Test - compare MTBS xls with python outcomes - Wouter (2 elements).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6bb113ce",
   "metadata": {},
   "source": [
    "#### 0. Import basic methods (a.o. from source2.py)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f9fd7be4",
   "metadata": {},
   "outputs": [],
   "source": [
    "from source2 import *\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ec38e936",
   "metadata": {},
   "outputs": [],
   "source": [
    "# load basic info from the Input sheet\n",
    "mapping = load_input_from_xls(filename=r'Case 1 - Input Sheet.xlsm')\n",
    "Inputs = extract_scenario(mapping, 'Scenario1')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89024b92",
   "metadata": {},
   "source": [
    "##### 1. prepare input data and generate objects\n",
    "We are testing the following cases:\n",
    "##### 1.1 Turbines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6e48b814",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'sub_system': 'Wind energy source & Transport',\n",
       " 'element': 'Offshore wind park',\n",
       " 'component': 'Turbine',\n",
       " 'escalation_base_year': 2023,\n",
       " 'escalation_rate': 0.02,\n",
       " 'capex_per_unit': 1139979.0,\n",
       " 'capex_per_unit_units': 'EUR / MW',\n",
       " 'unit': 3000.0,\n",
       " 'unit_units': 'MW',\n",
       " 'construction_duration': 3,\n",
       " 'share_of_investments': [0.2, 0.4, 0.4],\n",
       " 'economic_lifetime': 30,\n",
       " 'depreciation_flag': 1,\n",
       " 'depreciation_rate': 0.03333333333333333,\n",
       " 'yearly_variable_costs_flag': 1,\n",
       " 'yearly_variable_costs_rate': 0.03,\n",
       " 'insurance_flag': 1,\n",
       " 'insurance_rate': 0.005,\n",
       " 'decommissioning_rate': 0.08,\n",
       " 'residual_value': 0.01}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "turbine_data = get_object_data(Inputs=Inputs, \n",
    "                               subsystem='Wind energy source & Transport', \n",
    "                               element='Offshore wind park',\n",
    "                               component='Turbine')\n",
    "turbine_data['depreciation_rate']=1/turbine_data['economic_lifetime']\n",
    "display(turbine_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a1b0e25d",
   "metadata": {},
   "outputs": [],
   "source": [
    "Turbine = Object(**turbine_data)\n",
    "# hier heb je alleen het object met inputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e9773ec1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "*** determine investment_years, capex_years and capex_values ****\n",
      "\n",
      "initial investment in 2023\n",
      "\n",
      "divestment year: 2052\n",
      "divestment value: 357261393.15\n",
      "\n",
      "CAPEX years escalated: [2023, 2024, 2025, 2052]\n",
      "CAPEX values escalated: [-697667148.0, -1423240981.92, -1451705801.5584, 357261393.14784]\n",
      "\n",
      "*** determine opex_years and opex_values (including decommissioning) ****\n",
      "\n",
      "investment range start 2026 stop 2052\n",
      "opex_value -125041487.60, based on a summed_escalated_capex of -3572613931.48 \n",
      "decommissioning cost of -285809114.52 added in 2052, based on a summed_escalated_capex of -3572613931.48 \n",
      "\n",
      "OPEX years escalated: [2026, 2027, 2028, 2029, 2030, 2031, 2032, 2033, 2034, 2035, 2036, 2037, 2038, 2039, 2040, 2041, 2042, 2043, 2044, 2045, 2046, 2047, 2048, 2049, 2050, 2051, 2052]\n",
      "OPEX values escalated: [-135348927.51436898, -138055906.06465635, -140817024.18594947, -143633364.66966847, -146506031.96306187, -149436152.60232309, -152424875.65436956, -155473373.16745695, -158582840.6308061, -161754497.4434222, -164989587.39229065, -168289379.14013648, -171655166.72293922, -175088270.05739802, -178590035.45854598, -182161836.1677169, -185805072.89107123, -189521174.3488927, -193311597.83587053, -197177829.79258794, -201121386.38843971, -205143814.1162085, -209246690.39853266, -213431624.20650333, -217700256.69063342, -222054261.82444608, -744198997.4859294]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Turbine.generate_cashflows(startyear=2023, lifecycle=30, debug=True)\n",
    "# na deze regel heeft Turbine.df (dataframe met alleen Capex, Opex en Residuals)\n",
    "Turbine.df_npv = calculate_npv(Turbine.df, 2023, WACC=0.0984)\n",
    "create_npv_plot(Turbine.df_npv, title='Turbine \\n Escalation: yes, Residual: yes, Decommissioning: yes' )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67f8ce36",
   "metadata": {},
   "source": [
    "##### 1.2 Foundations and cables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b04ea050",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'sub_system': 'Wind energy source & Transport',\n",
       " 'element': 'Offshore wind park',\n",
       " 'component': 'Foundation & cable',\n",
       " 'escalation_base_year': 2023,\n",
       " 'escalation_rate': 0.02,\n",
       " 'capex_per_unit': 971621.0,\n",
       " 'capex_per_unit_units': 'EUR / MW',\n",
       " 'unit': 3000.0,\n",
       " 'unit_units': 'MW',\n",
       " 'construction_duration': 3,\n",
       " 'share_of_investments': [0.2, 0.4, 0.4],\n",
       " 'economic_lifetime': 30,\n",
       " 'depreciation_flag': 1,\n",
       " 'depreciation_rate': 0.03333333333333333,\n",
       " 'yearly_variable_costs_flag': 1,\n",
       " 'yearly_variable_costs_rate': 0.015,\n",
       " 'insurance_flag': 1,\n",
       " 'insurance_rate': 0.005,\n",
       " 'decommissioning_rate': 0.35,\n",
       " 'residual_value': 0.01}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "foundation_data = get_object_data(Inputs=Inputs, \n",
    "                               subsystem='Wind energy source & Transport', \n",
    "                               element='Offshore wind park',\n",
    "                               component='Foundation & cable')\n",
    "foundation_data['depreciation_rate']=1/foundation_data['economic_lifetime']\n",
    "display(foundation_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cf95a8fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "Foundation = Object(**foundation_data)\n",
    "# hier heb je alleen het object met inputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4fbd1661",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "*** determine investment_years, capex_years and capex_values ****\n",
      "\n",
      "initial investment in 2023\n",
      "\n",
      "divestment year: 2052\n",
      "divestment value: 304499181.19\n",
      "\n",
      "CAPEX years escalated: [2023, 2024, 2025, 2052]\n",
      "CAPEX values escalated: [-594632052.0, -1213049386.08, -1237310373.8016, 304499181.18815994]\n",
      "\n",
      "*** determine opex_years and opex_values (including decommissioning) ****\n",
      "\n",
      "investment range start 2026 stop 2052\n",
      "opex_value -60899836.24, based on a summed_escalated_capex of -3044991811.88 \n",
      "decommissioning cost of -1065747134.16 added in 2052, based on a summed_escalated_capex of -3044991811.88 \n",
      "\n",
      "OPEX years escalated: [2026, 2027, 2028, 2029, 2030, 2031, 2032, 2033, 2034, 2035, 2036, 2037, 2038, 2039, 2040, 2041, 2042, 2043, 2044, 2045, 2046, 2047, 2048, 2049, 2050, 2051, 2052]\n",
      "OPEX values escalated: [-65919941.28234628, -67238340.1079932, -68583106.91015308, -69954769.04835613, -71353864.42932326, -72780941.71790972, -74236560.55226792, -75721291.76331328, -77235717.59857954, -78780431.95055114, -80356040.58956216, -81963161.4013534, -83602424.62938048, -85274473.12196809, -86979962.58440746, -88719561.8360956, -90493953.07281752, -92303832.13427389, -94149908.77695936, -96032906.95249854, -97953565.09154852, -99912636.39337948, -101910889.12124707, -103949106.90367202, -106028089.04174547, -108148650.82258037, -2040765041.0220916]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Foundation.generate_cashflows(startyear=2023, lifecycle=30, debug=True)\n",
    "# na deze regel heeft Turbine.df (dataframe met alleen Capex, Opex en Residuals)\n",
    "Foundation.df_npv = calculate_npv(Foundation.df, 2023, WACC=0.0984)\n",
    "create_npv_plot(Foundation.df_npv, title='Foundation \\n Escalation: yes, Residual: yes, Recommissioning: yes' )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b2026527",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>years</th>\n",
       "      <th>capex</th>\n",
       "      <th>opex</th>\n",
       "      <th>revenue</th>\n",
       "      <th>cashflow</th>\n",
       "      <th>cashflow_sum</th>\n",
       "      <th>npv</th>\n",
       "      <th>npv_sum</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>years</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2048</th>\n",
       "      <td>4096</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>-3.111576e+08</td>\n",
       "      <td>0</td>\n",
       "      <td>-3.111576e+08</td>\n",
       "      <td>-1.242320e+10</td>\n",
       "      <td>-2.711482e+07</td>\n",
       "      <td>-6.975223e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2049</th>\n",
       "      <td>4098</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>-3.173807e+08</td>\n",
       "      <td>0</td>\n",
       "      <td>-3.173807e+08</td>\n",
       "      <td>-1.274058e+10</td>\n",
       "      <td>-2.517946e+07</td>\n",
       "      <td>-7.000403e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2050</th>\n",
       "      <td>4100</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>-3.237283e+08</td>\n",
       "      <td>0</td>\n",
       "      <td>-3.237283e+08</td>\n",
       "      <td>-1.306431e+10</td>\n",
       "      <td>-2.338224e+07</td>\n",
       "      <td>-7.023785e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2051</th>\n",
       "      <td>4102</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>-3.302029e+08</td>\n",
       "      <td>0</td>\n",
       "      <td>-3.302029e+08</td>\n",
       "      <td>-1.339451e+10</td>\n",
       "      <td>-2.171329e+07</td>\n",
       "      <td>-7.045498e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2052</th>\n",
       "      <td>4104</td>\n",
       "      <td>6.617606e+08</td>\n",
       "      <td>-2.784964e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>-2.123203e+09</td>\n",
       "      <td>-1.551771e+10</td>\n",
       "      <td>-1.271089e+08</td>\n",
       "      <td>-7.172607e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       years         capex          opex  revenue      cashflow  cashflow_sum  \\\n",
       "years                                                                           \n",
       "2048    4096  0.000000e+00 -3.111576e+08        0 -3.111576e+08 -1.242320e+10   \n",
       "2049    4098  0.000000e+00 -3.173807e+08        0 -3.173807e+08 -1.274058e+10   \n",
       "2050    4100  0.000000e+00 -3.237283e+08        0 -3.237283e+08 -1.306431e+10   \n",
       "2051    4102  0.000000e+00 -3.302029e+08        0 -3.302029e+08 -1.339451e+10   \n",
       "2052    4104  6.617606e+08 -2.784964e+09        0 -2.123203e+09 -1.551771e+10   \n",
       "\n",
       "                npv       npv_sum  \n",
       "years                              \n",
       "2048  -2.711482e+07 -6.975223e+09  \n",
       "2049  -2.517946e+07 -7.000403e+09  \n",
       "2050  -2.338224e+07 -7.023785e+09  \n",
       "2051  -2.171329e+07 -7.045498e+09  \n",
       "2052  -1.271089e+08 -7.172607e+09  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(Turbine.df+Foundation.df).tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7e17dbe",
   "metadata": {},
   "source": [
    "#####  2. Test values - Turbines\n",
    "##### 2.1 - CAPEX values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5aee3354",
   "metadata": {},
   "outputs": [],
   "source": [
    "MTBS_values = {'years': [2023, 2024, 2025], \n",
    "               'values': [-697_667_148, -1_423_240_982, -1_451_705_802]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f468dd49",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CAPEX value testing in 2023: MTBS: -697667148 TUD/VO: -697667148.0\n",
      "CAPEX value testing in 2024: MTBS: -1423240982 TUD/VO: -1423240981.92\n",
      "CAPEX value testing in 2025: MTBS: -1451705802 TUD/VO: -1451705801.5584\n"
     ]
    }
   ],
   "source": [
    "for index, year in enumerate(MTBS_values['years']):\n",
    "    \n",
    "    print('CAPEX value testing in {}: MTBS: {} TUD/VO: {}'.format(year, MTBS_values['values'][index], Turbine.df[Turbine.df.index==year].capex.item()))\n",
    "    np.testing.assert_almost_equal(MTBS_values['values'][index],  Turbine.df[Turbine.df.index==year].capex.item(), 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9bd2ef8",
   "metadata": {},
   "source": [
    "##### 2.2 - OPEX values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "45178cf4",
   "metadata": {},
   "outputs": [],
   "source": [
    "MTBS_values = {'years': [2026, 2027, 2028, 2029, 2030, 2031, 2032, 2033, 2034, 2035, 2036, 2037, 2038, 2039, 2040, 2041, 2042, 2043, 2044, 2045, 2046, 2047, 2048, 2049, 2050, 2051, 2052],\n",
    "               'values': [-135_348_928, -138_055_906, -140_817_024, -143_633_365, -146_506_032, -149_436_153, -152_424_876, -155_473_373, -158_582_841, -161_754_497, -164_989_587, -168_289_379, -171_655_167, -175_088_270, -178_590_035, -182_161_836, -185_805_073, -189_521_174, -193_311_598, -197_177_830, -201_121_386, -205_143_814, -209_246_690, -213_431_624, -217_700_257, -222_054_262, -744_198_997]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d1402afb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opex value testing in 2026: MTBS: -135348928 TUD/VO: -135348927.51436898\n",
      "Opex value testing in 2027: MTBS: -138055906 TUD/VO: -138055906.06465635\n",
      "Opex value testing in 2028: MTBS: -140817024 TUD/VO: -140817024.18594947\n",
      "Opex value testing in 2029: MTBS: -143633365 TUD/VO: -143633364.66966847\n",
      "Opex value testing in 2030: MTBS: -146506032 TUD/VO: -146506031.96306187\n",
      "Opex value testing in 2031: MTBS: -149436153 TUD/VO: -149436152.60232309\n",
      "Opex value testing in 2032: MTBS: -152424876 TUD/VO: -152424875.65436956\n",
      "Opex value testing in 2033: MTBS: -155473373 TUD/VO: -155473373.16745695\n",
      "Opex value testing in 2034: MTBS: -158582841 TUD/VO: -158582840.6308061\n",
      "Opex value testing in 2035: MTBS: -161754497 TUD/VO: -161754497.4434222\n",
      "Opex value testing in 2036: MTBS: -164989587 TUD/VO: -164989587.39229065\n",
      "Opex value testing in 2037: MTBS: -168289379 TUD/VO: -168289379.14013648\n",
      "Opex value testing in 2038: MTBS: -171655167 TUD/VO: -171655166.72293922\n",
      "Opex value testing in 2039: MTBS: -175088270 TUD/VO: -175088270.05739802\n",
      "Opex value testing in 2040: MTBS: -178590035 TUD/VO: -178590035.45854598\n",
      "Opex value testing in 2041: MTBS: -182161836 TUD/VO: -182161836.1677169\n",
      "Opex value testing in 2042: MTBS: -185805073 TUD/VO: -185805072.89107123\n",
      "Opex value testing in 2043: MTBS: -189521174 TUD/VO: -189521174.3488927\n",
      "Opex value testing in 2044: MTBS: -193311598 TUD/VO: -193311597.83587053\n",
      "Opex value testing in 2045: MTBS: -197177830 TUD/VO: -197177829.79258794\n",
      "Opex value testing in 2046: MTBS: -201121386 TUD/VO: -201121386.38843971\n",
      "Opex value testing in 2047: MTBS: -205143814 TUD/VO: -205143814.1162085\n",
      "Opex value testing in 2048: MTBS: -209246690 TUD/VO: -209246690.39853266\n",
      "Opex value testing in 2049: MTBS: -213431624 TUD/VO: -213431624.20650333\n",
      "Opex value testing in 2050: MTBS: -217700257 TUD/VO: -217700256.69063342\n",
      "Opex value testing in 2051: MTBS: -222054262 TUD/VO: -222054261.82444608\n",
      "Opex value testing in 2052: MTBS: -744198997 TUD/VO: -744198997.4859294\n"
     ]
    }
   ],
   "source": [
    "for index, year in enumerate(MTBS_values['years']):\n",
    "    \n",
    "    print('Opex value testing in {}: MTBS: {} TUD/VO: {}'.format(year, MTBS_values['values'][index], Turbine.df[Turbine.df.index==year].opex.item()))\n",
    "    np.testing.assert_almost_equal(MTBS_values['values'][index],  Turbine.df[Turbine.df.index==year].opex.item(), 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d4e2c84",
   "metadata": {},
   "source": [
    "##### 2.3 - Decommissioning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "9865bfa5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-285809114.51827204"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "2052"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "MTBS_values = {'years': [2052],\n",
    "               'values': [ -517703650]} # decommissioning from MTBS\n",
    "display(Turbine.decommissioning_values[-1])\n",
    "display(Turbine.decommissioning_years[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0dbbcf3b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decommissioning value testing in 2052: MTBS: -517703650 TUD/VO: -285809114.51827204\n"
     ]
    },
    {
     "ename": "AssertionError",
     "evalue": "\nArrays are not almost equal to 0 decimals\n ACTUAL: -517703650\n DESIRED: -285809114.51827204",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
      "Input \u001b[1;32mIn [15]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m index, year \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(MTBS_values[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124myears\u001b[39m\u001b[38;5;124m'\u001b[39m]):\n\u001b[0;32m      3\u001b[0m     \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDecommissioning value testing in \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m: MTBS: \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m TUD/VO: \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mformat(year, MTBS_values[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mvalues\u001b[39m\u001b[38;5;124m'\u001b[39m][index], Turbine\u001b[38;5;241m.\u001b[39mdecommissioning_values[index]))\n\u001b[1;32m----> 4\u001b[0m     \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtesting\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43massert_almost_equal\u001b[49m\u001b[43m(\u001b[49m\u001b[43mMTBS_values\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mvalues\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[43mindex\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m  \u001b[49m\u001b[43mTurbine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecommissioning_values\u001b[49m\u001b[43m[\u001b[49m\u001b[43mindex\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\Anaconda3\\lib\\site-packages\\numpy\\testing\\_private\\utils.py:599\u001b[0m, in \u001b[0;36massert_almost_equal\u001b[1;34m(actual, desired, decimal, err_msg, verbose)\u001b[0m\n\u001b[0;32m    597\u001b[0m     \u001b[38;5;28;01mpass\u001b[39;00m\n\u001b[0;32m    598\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mabs\u001b[39m(desired \u001b[38;5;241m-\u001b[39m actual) \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1.5\u001b[39m \u001b[38;5;241m*\u001b[39m \u001b[38;5;241m10.0\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m(\u001b[38;5;241m-\u001b[39mdecimal):\n\u001b[1;32m--> 599\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAssertionError\u001b[39;00m(_build_err_msg())\n",
      "\u001b[1;31mAssertionError\u001b[0m: \nArrays are not almost equal to 0 decimals\n ACTUAL: -517703650\n DESIRED: -285809114.51827204"
     ]
    }
   ],
   "source": [
    "for index, year in enumerate(MTBS_values['years']):\n",
    "    \n",
    "    print('Decommissioning value testing in {}: MTBS: {} TUD/VO: {}'.format(year, MTBS_values['values'][index], Turbine.decommissioning_values[index]))\n",
    "    np.testing.assert_almost_equal(MTBS_values['values'][index],  Turbine.decommissioning_values[index], 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c10b5fd",
   "metadata": {},
   "source": [
    "#####  3. Test values - Foundations and cables\n",
    "##### 3.1 - CAPEX values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "295200d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "MTBS_values = {'years': [2023, 2024, 2025], \n",
    "               'values': [-594632052, -1213049386, -1237310374,]}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "563c08b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "for index, year in enumerate(MTBS_values['years']):\n",
    "    \n",
    "    print('CAPEX value testing in {}: MTBS: {} TUD/VO: {}'.format(year, MTBS_values['values'][index], Foundation.df[Foundation.df.index==year].capex.item()))\n",
    "    np.testing.assert_almost_equal(MTBS_values['values'][index],  Foundation.df[Foundation.df.index==year].capex.item(), 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7267a9c",
   "metadata": {},
   "source": [
    "##### 3.2 - OPEX values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "70c2168a",
   "metadata": {},
   "outputs": [],
   "source": [
    "MTBS_values = {'years': [2026, 2027, 2028, 2029, 2030, 2031, 2032, 2033, 2034, 2035, 2036, 2037, 2038, 2039, 2040, 2041, 2042, 2043, 2044, 2045, 2046, 2047, 2048, 2049, 2050, 2051, 2052],\n",
    "               'values': [-65_919_941, -67_238_340, -68_583_107, -69_954_769, -71_353_864, -72_780_942, -74_236_561, -75_721_292, -77_235_718, -78_780_432, -80_356_041, -81_963_161, -83_602_425, -85_274_473, -86_979_963, -88_719_562, -90_493_953, -92_303_832, -94_149_909, -96_032_907, -97_953_565, -99_912_636, -101_910_889, -103_949_107, -106_028_089, -108_148_651, -2_040_765_041]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8c8752fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "for index, year in enumerate(MTBS_values['years']):\n",
    "    \n",
    "    print('Opex value testing in {}: MTBS: {} TUD/VO: {}'.format(year, MTBS_values['values'][index], Foundation.df[Foundation.df.index==year].opex.item()))\n",
    "    np.testing.assert_almost_equal(MTBS_values['values'][index],  Foundation.df[Foundation.df.index==year].opex.item(), 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "138e8282",
   "metadata": {},
   "source": [
    "##### 3.3 - Decommissioning \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fbb57951",
   "metadata": {},
   "outputs": [],
   "source": [
    "MTBS_values = {'years': [2052],\n",
    "               'values': [-1_930_453_417]} # decommissioning from MTBS, residual from python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f3d0fc9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "for index, year in enumerate(MTBS_values['years']):\n",
    "    \n",
    "    print('Residual value testing in {}: MTBS: {} TUD/VO: {}'.format(year, MTBS_values['values'][index], Foundation.decommissioning_values[-1]))\n",
    "    np.testing.assert_almost_equal(MTBS_values['values'][index],  Foundation.decommissioning_values[-1], 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f042add3",
   "metadata": {},
   "source": [
    "##### 3.4 - Divestment SUM (Foundation & Cables + Turbines)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "639bfb65",
   "metadata": {},
   "outputs": [],
   "source": [
    "MTBS_values = {'years': [2052],\n",
    "               'values': [ 661_760_574 ]} # decommissioning from MTBS\n",
    "\n",
    "wind_energy = [Foundation.divestment_values[-1], Turbine.divestment_values[-1]]\n",
    "\n",
    "for index, year in enumerate(MTBS_values['years']):\n",
    "    \n",
    "    print('Divestment value testing in {}: MTBS: {} TUD/VO: {}'.format(year, MTBS_values['values'][index], sum(wind_energy)))\n",
    "    np.testing.assert_almost_equal(MTBS_values['values'][index],  sum(wind_energy), 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "68ed65c1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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