{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Run EnergyScope with LCA impact scores" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this notebook, we show how to use LCA data in EnergyScope. We use the core model of EnergyScope as an illustrative example.\n", "Before following this tutorial, make sure you have followed the \"Generation of LCA impact scores\" tutorial to generate the .dat and .mod files of LCA parameters and constraints to be used in EnergyScope.\n", "\n", "We show how to:\n", "- easily add the LCA .mod and .dat files to the core version\n", "- run the model\n", "- format the results\n", "- visualise the results using [_mescal_'s](https://mescal.readthedocs.io/en/latest/) visualisation features" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%pip install mescal==1.2.4\n", "%pip install energyscope==2.1.2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Once you have generated your set of LCA metrics, you are ready to run EnergyScope with LCA variables as objective function or constraints." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Import packages" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:12:00.651643Z", "start_time": "2026-02-20T15:11:42.216022Z" } }, "outputs": [], "source": [ "from energyscope.models import core, Model\n", "from energyscope.energyscope import Energyscope\n", "from mescal import Plot\n", "import pandas as pd" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:12:00.678770Z", "start_time": "2026-02-20T15:12:00.670799Z" } }, "outputs": [], "source": [ "INPUT_DATA_FOLDER = 'path/to/your/input/files/' # put the path of your data folder here\n", "LCA_RESULTS_FOLDER = 'path/to/your/lca/results/files/' # put the path of your LCA results folder here\n", "license_uuid = 'xxx' # put your AMPL licence UUID here" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:12:01.490182Z", "start_time": "2026-02-20T15:12:01.388010Z" } }, "outputs": [], "source": [ "lifetime = pd.read_csv(INPUT_DATA_FOLDER+'lifetime.csv')\n", "impact_scores_lca = pd.read_csv(LCA_RESULTS_FOLDER+'impact_scores.csv') # LCA impact scores\n", "impact_scores_direct = pd.read_csv(LCA_RESULTS_FOLDER+'impact_scores_direct_emissions.csv') # Impact scores for direct emissions" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Run EnergyScope" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:12:01.591070Z", "start_time": "2026-02-20T15:12:01.583369Z" } }, "outputs": [], "source": [ "LCA_model = Model([\n", " ('mod', LCA_RESULTS_FOLDER+'objectives_lca.mod'),\n", " # ('mod', LCA_RESULTS_FOLDER+'objectives_lca_direct.mod'),\n", " ('dat', LCA_RESULTS_FOLDER+'techs_lca.dat'),\n", " # ('dat', LCA_RESULTS_FOLDER+'techs_lca_direct.dat'),\n", "])" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:12:01.628294Z", "start_time": "2026-02-20T15:12:01.618387Z" } }, "outputs": [], "source": [ "core = core.__add__(LCA_model) # add the LCA model to the core model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Make sure to replace the license UUID with your own, you can access it directly from the [AMPL portal](https://portal.ampl.com/user/ampl/license/list). If you don't have an account please create one, and favor your academic address to get access to the free academic license." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:12:01.670934Z", "start_time": "2026-02-20T15:12:01.661769Z" } }, "outputs": [], "source": [ "energyscope_lca = Energyscope(\n", " model=core,\n", " solver_options={'solver': 'gurobi','gurobi_options':'outlev=1 NumericFocus=2 method=2'},\n", " modules=['gurobi'],\n", " license_uuid=license_uuid,\n", ")" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:14:55.875561Z", "start_time": "2026-02-20T15:12:01.729642Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Gurobi 11.0.0: Set parameter LogToConsole to value 1\n", " tech:outlev = 1\n", "Set parameter NumericFocus to value 2\n", " alg:numericfocus = 2\n", "Set parameter Method to value 2\n", " alg:method = 2\n", "Set parameter InfUnbdInfo to value 1\n", "Gurobi Optimizer version 11.0.0 build v11.0.0rc2 (mac64[arm] - Darwin 23.5.0 23F79)\n", "\n", "CPU model: Apple M2 Pro\n", "Thread count: 10 physical cores, 10 logical processors, using up to 10 threads\n", "\n", "Optimize a model with 491079 rows, 268733 columns and 1576042 nonzeros\n", "Model fingerprint: 0x489b5254\n", "Coefficient statistics:\n", " Matrix range [1e-06, 7e+04]\n", " Objective range [1e+00, 1e+00]\n", " Bounds range [2e-02, 6e+01]\n", " RHS range [1e+00, 4e+04]\n", "Presolve removed 243247 rows and 128451 columns\n", "Presolve time: 1.11s\n", "Presolved: 247832 rows, 140282 columns, 798471 nonzeros\n", "\n", "Elapsed ordering time = 5s\n", "Ordering time: 5.65s\n", "\n", "Barrier statistics:\n", " Dense cols : 98\n", " AA' NZ : 3.806e+06\n", " Factor NZ : 1.871e+07 (roughly 300 MB of memory)\n", " Factor Ops : 7.223e+09 (less than 1 second per iteration)\n", " Threads : 10\n", "\n", " Objective Residual\n", "Iter Primal Dual Primal Dual Compl Time\n", " 0 1.26214894e+07 -1.08114072e+06 1.99e+05 7.82e-14 1.00e+06 8s\n", " 1 1.35339311e+07 -2.45874867e+06 1.48e+05 8.36e+02 9.01e+05 8s\n", " 2 1.38220425e+07 -4.82323219e+06 1.43e+05 8.19e+02 8.29e+05 9s\n", " 3 1.55994536e+07 -5.80812720e+07 9.43e+04 6.18e+02 6.47e+05 10s\n", " 4 1.69376975e+07 -8.75794573e+07 6.41e+04 2.55e+02 2.99e+05 10s\n", " 5 1.67070071e+07 -9.53004389e+07 4.38e+04 8.43e+01 1.23e+05 11s\n", " 6 1.49631224e+07 -9.21859993e+07 2.77e+04 2.79e+01 5.37e+04 11s\n", " 7 1.24321302e+07 -9.04378015e+07 1.43e+04 1.76e+01 3.09e+04 11s\n", " 8 1.17871098e+07 -8.62747350e+07 1.17e+04 1.15e+01 2.23e+04 12s\n", " 9 9.83264710e+06 -8.06615974e+07 5.15e+03 5.91e+00 1.11e+04 12s\n", " 10 8.27717146e+06 -7.19404442e+07 1.52e+03 2.11e+00 3.83e+03 13s\n", " 11 7.07560975e+06 -4.98458760e+07 5.99e+02 4.49e-01 1.06e+03 13s\n", " 12 4.69555157e+06 -2.83726138e+07 1.19e+02 1.45e-01 3.27e+02 14s\n", " 13 2.73919161e+06 -8.60861758e+06 2.36e+01 3.31e-02 8.11e+01 14s\n", " 14 1.58495883e+06 -5.04289313e+06 9.81e+00 1.89e-02 4.50e+01 15s\n", " 15 1.15002761e+06 -3.73458586e+06 5.92e+00 1.38e-02 3.26e+01 15s\n", " 16 1.00327382e+06 -2.27155989e+06 4.78e+00 8.30e-03 2.07e+01 15s\n", " 17 6.05300251e+05 -1.23203779e+06 2.28e+00 4.45e-03 1.13e+01 16s\n", " 18 4.64584361e+05 -6.32348880e+05 1.58e+00 2.30e-03 6.34e+00 16s\n", " 19 3.55194859e+05 -5.01622560e+05 1.08e+00 1.88e-03 5.02e+00 17s\n", " 20 2.94192951e+05 -3.71479342e+05 7.98e-01 1.44e-03 3.88e+00 17s\n", " 21 2.02704421e+05 -3.00907689e+05 4.08e-01 1.18e-03 3.00e+00 17s\n", " 22 1.67462697e+05 -1.68280621e+05 2.63e-01 6.95e-04 1.92e+00 18s\n", " 23 1.16017225e+05 -7.11479718e+04 6.35e-02 3.46e-04 1.04e+00 18s\n", " 24 1.05167669e+05 -3.62786352e+04 2.30e-02 2.23e-04 7.56e-01 18s\n", " 25 1.01090645e+05 -2.44646310e+04 1.27e-02 1.82e-04 6.60e-01 19s\n", " 26 9.11274044e+04 -9.36211225e+03 1.07e-02 1.30e-04 5.18e-01 19s\n", " 27 8.07349691e+04 2.69477488e+03 8.50e-03 9.13e-05 3.95e-01 20s\n", " 28 7.16514186e+04 1.64619174e+04 6.44e-03 5.70e-05 2.76e-01 20s\n", " 29 6.10425774e+04 2.63738488e+04 3.78e-03 3.10e-05 1.74e-01 21s\n", " 30 5.53785573e+04 3.41295145e+04 2.51e-03 1.81e-05 1.03e-01 21s\n", " 31 5.16638429e+04 3.70952997e+04 1.75e-03 1.40e-05 7.05e-02 21s\n", " 32 4.97160337e+04 3.87140228e+04 1.34e-03 1.14e-05 5.27e-02 22s\n", " 33 4.85231204e+04 3.98536285e+04 1.10e-03 8.79e-06 4.07e-02 22s\n", " 34 4.79416363e+04 4.02236940e+04 9.73e-04 7.78e-06 3.61e-02 22s\n", " 35 4.77836802e+04 4.05966990e+04 9.42e-04 6.74e-06 3.31e-02 23s\n", " 36 4.74617778e+04 4.10556830e+04 8.75e-04 5.49e-06 2.89e-02 23s\n", " 37 4.65818999e+04 4.14538277e+04 7.01e-04 4.24e-06 2.30e-02 23s\n", " 38 4.60620737e+04 4.16875188e+04 6.00e-04 3.52e-06 1.95e-02 24s\n", " 39 4.56003673e+04 4.20036758e+04 5.14e-04 2.62e-06 1.58e-02 24s\n", " 40 4.51788339e+04 4.22294120e+04 4.33e-04 1.99e-06 1.28e-02 25s\n", " 41 4.49533642e+04 4.23101110e+04 3.89e-04 1.77e-06 1.15e-02 25s\n", " 42 4.45119295e+04 4.24128387e+04 3.06e-04 1.48e-06 9.21e-03 26s\n", " 43 4.40936860e+04 4.25302794e+04 2.28e-04 1.12e-06 6.88e-03 26s\n", " 44 4.37293726e+04 4.26569933e+04 1.57e-04 7.37e-07 4.67e-03 27s\n", " 45 4.35295399e+04 4.27327619e+04 1.18e-04 5.05e-07 3.42e-03 27s\n", " 46 4.32563072e+04 4.27846262e+04 6.58e-05 3.32e-07 2.04e-03 28s\n", " 47 4.31874802e+04 4.28275410e+04 5.29e-05 1.93e-07 1.50e-03 29s\n", " 48 4.31408174e+04 4.28390582e+04 4.43e-05 1.53e-07 1.24e-03 29s\n", " 49 4.31149968e+04 4.28486203e+04 3.96e-05 1.21e-07 1.08e-03 29s\n", " 50 4.30727773e+04 4.28537318e+04 3.20e-05 1.04e-07 8.91e-04 30s\n", " 51 4.30174189e+04 4.28618969e+04 2.21e-05 7.55e-08 6.30e-04 31s\n", " 52 4.29811217e+04 4.28680043e+04 1.63e-05 5.30e-08 4.55e-04 33s\n", " 53 4.29621596e+04 4.28738129e+04 1.31e-05 3.13e-08 3.47e-04 33s\n", " 54 4.29403716e+04 4.28761294e+04 9.32e-06 2.40e-08 2.52e-04 34s\n", " 55 4.29298139e+04 4.28773018e+04 7.62e-06 1.94e-08 2.05e-04 35s\n", " 56 4.29251256e+04 4.28778535e+04 6.80e-06 1.77e-08 1.84e-04 36s\n", " 57 4.29217064e+04 4.28786685e+04 6.23e-06 1.46e-08 1.67e-04 37s\n", " 58 4.29166251e+04 4.28787407e+04 5.43e-06 1.42e-08 1.47e-04 38s\n", " 59 4.29109658e+04 4.28801101e+04 4.46e-06 1.01e-08 1.19e-04 39s\n", " 60 4.29047023e+04 4.28808103e+04 3.40e-06 8.05e-09 9.18e-05 40s\n", " 61 4.29007751e+04 4.28810904e+04 2.77e-06 7.19e-09 7.57e-05 42s\n", " 62 4.28978158e+04 4.28815872e+04 2.28e-06 5.68e-09 6.22e-05 43s\n", " 63 4.28958179e+04 4.28817601e+04 1.96e-06 5.01e-09 5.38e-05 44s\n", " 64 4.28949524e+04 4.28819003e+04 1.81e-06 4.68e-09 5.00e-05 44s\n", " 65 4.28904490e+04 4.28823731e+04 1.07e-06 3.38e-09 3.10e-05 45s\n", " 66 4.28879606e+04 4.28828284e+04 6.59e-07 2.12e-09 1.97e-05 46s\n", " 67 4.28871286e+04 4.28830120e+04 5.26e-07 1.62e-09 1.57e-05 47s\n", " 68 4.28867831e+04 4.28830540e+04 4.69e-07 1.52e-09 1.43e-05 48s\n", " 69 4.28863795e+04 4.28832572e+04 4.05e-07 1.11e-09 1.19e-05 49s\n", " 70 4.28860712e+04 4.28833410e+04 3.54e-07 9.48e-10 1.04e-05 50s\n", " 71 4.28856095e+04 4.28834629e+04 2.78e-07 7.07e-10 8.14e-06 50s\n", " 72 4.28853010e+04 4.28835296e+04 2.31e-07 5.67e-10 6.71e-06 51s\n", " 73 4.28850324e+04 4.28835725e+04 1.88e-07 4.87e-10 5.53e-06 52s\n", " 74 4.28847724e+04 4.28836136e+04 1.47e-07 4.03e-10 4.40e-06 52s\n", " 75 4.28845461e+04 4.28837236e+04 1.11e-07 1.44e-10 3.08e-06 53s\n", " 76 4.28843701e+04 4.28837595e+04 8.38e-08 8.27e-11 2.28e-06 54s\n", " 77 4.28842334e+04 4.28837720e+04 6.21e-08 6.53e-11 1.72e-06 55s\n", " 78 4.28841378e+04 4.28837761e+04 4.78e-08 5.88e-11 1.35e-06 56s\n", " 79 4.28840293e+04 4.28838001e+04 3.11e-08 1.36e-11 8.49e-07 56s\n", " 80 4.28838919e+04 4.28838121e+04 1.02e-08 1.14e-12 2.95e-07 57s\n", " 81 4.28838632e+04 4.28838158e+04 6.14e-09 1.56e-12 1.75e-07 57s\n", " 82 4.28838236e+04 4.28838169e+04 6.79e-09 2.39e-12 2.49e-08 57s\n", " 83 4.28838184e+04 4.28838176e+04 1.00e-09 3.98e-12 2.80e-09 58s\n", " 84 4.28838178e+04 4.28838177e+04 8.06e-10 7.28e-12 2.82e-10 58s\n", "\n", "Barrier solved model in 84 iterations and 57.89 seconds (74.59 work units)\n", "Optimal objective 4.28838178e+04\n", "\n", "Crossover log...\n", "\n", " 53749 DPushes remaining with DInf 0.0000000e+00 58s\n", " 5830 DPushes remaining with DInf 0.0000000e+00 60s\n", " 0 DPushes remaining with DInf 0.0000000e+00 65s\n", "\n", " 3062 PPushes remaining with PInf 2.7143602e-02 65s\n", " 2641 PPushes remaining with PInf 1.5617888e-02 65s\n", " 0 PPushes remaining with PInf 0.0000000e+00 66s\n", "\n", " Push phase complete: Pinf 0.0000000e+00, Dinf 8.0106546e+01 66s\n", "\n", "Iteration Objective Primal Inf. Dual Inf. Time\n", " 39744 4.2883818e+04 0.000000e+00 8.010655e+01 66s\n", "Extra simplex iterations after uncrush: 1\n", " 39962 4.2883818e+04 0.000000e+00 0.000000e+00 67s\n", "\n", "Solved in 39962 iterations and 67.15 seconds (86.38 work units)\n", "Optimal objective 4.288381774e+04\n", "\bGurobi 11.0.0: optimal solution; objective 42883.81774\n", "39962 simplex iteration(s)\n", "84 barrier iteration(s)\n" ] } ], "source": [ "results_tc = energyscope_lca.calc()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:18:05.809261Z", "start_time": "2026-02-20T15:18:05.789832Z" } }, "outputs": [ { "data": { "text/html": [ "
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TotalLCIARun
TTEQ1480.6001330
TTHH1137.1428740
\n", "
" ], "text/plain": [ " TotalLCIA Run\n", "TTEQ 1480.600133 0\n", "TTHH 1137.142874 0" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "results_tc.variables['TotalLCIA']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You might want to change the objective function with an environmental objective, such as the life-cycle greenhouse gas emissions, or the total damage on human health/ecosystem quality. Alternatively, you can also add a constraint on the total life-cycle impact, to be lower than a certain threshold." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:19:22.795844Z", "start_time": "2026-02-20T15:19:22.788504Z" } }, "outputs": [], "source": [ "# To change the objective function\n", "# energyscope_lca.es_model.eval(\"\"\"\n", "# drop obj;\n", "# minimize new_obj: TotalLCIA_TTHH;\n", "# \"\"\")" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:20:01.704945Z", "start_time": "2026-02-20T15:20:01.694141Z" } }, "outputs": [], "source": [ "# To add upper limits on environmental impacts\n", "reduction_target = 0.5 # for instance, 50% reduction target of damages\n", "scenario_file_path = LCA_RESULTS_FOLDER + 'scenario.dat'\n", "with open(scenario_file_path, 'w', encoding='utf-8', newline='\\n') as f:\n", " f.write(f\"let limit_lcia['TTHH'] := {reduction_target} * {results_tc.variables['TotalLCIA'].loc['TTHH'].iloc[0]};\\n\")\n", " f.write(f\"let limit_lcia['TTEQ'] := {reduction_target} * {results_tc.variables['TotalLCIA'].loc['TTEQ'].iloc[0]};\\n\")" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:21:36.040537Z", "start_time": "2026-02-20T15:21:36.032563Z" } }, "outputs": [], "source": [ "core = core.__add__(Model([('dat', scenario_file_path)])) # add the scenario file to the core model" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:25:26.999072Z", "start_time": "2026-02-20T15:25:26.925190Z" } }, "outputs": [], "source": [ "energyscope_lca = Energyscope(\n", " model=core,\n", " solver_options={'solver': 'gurobi', 'gurobi_options':'outlev=1 NumericFocus=2 method=2'},\n", " modules=['gurobi'],\n", " license_uuid=license_uuid,\n", ")" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:28:36.227754Z", "start_time": "2026-02-20T15:25:28.108283Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Gurobi 11.0.0: Set parameter LogToConsole to value 1\n", " tech:outlev = 1\n", "Set parameter NumericFocus to value 2\n", " alg:numericfocus = 2\n", "Set parameter Method to value 2\n", " alg:method = 2\n", "Set parameter InfUnbdInfo to value 1\n", "Gurobi Optimizer version 11.0.0 build v11.0.0rc2 (mac64[arm] - Darwin 23.5.0 23F79)\n", "\n", "CPU model: Apple M2 Pro\n", "Thread count: 10 physical cores, 10 logical processors, using up to 10 threads\n", "\n", "Optimize a model with 491079 rows, 268733 columns and 1576042 nonzeros\n", "Model fingerprint: 0xdcb6a7e9\n", "Coefficient statistics:\n", " Matrix range [1e-06, 7e+04]\n", " Objective range [1e+00, 1e+00]\n", " Bounds range [2e-02, 7e+02]\n", " RHS range [1e+00, 4e+04]\n", "Presolve removed 243244 rows and 128162 columns\n", "Presolve time: 1.09s\n", "Presolved: 247835 rows, 140571 columns, 825165 nonzeros\n", "\n", "Ordering time: 3.75s\n", "\n", "Barrier statistics:\n", " Dense cols : 98\n", " AA' NZ : 3.844e+06\n", " Factor NZ : 1.872e+07 (roughly 300 MB of memory)\n", " Factor Ops : 7.224e+09 (less than 1 second per iteration)\n", " Threads : 10\n", "\n", " Objective Residual\n", "Iter Primal Dual Primal Dual Compl Time\n", " 0 2.53843025e+06 -2.99215692e+05 3.27e+06 3.55e-14 1.00e+06 6s\n", " 1 3.04076457e+06 -7.18144107e+05 2.82e+06 8.33e+02 9.89e+05 6s\n", " 2 3.18107906e+06 -3.60235627e+06 2.48e+06 6.92e+02 7.95e+05 6s\n", " 3 4.56493266e+06 -1.18222818e+07 1.98e+06 5.19e+02 6.15e+05 7s\n", " 4 5.54382554e+06 -2.08075497e+07 9.34e+05 3.58e+02 4.06e+05 7s\n", " 5 5.47355389e+06 -3.09204199e+07 4.47e+05 1.57e+02 1.83e+05 8s\n", " 6 4.57233413e+06 -3.60665673e+07 2.64e+05 8.59e+01 1.02e+05 8s\n", " 7 3.83989050e+06 -4.28818121e+07 1.81e+05 5.05e+01 6.35e+04 8s\n", " 8 2.96318349e+06 -4.36282973e+07 1.14e+05 4.50e+01 5.32e+04 9s\n", " 9 2.36873470e+06 -5.37880547e+07 7.84e+04 2.54e+01 3.30e+04 9s\n", " 10 1.93445861e+06 -5.87250366e+07 5.74e+04 1.93e+01 2.50e+04 9s\n", " 11 1.80936991e+06 -5.98724256e+07 5.11e+04 1.58e+01 2.03e+04 9s\n", " 12 1.60562656e+06 -6.31849344e+07 3.95e+04 1.06e+01 1.49e+04 10s\n", " 13 1.47890144e+06 -5.97169202e+07 2.86e+04 7.98e+00 1.10e+04 10s\n", " 14 1.54082883e+06 -5.44646230e+07 2.31e+04 6.59e+00 8.84e+03 11s\n", " 15 1.70192735e+06 -5.14513691e+07 1.84e+04 6.16e+00 7.95e+03 11s\n", " 16 2.64073408e+06 -3.61262867e+07 9.28e+03 3.60e+00 4.69e+03 12s\n", " 17 3.22595919e+06 -2.47893877e+07 4.72e+03 2.06e+00 2.75e+03 12s\n", " 18 3.36953008e+06 -1.90952308e+07 3.12e+03 1.20e+00 1.64e+03 13s\n", " 19 3.46994899e+06 -1.77935448e+07 1.79e+03 1.05e+00 1.41e+03 13s\n", " 20 3.48520576e+06 -1.13073450e+07 1.33e+03 4.62e-01 6.56e+02 13s\n", " 21 3.30532899e+06 -5.78248305e+06 5.72e+02 1.72e-01 2.52e+02 13s\n", " 22 2.86627597e+06 -2.39424076e+06 2.40e+02 5.81e-02 9.02e+01 14s\n", " 23 2.00349506e+06 -1.41483522e+06 1.09e+02 3.27e-02 4.95e+01 14s\n", " 24 1.17009444e+06 -5.01615907e+05 3.23e+01 1.00e-02 1.69e+01 14s\n", " 25 6.39351203e+05 -2.74630866e+05 1.29e+01 5.12e-03 8.62e+00 15s\n", " 26 3.91972204e+05 -1.93791942e+05 6.91e+00 3.08e-03 5.15e+00 15s\n", " 27 3.63207139e+05 -1.25667056e+05 6.39e+00 1.74e-03 3.45e+00 15s\n", " 28 3.59261701e+05 -1.05506447e+05 6.20e+00 1.48e-03 3.11e+00 16s\n", " 29 2.51020289e+05 -8.13710586e+04 3.88e+00 1.17e-03 2.28e+00 16s\n", " 30 2.01903969e+05 -6.02203511e+04 3.01e+00 9.11e-04 1.77e+00 16s\n", " 31 1.76234214e+05 -3.68403815e+04 2.42e+00 7.25e-04 1.42e+00 17s\n", " 32 1.61180575e+05 -4.70450996e+03 1.77e+00 5.16e-04 1.06e+00 17s\n", " 33 1.47262965e+05 8.09243903e+03 1.46e+00 4.32e-04 8.83e-01 18s\n", " 34 1.26371833e+05 2.26577691e+04 9.82e-01 3.35e-04 6.64e-01 18s\n", " 35 1.19276413e+05 3.71262364e+04 8.59e-01 2.38e-04 5.05e-01 19s\n", " 36 1.10073313e+05 4.55089831e+04 7.10e-01 1.77e-04 3.94e-01 19s\n", " 37 1.01343133e+05 4.94201905e+04 5.83e-01 1.42e-04 3.25e-01 20s\n", " 38 9.34773402e+04 5.14798974e+04 4.84e-01 1.20e-04 2.77e-01 21s\n", " 39 8.92751601e+04 5.27248989e+04 4.31e-01 1.10e-04 2.48e-01 22s\n", " 40 8.35868864e+04 5.34854887e+04 3.44e-01 9.65e-05 2.12e-01 22s\n", " 41 7.83983589e+04 5.51154446e+04 2.56e-01 7.37e-05 1.63e-01 23s\n", " 42 7.46263093e+04 5.65402182e+04 2.00e-01 5.31e-05 1.22e-01 23s\n", " 43 7.09943711e+04 5.74514802e+04 1.47e-01 3.84e-05 9.00e-02 24s\n", " 44 6.97634736e+04 5.79259480e+04 1.30e-01 3.16e-05 7.67e-02 25s\n", " 45 6.87002534e+04 5.82711939e+04 1.16e-01 2.63e-05 6.61e-02 25s\n", " 46 6.76451941e+04 5.85570027e+04 1.02e-01 2.10e-05 5.56e-02 26s\n", " 47 6.70852871e+04 5.87171482e+04 9.53e-02 1.79e-05 4.98e-02 26s\n", " 48 6.68973058e+04 5.87808962e+04 9.28e-02 1.68e-05 4.77e-02 27s\n", " 49 6.57836808e+04 5.89188917e+04 7.89e-02 1.41e-05 4.04e-02 27s\n", " 50 6.46067235e+04 5.90295130e+04 6.41e-02 1.19e-05 3.34e-02 28s\n", " 51 6.35207274e+04 5.91090125e+04 5.03e-02 1.03e-05 2.73e-02 28s\n", " 52 6.28148607e+04 5.92760786e+04 4.06e-02 7.10e-06 2.06e-02 29s\n", " 53 6.18438911e+04 5.93640618e+04 2.72e-02 5.54e-06 1.50e-02 29s\n", " 54 6.12747598e+04 5.94494550e+04 1.95e-02 4.25e-06 1.12e-02 30s\n", " 55 6.07002614e+04 5.95266244e+04 1.15e-02 3.20e-06 7.63e-03 31s\n", " 56 6.05388849e+04 5.95731258e+04 9.36e-03 2.54e-06 6.15e-03 31s\n", " 57 6.03611503e+04 5.96082897e+04 6.94e-03 2.07e-06 4.86e-03 32s\n", " 58 6.02612497e+04 5.96747256e+04 5.51e-03 1.28e-06 3.43e-03 32s\n", " 59 6.02110801e+04 5.97017132e+04 4.76e-03 1.07e-06 2.92e-03 33s\n", " 60 6.01656906e+04 5.97281576e+04 4.15e-03 8.43e-07 2.43e-03 33s\n", " 61 6.01295901e+04 5.97474492e+04 3.65e-03 6.75e-07 2.05e-03 34s\n", " 62 6.00592385e+04 5.97539844e+04 2.68e-03 6.21e-07 1.70e-03 34s\n", " 63 6.00274421e+04 5.97714957e+04 2.25e-03 4.92e-07 1.39e-03 35s\n", " 64 6.00063199e+04 5.97832268e+04 1.96e-03 4.04e-07 1.18e-03 35s\n", " 65 5.99869217e+04 5.97951690e+04 1.70e-03 3.28e-07 9.91e-04 36s\n", " 66 5.99728583e+04 5.98009488e+04 1.51e-03 2.91e-07 8.82e-04 37s\n", " 67 5.99554247e+04 5.98085292e+04 1.29e-03 2.38e-07 7.40e-04 37s\n", " 68 5.99346101e+04 5.98180026e+04 1.01e-03 1.79e-07 5.74e-04 37s\n", " 69 5.99303783e+04 5.98212785e+04 9.52e-04 1.59e-07 5.29e-04 38s\n", " 70 5.99240814e+04 5.98273948e+04 8.73e-04 1.24e-07 4.54e-04 39s\n", " 71 5.99089482e+04 5.98292787e+04 6.79e-04 1.14e-07 3.80e-04 39s\n", " 72 5.99062123e+04 5.98312079e+04 6.48e-04 1.01e-07 3.52e-04 40s\n", " 73 5.98943187e+04 5.98321969e+04 5.07e-04 9.46e-08 2.97e-04 41s\n", " 74 5.98856417e+04 5.98347163e+04 4.05e-04 7.83e-08 2.42e-04 41s\n", " 75 5.98818806e+04 5.98376863e+04 3.59e-04 6.16e-08 2.05e-04 42s\n", " 76 5.98727580e+04 5.98398429e+04 2.50e-04 5.00e-08 1.54e-04 43s\n", " 77 5.98701402e+04 5.98411146e+04 2.19e-04 4.34e-08 1.35e-04 43s\n", " 78 5.98682990e+04 5.98425256e+04 1.98e-04 3.58e-08 1.17e-04 44s\n", " 79 5.98627424e+04 5.98440672e+04 1.32e-04 2.85e-08 8.58e-05 45s\n", " 80 5.98591239e+04 5.98456393e+04 9.12e-05 2.12e-08 6.18e-05 46s\n", " 81 5.98584576e+04 5.98460685e+04 8.42e-05 1.91e-08 5.65e-05 47s\n", " 82 5.98577825e+04 5.98474989e+04 7.70e-05 1.28e-08 4.50e-05 49s\n", " 83 5.98533242e+04 5.98488364e+04 2.84e-05 6.45e-09 1.99e-05 51s\n", " 84 5.98518840e+04 5.98493358e+04 1.41e-05 4.31e-09 1.16e-05 52s\n", " 85 5.98516221e+04 5.98493826e+04 1.15e-05 4.10e-09 1.03e-05 53s\n", " 86 5.98514260e+04 5.98495159e+04 9.66e-06 3.56e-09 8.81e-06 54s\n", " 87 5.98513880e+04 5.98496263e+04 9.30e-06 3.12e-09 8.04e-06 55s\n", " 88 5.98512869e+04 5.98496390e+04 8.33e-06 3.07e-09 7.59e-06 55s\n", " 89 5.98512330e+04 5.98496906e+04 7.80e-06 2.84e-09 7.09e-06 56s\n", " 90 5.98511585e+04 5.98498498e+04 7.05e-06 2.18e-09 5.90e-06 57s\n", " 91 5.98510341e+04 5.98499731e+04 5.81e-06 1.68e-09 4.73e-06 57s\n", " 92 5.98509843e+04 5.98499917e+04 5.34e-06 1.61e-09 4.45e-06 58s\n", " 93 5.98509258e+04 5.98500172e+04 4.78e-06 1.51e-09 4.09e-06 59s\n", " 94 5.98506864e+04 5.98500758e+04 2.44e-06 1.28e-09 2.88e-06 59s\n", " 95 5.98505216e+04 5.98502473e+04 8.96e-07 6.20e-10 1.31e-06 60s\n", " 96 5.98504547e+04 5.98503186e+04 3.22e-07 3.45e-10 6.69e-07 62s\n", " 97 5.98504496e+04 5.98503280e+04 2.82e-07 3.09e-10 5.98e-07 62s\n", " 98 5.98504415e+04 5.98503416e+04 2.19e-07 2.58e-10 4.93e-07 63s\n", " 99 5.98504310e+04 5.98503926e+04 1.42e-07 5.76e-11 1.69e-07 63s\n", " 100 5.98504127e+04 5.98504074e+04 2.12e-08 6.47e-12 2.26e-08 64s\n", " 101 5.98504097e+04 5.98504091e+04 2.00e-09 8.79e-13 2.38e-09 64s\n", " 102 5.98504094e+04 5.98504093e+04 2.58e-10 2.13e-12 2.39e-10 65s\n", "\n", "Barrier solved model in 102 iterations and 65.29 seconds (92.79 work units)\n", "Optimal objective 5.98504094e+04\n", "\n", "Crossover log...\n", "\n", " 42281 DPushes remaining with DInf 2.6466504e-02 66s\n", " 2272 DPushes remaining with DInf 0.0000000e+00 70s\n", " 0 DPushes remaining with DInf 0.0000000e+00 75s\n", "\n", " 3459 PPushes remaining with PInf 3.2086930e-05 75s\n", " 2433 PPushes remaining with PInf 1.8013505e-03 75s\n", " 0 PPushes remaining with PInf 0.0000000e+00 76s\n", "\n", " Push phase complete: Pinf 0.0000000e+00, Dinf 6.0393358e-01 76s\n", "\n", "Iteration Objective Primal Inf. Dual Inf. Time\n", " 27352 5.9850411e+04 0.000000e+00 6.039336e-01 76s\n", " 27374 5.9850409e+04 0.000000e+00 0.000000e+00 76s\n", "\n", "Solved in 27374 iterations and 76.18 seconds (109.67 work units)\n", "Optimal objective 5.985040933e+04\n", "\bGurobi 11.0.0: optimal solution; objective 59850.40933\n", "27374 simplex iteration(s)\n", "102 barrier iteration(s)\n" ] } ], "source": [ "results_lca = energyscope_lca.calc()" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:28:36.893633Z", "start_time": "2026-02-20T15:28:36.873267Z" } }, "outputs": [ { "data": { "text/html": [ "
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TotalLCIARun
TTEQ740.3000670
TTHH423.5840770
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" ], "text/plain": [ " TotalLCIA Run\n", "TTEQ 740.300067 0\n", "TTHH 423.584077 0" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "results_lca.variables['TotalLCIA']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Formatting the results" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:29:52.769168Z", "start_time": "2026-02-20T15:29:52.755788Z" } }, "outputs": [], "source": [ "results = results_lca # choose among results_tc and results_lca" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:29:53.757002Z", "start_time": "2026-02-20T15:29:53.674711Z" } }, "outputs": [], "source": [ "df_annual_prod = pd.merge(results.variables['F_t'].reset_index(), results.parameters['t_op'].reset_index(), left_on=['index1', 'index2'], right_on=['index0', 'index1'], suffixes=('', '_'))\n", "df_annual_prod['Annual_Prod'] = df_annual_prod['F_t'] * df_annual_prod['t_op']\n", "df_annual_prod = df_annual_prod.groupby(['index0', 'Run'])['Annual_Prod'].sum().reset_index()\n", "df_installed_cap = results.variables['F'].reset_index()" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:29:54.277639Z", "start_time": "2026-02-20T15:29:54.265039Z" } }, "outputs": [], "source": [ "df_annual_res = df_annual_prod[df_annual_prod.index0.isin(list(results.sets['RESOURCES'].RESOURCES))].rename(columns={'index0':'index', 'Annual_Prod':'Annual_Res'})\n", "df_annual_prod = df_annual_prod[~df_annual_prod.index0.isin(list(results.sets['RESOURCES'].RESOURCES))].rename(columns={'index0':'index'})" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:29:54.847841Z", "start_time": "2026-02-20T15:29:54.812210Z" } }, "outputs": [], "source": [ "esm_results_tech = pd.merge(\n", " df_annual_prod,\n", " df_installed_cap,\n", " on=['index', 'Run']\n", ").rename(columns={'index':'Name', 'Annual_Prod': 'Production', 'F': 'Capacity'})\n", "esm_results_res = df_annual_res.rename(columns={'index': 'Name', 'Annual_Res': 'Import'})" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:29:55.391716Z", "start_time": "2026-02-20T15:29:55.375274Z" } }, "outputs": [ { "data": { "text/html": [ "
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NameRunProductionCapacity
2ATM_CCS0249.8194761.642478
4BEV_BATT00.00000091.160423
10BOAT_FREIGHT_NG0966.90855830.521103
14BUS_COACH_HYDIESEL0551.3382406.381230
15CAR_BEV02756.691201191.436889
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" ], "text/plain": [ " Name Run Production Capacity\n", "2 ATM_CCS 0 249.819476 1.642478\n", "4 BEV_BATT 0 0.000000 91.160423\n", "10 BOAT_FREIGHT_NG 0 966.908558 30.521103\n", "14 BUS_COACH_HYDIESEL 0 551.338240 6.381230\n", "15 CAR_BEV 0 2756.691201 191.436889" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "esm_results_tech = esm_results_tech[esm_results_tech.Capacity != 0]\n", "esm_results_tech.head()" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:29:55.624055Z", "start_time": "2026-02-20T15:29:55.606652Z" } }, "outputs": [ { "data": { "text/html": [ "
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NameRunImport
7BIODIESEL0110.267648
29CO2_ATM0249.819476
31CO2_EMISSIONS0435.516977
64ELEC_EXPORT0671.424283
76H2_RE06180.293383
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" ], "text/plain": [ " Name Run Import\n", "7 BIODIESEL 0 110.267648\n", "29 CO2_ATM 0 249.819476\n", "31 CO2_EMISSIONS 0 435.516977\n", "64 ELEC_EXPORT 0 671.424283\n", "76 H2_RE 0 6180.293383" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "esm_results_res = esm_results_res[esm_results_res.Import != 0]\n", "esm_results_res.head()" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:29:56.603858Z", "start_time": "2026-02-20T15:29:56.590135Z" } }, "outputs": [], "source": [ "esm_results_tech.to_csv(LCA_RESULTS_FOLDER+'esm_results_tech.csv', index=False)\n", "esm_results_res.to_csv(LCA_RESULTS_FOLDER+'esm_results_res.csv', index=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Visualise the results" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:41:13.172101Z", "start_time": "2026-02-20T15:41:13.163264Z" } }, "outputs": [], "source": [ "plot = Plot(\n", " df_impact_scores=impact_scores_lca,\n", " esm_results_tech=esm_results_tech[~esm_results_tech.Name.isin(['ATM_CCS'])], # negative impacts are not displayed in the following plots\n", " esm_results_res=esm_results_res,\n", " lifetime=lifetime,\n", ")" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "ExecuteTime": { "end_time": "2026-02-20T15:41:14.286493Z", "start_time": "2026-02-20T15:41:14.126058Z" } }, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "customdata": [ [ "95.21 %" ], [ "95.22 %" ] ], "hovertemplate": "
Impact category: %{y}
Normalized impacts: %{customdata}
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Impact category: %{y}
Normalized impacts: %{customdata}
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"metadata": {}, "source": [ "Due to IAM projections (in the present case, scenario SSP2-RCP26 run in TIAM-UCL) in the LCA database, some important changes occur in LCA datasets. For instance, diesel production has switched to biodiesel (from used cooking oil with CCS). Consequently, CO2 emissions from diesel combustion are biogenic (i.e., their characterization factor is 0) and the impact of TRUCK_DIESEL mostly comes from its construction." ] } ], "metadata": { "colab": { "provenance": [ { "file_id": "1iXiT1Y7Ld9Cy9BVn8DyUan3JyaPru8sB", "timestamp": 1760451064422 } ] }, "kernelspec": { "display_name": ".venv", "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": "3.11.5" } }, "nbformat": 4, "nbformat_minor": 0 }