{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Wind farm optimisation"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"import cartopy.crs as ccrs\n",
"import contextily as cx\n",
"import geopandas as gpd\n",
"import mapclassify as mc\n",
"import matplotlib.patches as mpatches\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"from cartopy.mpl.ticker import LatitudeFormatter, LongitudeFormatter\n",
"from matplotlib import patheffects\n",
"from matplotlib_scalebar.scalebar import ScaleBar\n",
"\n",
"from h2ss import capacity as cap\n",
"from h2ss import compare\n",
"from h2ss import data as rd\n",
"from h2ss import functions as fns\n",
"from h2ss import optimisation as opt"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# basemap cache directory\n",
"cx.set_cache_dir(os.path.join(\"data\", \"basemaps\"))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Halite data"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"ds, extent = rd.kish_basin_data_depth_adjusted(\n",
" dat_path=os.path.join(\"data\", \"kish-basin\"),\n",
" bathymetry_path=os.path.join(\"data\", \"bathymetry\"),\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Constraints"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# exploration wells\n",
"_, wells_b = fns.constraint_exploration_well(\n",
" data_path=os.path.join(\n",
" \"data\",\n",
" \"exploration-wells\",\n",
" \"Exploration_Wells_Irish_Offshore.shapezip.zip\",\n",
" )\n",
")\n",
"\n",
"# wind farms\n",
"wind_farms = fns.constraint_wind_farm(\n",
" data_path=os.path.join(\n",
" \"data\", \"wind-farms\", \"marine-area-consent-wind.zip\"\n",
" )\n",
")\n",
"\n",
"# frequent shipping routes\n",
"_, shipping_b = fns.constraint_shipping_routes(\n",
" data_path=os.path.join(\n",
" \"data\", \"shipping\", \"shipping_frequently_used_routes.zip\"\n",
" ),\n",
" dat_extent=extent,\n",
")\n",
"\n",
"# shipwrecks\n",
"_, shipwrecks_b = fns.constraint_shipwrecks(\n",
" data_path=os.path.join(\n",
" \"data\", \"shipwrecks\", \"IE_GSI_MI_Shipwrecks_IE_Waters_WGS84_LAT.zip\"\n",
" ),\n",
" dat_extent=extent,\n",
")\n",
"\n",
"# subsea cables\n",
"_, cables_b = fns.constraint_subsea_cables(\n",
" data_path=os.path.join(\"data\", \"subsea-cables\", \"KIS-ORCA.gpkg\"),\n",
" dat_extent=extent,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# distance from salt formation edge\n",
"edge_buffer = fns.constraint_halite_edge(dat_xr=ds)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Zones of interest"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"zones, zds = fns.zones_of_interest(\n",
" dat_xr=ds,\n",
" constraints={\"net_height\": 120, \"min_depth\": 500, \"max_depth\": 2000},\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Generate caverns"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"caverns = fns.generate_caverns_hexagonal_grid(\n",
" zones_df=zones,\n",
" dat_extent=extent,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"caverns = fns.cavern_dataframe(\n",
" dat_zone=zds,\n",
" cavern_df=caverns,\n",
" depths={\"min\": 500, \"min_opt\": 1000, \"max_opt\": 1500, \"max\": 2000},\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"# label caverns by depth and heights\n",
"caverns = fns.label_caverns(\n",
" cavern_df=caverns,\n",
" heights=[120],\n",
" depths={\"min\": 500, \"min_opt\": 1000, \"max_opt\": 1500, \"max\": 2000},\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"metadata": {}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Without constraints...\n",
"Number of potential caverns: 568\n",
"------------------------------------------------------------\n",
"Excluding salt formation edges...\n",
"Number of potential caverns: 539\n",
"------------------------------------------------------------\n",
"Exclude shipping...\n",
"Number of potential caverns: 261\n",
"Caverns excluded: 51.58%\n",
"------------------------------------------------------------\n",
"Exclude wind farms...\n",
"Number of potential caverns: 218\n",
"Caverns excluded: 59.55%\n",
"------------------------------------------------------------\n",
"Exclude cables...\n",
"Number of potential caverns: 218\n",
"Caverns excluded: 59.55%\n",
"------------------------------------------------------------\n",
"Exclude wells...\n",
"Number of potential caverns: 218\n",
"Caverns excluded: 59.55%\n",
"------------------------------------------------------------\n",
"Exclude shipwrecks...\n",
"Number of potential caverns: 218\n",
"Caverns excluded: 59.55%\n",
"------------------------------------------------------------\n"
]
}
],
"source": [
"caverns, _ = fns.generate_caverns_with_constraints(\n",
" cavern_df=caverns,\n",
" exclusions={\n",
" \"wells\": wells_b,\n",
" \"wind_farms\": wind_farms,\n",
" \"shipwrecks\": shipwrecks_b,\n",
" \"shipping\": shipping_b,\n",
" \"cables\": cables_b,\n",
" \"edge\": edge_buffer,\n",
" },\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Capacity"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"metadata": {}
},
"outputs": [],
"source": [
"caverns[\"cavern_total_volume\"] = cap.cavern_volume(\n",
" height=caverns[\"cavern_height\"]\n",
")\n",
"caverns[\"cavern_volume\"] = cap.corrected_cavern_volume(\n",
" v_cavern=caverns[\"cavern_total_volume\"]\n",
")\n",
"\n",
"caverns[\"t_mid_point\"] = cap.temperature_cavern_mid_point(\n",
" height=caverns[\"cavern_height\"], depth_top=caverns[\"cavern_depth\"]\n",
")\n",
"\n",
"(\n",
" caverns[\"p_operating_min\"],\n",
" caverns[\"p_operating_max\"],\n",
") = cap.pressure_operating(\n",
" thickness_overburden=caverns[\"TopDepthSeabed\"],\n",
" depth_water=-caverns[\"Bathymetry\"],\n",
")\n",
"\n",
"caverns[\"rho_min\"], caverns[\"rho_max\"] = cap.density_hydrogen_gas(\n",
" p_operating_min=caverns[\"p_operating_min\"],\n",
" p_operating_max=caverns[\"p_operating_max\"],\n",
" t_mid_point=caverns[\"t_mid_point\"],\n",
")\n",
"\n",
"(\n",
" caverns[\"working_mass\"],\n",
" caverns[\"mass_operating_min\"],\n",
" caverns[\"mass_operating_max\"],\n",
") = cap.mass_hydrogen_working(\n",
" rho_h2_min=caverns[\"rho_min\"],\n",
" rho_h2_max=caverns[\"rho_max\"],\n",
" v_cavern=caverns[\"cavern_volume\"],\n",
")\n",
"\n",
"caverns[\"capacity\"] = cap.energy_storage_capacity(\n",
" m_working=caverns[\"working_mass\"]\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Power curve [MW] and Weibull wind speed distribution"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"metadata": {}
},
"outputs": [],
"source": [
"# extract data for wind farms at 150 m\n",
"weibull_wf_df = fns.read_weibull_data(\n",
" data_path_weibull=os.path.join(\n",
" \"data\", \"weibull-parameters-wind-speeds\", \"Weibull_150m_params_ITM.zip\"\n",
" ),\n",
" data_path_wind_farms=os.path.join(\n",
" \"data\", \"wind-farms\", \"marine-area-consent-wind.zip\"\n",
" ),\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"metadata": {}
},
"outputs": [],
"source": [
"weibull_powercurve = opt.weibull_distribution(weibull_wf_data=weibull_wf_df)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"metadata": {}
},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" wind_speed | \n",
" power_curve | \n",
" Codling Wind Park | \n",
" Dublin Array | \n",
" North Irish Sea Array | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" 0.00 | \n",
" 0.0 | \n",
" 0.000000 | \n",
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\n",
" \n",
" 1 | \n",
" 0.01 | \n",
" 0.0 | \n",
" 0.000250 | \n",
" 0.000260 | \n",
" 0.000070 | \n",
"
\n",
" \n",
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" 0.02 | \n",
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" 0.000484 | \n",
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" 0.000154 | \n",
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\n",
" \n",
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" 0.000243 | \n",
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\n",
" \n",
" 4 | \n",
" 0.04 | \n",
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\n",
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\n",
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"
],
"text/plain": [
" wind_speed power_curve Codling Wind Park Dublin Array \\\n",
"0 0.00 0.0 0.000000 0.000000 \n",
"1 0.01 0.0 0.000250 0.000260 \n",
"2 0.02 0.0 0.000484 0.000503 \n",
"3 0.03 0.0 0.000711 0.000739 \n",
"4 0.04 0.0 0.000935 0.000972 \n",
"\n",
" North Irish Sea Array \n",
"0 0.000000 \n",
"1 0.000070 \n",
"2 0.000154 \n",
"3 0.000243 \n",
"4 0.000337 "
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"weibull_powercurve.head()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"metadata": {}
},
"outputs": [
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = weibull_powercurve.plot(\n",
" x=\"wind_speed\",\n",
" y=\"power_curve\",\n",
" linewidth=3,\n",
" color=\"tab:blue\",\n",
" figsize=(10, 5.5),\n",
" legend=False,\n",
")\n",
"ax.set_xlabel(\"Wind speed [m s\\N{SUPERSCRIPT MINUS}\\N{SUPERSCRIPT ONE}]\")\n",
"ax.set_ylabel(\"Power [MW]\")\n",
"plt.yticks([3 * n for n in range(6)])\n",
"sns.despine()\n",
"ax.xaxis.grid(True, linewidth=0.25)\n",
"ax.yaxis.grid(True, linewidth=0.25)\n",
"plt.tight_layout()\n",
"# plt.savefig(\n",
"# os.path.join(\"graphics\", \"Figure_6.png\"), format=\"png\", dpi=600\n",
"# )\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"metadata": {}
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(10, 5.5))\n",
"ax = sns.lineplot(\n",
" data=weibull_powercurve.drop(columns=[\"power_curve\"]).melt(\n",
" id_vars=\"wind_speed\"\n",
" ),\n",
" x=\"wind_speed\",\n",
" y=\"value\",\n",
" hue=\"variable\",\n",
" linestyle=\"dashed\",\n",
" linewidth=2.25,\n",
" alpha=0.85,\n",
" palette=sns.color_palette([\"tab:red\", \"tab:gray\", \"tab:blue\"]),\n",
")\n",
"ax.set_xlabel(\"Wind speed [m s\\N{SUPERSCRIPT MINUS}\\N{SUPERSCRIPT ONE}]\")\n",
"ax.set_ylabel(\n",
" \"Weibull probability distribution function \"\n",
" \"[s m\\N{SUPERSCRIPT MINUS}\\N{SUPERSCRIPT ONE}]\"\n",
")\n",
"ax.xaxis.grid(True, linewidth=0.25)\n",
"ax.yaxis.grid(True, linewidth=0.25)\n",
"sns.despine()\n",
"ax.legend(title=None, fontsize=10.5)\n",
"plt.tight_layout()\n",
"# plt.savefig(\n",
"# os.path.join(\"graphics\", \"fig_weibull.jpg\"), format=\"jpg\", dpi=600\n",
"# )\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Number of reference wind turbines"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"metadata": {}
},
"outputs": [],
"source": [
"# number of 15 MW turbines, rounded down to the nearest integer\n",
"weibull_wf_df[\"n_turbines\"] = opt.number_of_turbines(\n",
" owf_cap=weibull_wf_df[\"cap\"]\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Annual energy production [MWh]"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"metadata": {}
},
"outputs": [],
"source": [
"weibull_wf_df = opt.annual_energy_production(weibull_wf_data=weibull_wf_df)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Annual hydrogen production [kg]"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"metadata": {}
},
"outputs": [],
"source": [
"weibull_wf_df[\"AHP\"] = opt.annual_hydrogen_production(aep=weibull_wf_df[\"AEP\"])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## AHP as a proportion of the total working mass"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"metadata": {}
},
"outputs": [],
"source": [
"weibull_wf_df[\"AHP_frac\"] = (\n",
" weibull_wf_df[\"AHP\"] / caverns[[\"working_mass\"]].sum().iloc[0]\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## AHP converted to storage demand [GWh]"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"metadata": {}
},
"outputs": [],
"source": [
"weibull_wf_df[\"demand\"] = cap.energy_storage_capacity(\n",
" m_working=weibull_wf_df[\"AHP\"]\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Number of caverns required based on cumulative working mass and AHP"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"metadata": {}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Codling Wind Park\n",
"Working mass [kg]: 1.095672E+08\n",
"Number of caverns required: 25–51\n",
"Capacity (approx.) [GWh]: 3,735.76\n",
"------------------------------------------------------------------------------\n",
"Dublin Array\n",
"Working mass [kg]: 6.742514E+07\n",
"Number of caverns required: 15–33\n",
"Capacity (approx.) [GWh]: 2,289.53\n",
"------------------------------------------------------------------------------\n",
"North Irish Sea Array\n",
"Working mass [kg]: 4.515738E+07\n",
"Number of caverns required: 10–24\n",
"Capacity (approx.) [GWh]: 1,556.50\n",
"------------------------------------------------------------------------------\n",
"Total number of caverns required: 50–108\n",
"------------------------------------------------------------------------------\n",
"Number of caverns required as a percentage of all available caverns:\n",
"22.94–49.54%\n",
"------------------------------------------------------------------------------\n",
"Total maximum cavern capacity (approx.): 7,581.79 GWh\n"
]
}
],
"source": [
"compare.calculate_number_of_caverns(\n",
" cavern_df=caverns, weibull_wf_data=weibull_wf_df\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Transmission distance [km]"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"metadata": {}
},
"outputs": [],
"source": [
"caverns, injection_point = opt.transmission_distance(\n",
" cavern_df=caverns, wf_data=wind_farms\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Electrolyser capacity [MW]"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"metadata": {}
},
"outputs": [],
"source": [
"weibull_wf_df[\"E_cap\"] = opt.electrolyser_capacity(\n",
" n_turbines=weibull_wf_df[\"n_turbines\"]\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## CAPEX for pipeline [€ km⁻¹]"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"metadata": {}
},
"outputs": [],
"source": [
"weibull_wf_df[\"CAPEX\"] = opt.capex_pipeline(e_cap=weibull_wf_df[\"E_cap\"])"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"metadata": {}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" name | \n",
" cap | \n",
" (c, min) | \n",
" (c, max) | \n",
" (c, mean) | \n",
" (k, min) | \n",
" (k, max) | \n",
" (k, mean) | \n",
" n_turbines | \n",
" AEP | \n",
" integral | \n",
" abserr | \n",
" AHP | \n",
" AHP_frac | \n",
" demand | \n",
" E_cap | \n",
" CAPEX | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" Codling Wind Park | \n",
" 1300 | \n",
" 10.2 | \n",
" 10.8 | \n",
" 10.500000 | \n",
" 1.9 | \n",
" 2.0 | \n",
" 1.950000 | \n",
" 86 | \n",
" 5.550255e+06 | \n",
" 8.335975 | \n",
" 2.528685e-07 | \n",
" 1.095672e+08 | \n",
" 0.154167 | \n",
" 3651.022453 | \n",
" 1070 | \n",
" 1.451786e+06 | \n",
"
\n",
" \n",
" 1 | \n",
" Dublin Array | \n",
" 824 | \n",
" 9.9 | \n",
" 10.6 | \n",
" 10.292857 | \n",
" 1.9 | \n",
" 2.0 | \n",
" 1.950000 | \n",
" 54 | \n",
" 3.415500e+06 | \n",
" 8.169630 | \n",
" 3.778893e-07 | \n",
" 6.742514e+07 | \n",
" 0.094871 | \n",
" 2246.755615 | \n",
" 672 | \n",
" 1.205538e+06 | \n",
"
\n",
" \n",
" 2 | \n",
" North Irish Sea Array | \n",
" 500 | \n",
" 10.7 | \n",
" 11.2 | \n",
" 10.950000 | \n",
" 2.1 | \n",
" 2.2 | \n",
" 2.133333 | \n",
" 33 | \n",
" 2.287500e+06 | \n",
" 8.953423 | \n",
" 1.516351e-07 | \n",
" 4.515738e+07 | \n",
" 0.063539 | \n",
" 1504.744246 | \n",
" 410 | \n",
" 1.032447e+06 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" name cap (c, min) (c, max) (c, mean) (k, min) \\\n",
"0 Codling Wind Park 1300 10.2 10.8 10.500000 1.9 \n",
"1 Dublin Array 824 9.9 10.6 10.292857 1.9 \n",
"2 North Irish Sea Array 500 10.7 11.2 10.950000 2.1 \n",
"\n",
" (k, max) (k, mean) n_turbines AEP integral abserr \\\n",
"0 2.0 1.950000 86 5.550255e+06 8.335975 2.528685e-07 \n",
"1 2.0 1.950000 54 3.415500e+06 8.169630 3.778893e-07 \n",
"2 2.2 2.133333 33 2.287500e+06 8.953423 1.516351e-07 \n",
"\n",
" AHP AHP_frac demand E_cap CAPEX \n",
"0 1.095672e+08 0.154167 3651.022453 1070 1.451786e+06 \n",
"1 6.742514e+07 0.094871 2246.755615 672 1.205538e+06 \n",
"2 4.515738e+07 0.063539 1504.744246 410 1.032447e+06 "
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"weibull_wf_df"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"metadata": {}
},
"outputs": [
{
"data": {
"text/plain": [
"cap 2.624000e+03\n",
"n_turbines 1.730000e+02\n",
"AEP 1.125325e+07\n",
"AHP 2.221497e+08\n",
"AHP_frac 3.125772e-01\n",
"demand 7.402522e+03\n",
"E_cap 2.152000e+03\n",
"CAPEX 3.689771e+06\n",
"dtype: float64"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# totals\n",
"weibull_wf_df[\n",
" [\"cap\", \"n_turbines\", \"AEP\", \"AHP\", \"AHP_frac\", \"demand\", \"E_cap\", \"CAPEX\"]\n",
"].sum()"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"metadata": {}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Energy capacity as a percentage of Ireland's electricity demand\n",
"in 2050 (84–122 TWh electricity), assuming a conversion efficiency\n",
"of 50%: 3.03–4.41%\n",
"Energy capacity as a percentage of Ireland's hydrogen demand\n",
"in 2050, assuming it is 17% of the electricity demand\n",
"(84–122 TWh electricity): 35.69–51.84%\n"
]
}
],
"source": [
"compare.electricity_demand_ie(data=weibull_wf_df[\"demand\"])"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"metadata": {}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Energy capacity as a percentage of Ireland's domestic hydrogen\n",
"demand in 2050 (4.6–39 TWh hydrogen): 18.98–160.92%\n",
"Energy capacity as a percentage of Ireland's domestic and\n",
"non-domestic hydrogen demand in 2050 (19.8–74.6 TWh hydrogen): 9.92–37.39%\n"
]
}
],
"source": [
"compare.hydrogen_demand_ie(data=weibull_wf_df[\"demand\"])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## LCOT for pipeline [€ kg⁻¹]"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"metadata": {}
},
"outputs": [],
"source": [
"caverns = opt.lcot_pipeline(weibull_wf_data=weibull_wf_df, cavern_df=caverns)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"metadata": {}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" cavern_depth | \n",
" working_mass | \n",
" capacity | \n",
" distance_ip | \n",
" dist_Codling_Wind_Park | \n",
" dist_Dublin_Array | \n",
" dist_North_Irish_Sea_Array | \n",
" LCOT_Codling_Wind_Park | \n",
" LCOT_Dublin_Array | \n",
" LCOT_North_Irish_Sea_Array | \n",
"
\n",
" \n",
" \n",
" \n",
" count | \n",
" 218.000000 | \n",
" 2.180000e+02 | \n",
" 218.000000 | \n",
" 218.000000 | \n",
" 218.000000 | \n",
" 218.000000 | \n",
" 218.000000 | \n",
" 218.000000 | \n",
" 218.000000 | \n",
" 218.000000 | \n",
"
\n",
" \n",
" mean | \n",
" 1154.020877 | \n",
" 3.260108e+06 | \n",
" 108.634041 | \n",
" 29.197826 | \n",
" 58.408245 | \n",
" 43.581633 | \n",
" 44.393167 | \n",
" 0.078615 | \n",
" 0.079154 | \n",
" 0.103102 | \n",
"
\n",
" \n",
" std | \n",
" 365.142804 | \n",
" 7.786651e+05 | \n",
" 25.946851 | \n",
" 6.830597 | \n",
" 11.452952 | \n",
" 13.055932 | \n",
" 7.523248 | \n",
" 0.015415 | \n",
" 0.023713 | \n",
" 0.017473 | \n",
"
\n",
" \n",
" min | \n",
" 502.745339 | \n",
" 1.678950e+06 | \n",
" 55.946359 | \n",
" 16.263066 | \n",
" 33.027322 | \n",
" 17.542931 | \n",
" 32.980512 | \n",
" 0.044454 | \n",
" 0.031862 | \n",
" 0.076596 | \n",
"
\n",
" \n",
" 25% | \n",
" 872.651330 | \n",
" 2.685380e+06 | \n",
" 89.482842 | \n",
" 23.216441 | \n",
" 51.592318 | \n",
" 33.503367 | \n",
" 36.808911 | \n",
" 0.069441 | \n",
" 0.060850 | \n",
" 0.085488 | \n",
"
\n",
" \n",
" 50% | \n",
" 1128.329146 | \n",
" 3.277441e+06 | \n",
" 109.211632 | \n",
" 30.947028 | \n",
" 58.988376 | \n",
" 47.378240 | \n",
" 44.619590 | \n",
" 0.079396 | \n",
" 0.086050 | \n",
" 0.103628 | \n",
"
\n",
" \n",
" 75% | \n",
" 1433.385847 | \n",
" 3.886101e+06 | \n",
" 129.493525 | \n",
" 34.863247 | \n",
" 67.109072 | \n",
" 54.107289 | \n",
" 50.773606 | \n",
" 0.090326 | \n",
" 0.098271 | \n",
" 0.117920 | \n",
"
\n",
" \n",
" max | \n",
" 1980.680682 | \n",
" 4.765555e+06 | \n",
" 158.798899 | \n",
" 42.990158 | \n",
" 80.806729 | \n",
" 70.176200 | \n",
" 67.926218 | \n",
" 0.108763 | \n",
" 0.127456 | \n",
" 0.157757 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" cavern_depth working_mass capacity distance_ip \\\n",
"count 218.000000 2.180000e+02 218.000000 218.000000 \n",
"mean 1154.020877 3.260108e+06 108.634041 29.197826 \n",
"std 365.142804 7.786651e+05 25.946851 6.830597 \n",
"min 502.745339 1.678950e+06 55.946359 16.263066 \n",
"25% 872.651330 2.685380e+06 89.482842 23.216441 \n",
"50% 1128.329146 3.277441e+06 109.211632 30.947028 \n",
"75% 1433.385847 3.886101e+06 129.493525 34.863247 \n",
"max 1980.680682 4.765555e+06 158.798899 42.990158 \n",
"\n",
" dist_Codling_Wind_Park dist_Dublin_Array dist_North_Irish_Sea_Array \\\n",
"count 218.000000 218.000000 218.000000 \n",
"mean 58.408245 43.581633 44.393167 \n",
"std 11.452952 13.055932 7.523248 \n",
"min 33.027322 17.542931 32.980512 \n",
"25% 51.592318 33.503367 36.808911 \n",
"50% 58.988376 47.378240 44.619590 \n",
"75% 67.109072 54.107289 50.773606 \n",
"max 80.806729 70.176200 67.926218 \n",
"\n",
" LCOT_Codling_Wind_Park LCOT_Dublin_Array LCOT_North_Irish_Sea_Array \n",
"count 218.000000 218.000000 218.000000 \n",
"mean 0.078615 0.079154 0.103102 \n",
"std 0.015415 0.023713 0.017473 \n",
"min 0.044454 0.031862 0.076596 \n",
"25% 0.069441 0.060850 0.085488 \n",
"50% 0.079396 0.086050 0.103628 \n",
"75% 0.090326 0.098271 0.117920 \n",
"max 0.108763 0.127456 0.157757 "
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"caverns[\n",
" [\n",
" \"cavern_depth\",\n",
" \"working_mass\",\n",
" \"capacity\",\n",
" \"distance_ip\",\n",
" ]\n",
" + list(caverns.filter(like=\"dist_\"))\n",
" + list(caverns.filter(like=\"LCOT_\"))\n",
"].describe()"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"count 654.000000\n",
"mean 48.794348\n",
"std 12.862247\n",
"min 17.542931\n",
"25% 36.924385\n",
"50% 49.890968\n",
"75% 57.488679\n",
"max 80.806729\n",
"dtype: float64"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.Series(caverns[list(caverns.filter(like=\"dist_\"))].values.flat).describe()"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"count 654.000000\n",
"mean 0.086957\n",
"std 0.022312\n",
"min 0.031862\n",
"25% 0.071538\n",
"50% 0.087836\n",
"75% 0.101471\n",
"max 0.157757\n",
"dtype: float64"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.Series(caverns[list(caverns.filter(like=\"LCOT_\"))].values.flat).describe()"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
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