedirs(folder_path)\n",
" os.makedirs(os.path.join(folder_path,'ess'))\n",
" os.makedirs(os.path.join(folder_path,'pv'))\n",
"\n",
"folder_path = 'plots'\n",
"clear_folder_make_ess_pv(folder_path)"
]
},
{
"cell_type": "code",
"execution_count": 32,
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"metadata": {},
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"outputs": [],
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"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",
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"figure_size = (10,8)\n"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
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"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",
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"pv_lifetime = 15\n",
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"\n",
"ess_loss = 0.98\n",
"ess_cost_per_kW = 300\n",
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"ess_lifetime = 8\n",
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"\n",
"grid_loss = 0.98\n",
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"sell_price = 0.2 #kWh\n",
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"grid_capacity = 5000 #kWh\n",
"\n",
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"pv_capacities = np.linspace(30000, 50000, 5)\n",
"ess_capacities = np.linspace(50000, 100000, 5)\n",
"results = pd.DataFrame(index=pv_capacities, columns= ess_capacities)\n",
"affords = pd.DataFrame(index=pv_capacities, columns= ess_capacities)\n",
"overload_cnt = pd.DataFrame(index=pv_capacities, columns= ess_capacities)\n"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
"hour_demand = []\n",
"for index, row in data.iterrows():\n",
" time = row['time']\n",
" demand = row['demand']\n",
" if time.endswith('00'):\n",
" hour_demand.append(demand)\n",
"plt.figure(figsize=(10,8))\n",
"plt.plot(hour_demand)\n",
"plt.ylabel('Demand Power / kW')\n",
"plt.savefig('plots/demand.png')\n",
"plt.close()"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [],
"source": [
"def cal_profit(es: EnergySystem, saved_money):\n",
" profit = saved_money - es.ess.get_cost_per_year() - es.pv.get_cost_per_year()\n",
" return profit"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"pv_capacity:6000.0\n",
"ess_capacity:20000.0\n",
"ess_capacity:40000.0\n",
"ess_capacity:60000.0\n",
"ess_capacity:80000.0\n",
"ess_capacity:100000.0\n",
"pv_capacity:12000.0\n",
"ess_capacity:20000.0\n",
"ess_capacity:40000.0\n",
"ess_capacity:60000.0\n",
"ess_capacity:80000.0\n",
"ess_capacity:100000.0\n",
"pv_capacity:18000.0\n",
"ess_capacity:20000.0\n",
"ess_capacity:40000.0\n",
"ess_capacity:60000.0\n",
"ess_capacity:80000.0\n",
"ess_capacity:100000.0\n",
"pv_capacity:24000.0\n",
"ess_capacity:20000.0\n",
"ess_capacity:40000.0\n",
"ess_capacity:60000.0\n",
"ess_capacity:80000.0\n",
"ess_capacity:100000.0\n",
"pv_capacity:30000.0\n",
"ess_capacity:20000.0\n",
"ess_capacity:40000.0\n",
"ess_capacity:60000.0\n",
"ess_capacity:80000.0\n",
"ess_capacity:100000.0\n"
]
}
],
"source": [
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"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",
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" results.loc[pv_capacity,ess_capacity] = cal_profit(energySystem, benefit)\n",
" affords.loc[pv_capacity,ess_capacity] = energySystem.afford\n",
" overload_cnt.loc[pv_capacity,ess_capacity] = energySystem.overload_cnt\n",
" pv_generated = energySystem.day_generated\n",
" ess_generated = energySystem.hour_stored\n",
" ess_generated_2 = energySystem.hour_stored_2\n",
" plt.figure(figsize=(10,8));\n",
" plt.plot(ess_generated)\n",
" plt.xlabel('day #')\n",
" plt.ylabel('SoC %')\n",
" plt.title(f'14:00 ESS SoC \\n PV cap:{pv_capacity}, ESS cap:{ess_capacity}')\n",
" plt.savefig(f'plots/ess/1400-{pv_capacity}-{ess_capacity}.png')\n",
" plt.close()\n",
" plt.figure(figsize=(10,8));\n",
" plt.plot(ess_generated_2)\n",
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" plt.xlabel('day #')\n",
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" plt.ylabel('SoC%')\n",
" plt.title(f'08:00 ESS SoC \\n PV cap:{pv_capacity}, ESS cap:{ess_capacity}')\n",
" plt.savefig(f'plots/ess/0800-{pv_capacity}-{ess_capacity}.png')\n",
" plt.close()\n",
"\n",
" spring_week_start = energySystem.season_start\n",
" spring_week_end = spring_week_start + energySystem.week_length\n",
" summer_week_start = energySystem.season_start + 1 * energySystem.season_step\n",
" summer_week_end = summer_week_start + energySystem.week_length\n",
" autumn_week_start = energySystem.season_start + 2 * energySystem.season_step\n",
" autumn_week_end = autumn_week_start + energySystem.week_length\n",
" winter_week_start = energySystem.season_start + 3 * energySystem.season_step\n",
" winter_week_end = winter_week_start+ energySystem.week_length\n",
"\n",
" spring_consume_data = []\n",
" summer_consume_data = []\n",
" autumn_consume_data = []\n",
" winter_consume_data = []\n",
" for index, row in data.iterrows():\n",
" if index in range(spring_week_start, spring_week_end):\n",
" spring_consume_data.append(row['demand'])\n",
" elif index in range(summer_week_start, summer_week_end):\n",
" summer_consume_data.append(row['demand'])\n",
" elif index in range(autumn_week_start, autumn_week_end):\n",
" autumn_consume_data.append(row['demand'])\n",
" elif index in range(winter_week_start, winter_week_end):\n",
" winter_consume_data.append(row['demand'])\n",
"\n",
" spring_week_time = list(range(spring_week_start, spring_week_end))\n",
" summer_week_time = list(range(summer_week_start, summer_week_end))\n",
" autumn_week_time = list(range(autumn_week_start, autumn_week_end))\n",
" winter_week_time = list(range(winter_week_start, winter_week_end))\n",
"\n",
" spring_pv_generated = energySystem.spring_week_gen\n",
" summer_pv_generated = energySystem.summer_week_gen\n",
" autumn_pv_generated = energySystem.autumn_week_gen\n",
" winter_pv_generated = energySystem.winter_week_gen\n",
"\n",
" plt.plot(spring_week_time, spring_pv_generated, label = 'pv generation')\n",
" plt.plot(spring_week_time, spring_consume_data, label = 'factory consume')\n",
" plt.ylabel('Power / kW')\n",
" plt.xlabel('15 min #')\n",
" plt.title(f'ess: {energySystem.ess.capacity/1000 } MWh pv: {energySystem.pv.capacity/1000 } MW spring week generate condition')\n",
" plt.legend()\n",
" plt.savefig(f'plots/{energySystem.ess.capacity}-{energySystem.pv.capacity}-spring.png')\n",
" plt.close()\n",
"\n",
" plt.plot(summer_week_time, summer_pv_generated, label = 'pv generation')\n",
" plt.plot(summer_week_time, summer_consume_data, label = 'factory consume')\n",
" plt.ylabel('Power / kW')\n",
" plt.xlabel('15 min #')\n",
" plt.title(f'ess: {energySystem.ess.capacity/1000 } MWh pv: {energySystem.pv.capacity/1000 } MW summer week generate condition')\n",
" plt.legend()\n",
" plt.savefig(f'plots/{energySystem.ess.capacity}-{energySystem.pv.capacity}-summer.png')\n",
" plt.close()\n",
"\n",
" plt.plot(autumn_week_time, autumn_pv_generated, label = 'pv generation')\n",
" plt.plot(autumn_week_time, autumn_consume_data, label = 'factory consume')\n",
" plt.ylabel('Power / kW')\n",
" plt.xlabel('15 min #')\n",
" plt.title(f'ess: {energySystem.ess.capacity/1000 } MWh pv: {energySystem.pv.capacity/1000 } MW autumn week generate condition')\n",
" plt.legend()\n",
" plt.savefig(f'plots/{energySystem.ess.capacity}-{energySystem.pv.capacity}-autumn.png')\n",
" plt.close()\n",
"\n",
" plt.plot(winter_week_time, winter_pv_generated, label = 'pv generation')\n",
" plt.plot(winter_week_time, winter_consume_data, label = 'factory consume')\n",
" plt.ylabel('Power / kW')\n",
" plt.xlabel('15 min #')\n",
" plt.title(f'ess: {energySystem.ess.capacity/1000 } MWh pv: {energySystem.pv.capacity/1000 } MW winter week generate condition')\n",
" plt.legend()\n",
" plt.savefig(f'plots/{energySystem.ess.capacity}-{energySystem.pv.capacity}-winter.png')\n",
" plt.close()\n",
"\n",
" plt.figure();\n",
" plt.plot(pv_generated)\n",
" plt.xlabel('day #')\n",
" plt.ylabel('Electricity kWh')\n",
" plt.title(f'PV generated pv cap:{pv_capacity}, ess cap:{ess_capacity}')\n",
" plt.savefig(f'plots/pv/{pv_capacity}-{ess_capacity}.png')\n",
" plt.close()\n",
"\n",
"\n",
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" # plt.show()\n",
"\n",
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"\n",
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" \n",
"\n",
"# results = results.astype(float)\n",
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"\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",
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"execution_count": 37,
"metadata": {},
"outputs": [
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},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"energySystem.spring_week_gen"
]
},
{
"cell_type": "code",
"execution_count": null,
try to plot a pic
2024-05-04 09:59:27 +02:00
"metadata": {},
"outputs": [],
add plot code
2024-05-06 19:23:42 +02:00
"source": [
"\n"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(95.72222222222221, 0.5, 'PV Capacity (MW)')"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"text/plain": [
"<Figure size 1000x800 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
try to plot a pic
2024-05-04 09:59:27 +02:00
"source": [
"df=results\n",
add plot code'
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"df = df.astype(float)\n",
add plot code
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"df.index = df.index / 1000\n",
"df.columns = df.columns / 1000\n",
"plt.figure(figsize=figure_size)\n",
"sns.heatmap(df/1000, annot=True, fmt=\".1f\", cmap='viridis')\n",
"plt.title('Benefit Heatmap Based on PV and ESS Capacities (kEUR/year)')\n",
"plt.gca().invert_yaxis()\n",
"plt.xlabel('ESS Capacity (MWh)')\n",
"plt.ylabel('PV Capacity (MW)')\n"
try to plot a pic
2024-05-04 09:59:27 +02:00
]
},
{
"cell_type": "code",
add plot code
2024-05-06 19:23:42 +02:00
"execution_count": 39,
try to plot a pic
2024-05-04 09:59:27 +02:00
"metadata": {},
"outputs": [
{
"data": {
add plot code'
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"text/plain": [
add plot code
2024-05-06 19:23:42 +02:00
"Text(95.72222222222221, 0.5, 'PV Capacity (MW)')"
add plot code'
2024-05-04 16:35:55 +02:00
]
},
add plot code
2024-05-06 19:23:42 +02:00
"execution_count": 39,
add plot code'
2024-05-04 16:35:55 +02:00
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
add plot code
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"image/png": "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"text/plain": [
add plot code
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"<Figure size 1000x800 with 2 Axes>"
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]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
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"\n",
"df = affords\n",
"df = df.astype(bool)\n",
"df.index = df.index / 1000\n",
"df.columns = df.columns / 1000\n",
"\n",
"plt.figure(figsize=figure_size)\n",
"sns.heatmap(df, annot=True, fmt=\".1f\", cmap='viridis')\n",
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"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",
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"\n",
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"\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)"
]
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},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(95.72222222222221, 0.5, 'PV Capacity (MW)')"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 1000x800 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"\n",
"df = overload_cnt\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, annot=True, fmt=\".1f\", cmap='viridis')\n",
"plt.title('Number of unmet electricity demands')\n",
"plt.gca().invert_yaxis()\n",
"plt.xlabel('ESS Capacity (MWh)')\n",
"plt.ylabel('PV Capacity (MW)')"
]
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}
],
"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",
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"version": "3.11.9"
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}
},
"nbformat": 4,
"nbformat_minor": 2
}
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