diff --git a/docs/source/examples/constraint_tutorial.ipynb b/docs/source/examples/constraint_tutorial.ipynb new file mode 100644 index 0000000..8809ce3 --- /dev/null +++ b/docs/source/examples/constraint_tutorial.ipynb @@ -0,0 +1,670 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/samgdotson/osier/env-instructions?labpath=docs%2Fsource%2Fexamples%2Fconstraint_tutorial.ipynb)\n", + "\n", + "# Constraint Tutorial\n", + "\n", + "In this tutorial, we will use `osier` to optimize the capacity for a test energy system using \n", + "`osier`'s `CapacityExpansion` model and demonstrate converting an objective into a constraint.\n", + "\n", + "\n", + "**Important Caveat**\n", + "\n", + "For simplicity and the sake of time, this notebook specifies a certain number of generations before the model terminates. Therefore it is unlikely that the capacity expansion models shown in this notebook are fully converged. These results should be used for instructional purposes only!" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Solver set: cbc\n" + ] + } + ], + "source": [ + "# basic imports\n", + "import pandas as pd \n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from unyt import kW, minute, hour, day, MW\n", + "import sys\n", + "\n", + "# osier imports\n", + "from osier import CapacityExpansion\n", + "import osier.tech_library as lib\n", + "\n", + "# pymoo imports\n", + "from pymoo.algorithms.moo.nsga2 import NSGA2\n", + "from pymoo.optimize import minimize\n", + "\n", + "\n", + "# set the solver based on operating system -- assumes glpk or cbc is installed.\n", + "if \"win32\" in sys.platform:\n", + " solver = 'glpk'\n", + "elif \"linux\" in sys.platform:\n", + " solver = \"cbc\"\n", + "else:\n", + " solver = \"cbc\"\n", + "\n", + "print(f\"Solver set: {solver}\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As before, `osier` needs two fundamental things in order to run the model\n", + "\n", + "1. A technology set\n", + "2. A net demand profile\n", + "\n", + "Let's create both of these, first. This time, we'll also create a dummy \"wind\" profile and a wind technology to use in the latter two examples.\n", + "We'll also borrow some code from the dispatch tutorial.\n", + "\n", + "## Creating the demand profile" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "n_hours = 24 # hours per day\n", + "n_days = 2 # days to model\n", + "N = n_hours*n_days # total number of time steps\n", + "phase_shift = 0 # horizontal shift [radians]\n", + "base_shift = 2 # vertical shift [units of demand]\n", + "hours = np.linspace(0,N,N)\n", + "total_demand = 185 # [MWh], sets the total demand [units of energy]\n", + "\n", + "demand = (np.sin((hours*np.pi/n_hours*2+phase_shift))*-1+np.ones(N)*(base_shift+1))\n", + "\n", + "np.random.seed(1234) # sets the seed for repeatability\n", + "\n", + "noise = np.random.random(N)\n", + "demand += noise\n", + "\n", + "demand = demand/demand.sum() * total_demand # rescale\n", + "\n", + "with plt.style.context(\"dark_background\"):\n", + " plt.plot(hours, demand, color='cyan')\n", + " plt.ylabel('Demand [MW]')\n", + " plt.xlabel('Time [hr]')\n", + " plt.grid(alpha=0.2)\n", + " plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Creating the \"wind\" profile\n", + "\n", + "Wind speeds follow a Weibull distribution \n", + "\n", + "$f(v) = \\left(\\frac{k}{\\lambda}\\right)\\left(\\frac{v}{\\lambda}\\right)^{k-1}e^{-\\left(\\frac{v}{\\lambda}\\right)^k}$\n", + "\n", + "Where $v$ is our random variable (velocity)." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "np.random.seed(123)\n", + "shape_factor = 2.5\n", + "wind_speed = np.random.weibull(a=shape_factor,size=N)\n", + "\n", + "with plt.style.context('dark_background'):\n", + " plt.plot(wind_speed, color='lime')\n", + " plt.grid(alpha=0.2)\n", + " plt.ylabel('Demand [MW]')\n", + " plt.xlabel('Time [hr]')\n", + " plt.show()\n", + " " + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`osier.CapacityExpansion` will normalize the wind and solar profiles and rescale the maximum values to the rated capacity of the installed technology (for each \"individual\" portfolio tested). Just for fun, let's plot the \"net demand\" if this wind speed were the true value.\n", + "\n", + "Also note that the weibull distribution is related to wind *speed*, not energy production. For simplicity, we will assume they're equal." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "with plt.style.context('dark_background'):\n", + " plt.plot(hours, demand-wind_speed, color='white', linestyle='--', label='Net Demand')\n", + " plt.plot(hours, demand, color='cyan', label='Demand')\n", + " plt.plot(hours, wind_speed, color='lime', label='Wind')\n", + " plt.grid(alpha=0.2)\n", + " plt.ylabel('Demand [MW]')\n", + " plt.xlabel('Time [hr]')\n", + " plt.legend()\n", + " plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Creating the Technology Mix\n", + "\n", + "Let's try to meet demand with a properly sized wind turbine and storage combination." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[WindTurbine: 0.0 MW,\n", + " NaturalGas_Conv: 8375.1331 MW,\n", + " Battery: 815.3412599999999 MW]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "technologies = [lib.wind, lib.natural_gas, lib.battery]\n", + "technologies" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Setting up the Capacity Expansion Problem\n", + "\n", + "`osier.CapacityExpansion` inherits from a `pymoo.Problem` object. This class does not run the optimization itself, so we'll have to add the `pymoo` pieces later. Before we can instantiate the problem, though, we need to define the **objectives** to optimize over!\n", + "\n", + "### Defining objectives\n", + "\n", + "`osier` comes with a set of predefined objectives, such as cost and carbon emissions. Let's start with cost and carbon emissions." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "from osier import annual_emission, total_cost\n", + "\n", + "# the default emission is `lifecycle_co2_rate`" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "problem = CapacityExpansion(technology_list = technologies,\n", + " demand=demand*MW,\n", + " wind=wind_speed,\n", + " upper_bound= 1 / lib.wind.capacity_credit,\n", + " objectives = [total_cost, annual_emission],\n", + " solver=solver) # the objectives must be passed as a LIST of functions!" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "==========================================================\n", + "n_gen | n_eval | n_nds | eps | indicator \n", + "==========================================================\n", + " 1 | 20 | 6 | - | -\n", + " 2 | 40 | 4 | 0.0158631600 | nadir\n", + " 3 | 60 | 6 | 0.0046803095 | nadir\n", + " 4 | 80 | 13 | 0.0075483249 | ideal\n", + " 5 | 100 | 11 | 0.0286189133 | ideal\n", + " 6 | 120 | 16 | 0.0143108618 | f\n", + " 7 | 140 | 19 | 0.0038096293 | ideal\n", + " 8 | 160 | 20 | 0.0123935101 | f\n", + " 9 | 180 | 20 | 0.0488020532 | nadir\n", + " 10 | 200 | 20 | 0.0176305024 | f\n", + "The simulation took 1.103 minutes.\n" + ] + } + ], + "source": [ + "algorithm = NSGA2(pop_size=20)\n", + "\n", + "import time\n", + "start = time.perf_counter()\n", + "res = minimize(problem,\n", + " algorithm,\n", + " termination=('n_gen', 10),\n", + " seed=1,\n", + " save_history=True,\n", + " verbose=True)\n", + "end = time.perf_counter()\n", + "print(f\"The simulation took {(end-start)/60:.3f} minutes.\")" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "with plt.style.context('dark_background'):\n", + " fig, ax = plt.subplots(1,1,figsize=(6,4))\n", + "\n", + " ax.scatter(res.F[:,0], res.F[:,1], edgecolors='red', facecolors='k')\n", + " ax.set_ylabel(r\"Lifecycle CO$_2$ Emissions [MT/MWh]\")\n", + " ax.set_xlabel(r\"Total Cost [M\\$]\")\n", + " ax.grid(alpha=0.2)\n", + "\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Converting an objective into a constraint\n", + "\n", + "A popular strategy with other ESOMs is to apply a constraint to a variable like carbon emissions. Although this limits understanding of tradeoffs, this may be a viable approach if there is an existing policy objective that specifies a certain level of carbon emissions.\n", + "\n", + "Instead of having two objectives, let's turn the ``annual_emission`` objective into a constraint! ``Osier`` reads constraints as a dictionary where the keys are the functions to calculate the constraint and the values are the limits to those constraints." + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "co2_limit = 2.5e-5\n", + "problem = CapacityExpansion(technology_list = technologies,\n", + " demand=demand*MW,\n", + " wind=wind_speed,\n", + " upper_bound= 1 / lib.wind.capacity_credit,\n", + " objectives = [total_cost],\n", + " constraints= {annual_emission:co2_limit},\n", + " solver=solver) # the objectives must be passed as a LIST of functions!" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "==========================================================================================\n", + "n_gen | n_eval | n_nds | cv_min | cv_avg | eps | indicator \n", + "==========================================================================================\n", + " 1 | 20 | 1 | 0.000000E+00 | 1.500000E+19 | - | -\n", + " 2 | 40 | 1 | 0.000000E+00 | 0.000000E+00 | 0.1000191518 | ideal\n", + " 3 | 60 | 1 | 0.000000E+00 | 0.000000E+00 | 0.000000E+00 | f\n", + " 4 | 80 | 1 | 0.000000E+00 | 0.000000E+00 | 0.1751703124 | ideal\n", + " 5 | 100 | 1 | 0.000000E+00 | 0.000000E+00 | 0.0269796921 | ideal\n", + " 6 | 120 | 1 | 0.000000E+00 | 0.000000E+00 | 0.0409734359 | ideal\n", + " 7 | 140 | 1 | 0.000000E+00 | 0.000000E+00 | 0.0221669721 | ideal\n", + " 8 | 160 | 1 | 0.000000E+00 | 0.000000E+00 | 0.000000E+00 | f\n", + " 9 | 180 | 1 | 0.000000E+00 | 0.000000E+00 | 0.000000E+00 | f\n", + " 10 | 200 | 1 | 0.000000E+00 | 0.000000E+00 | 0.0035921908 | ideal\n", + "The simulation took 1.120 minutes.\n" + ] + } + ], + "source": [ + "algorithm = NSGA2(pop_size=20)\n", + "\n", + "import time\n", + "start = time.perf_counter()\n", + "res_constraint = minimize(problem,\n", + " algorithm,\n", + " termination=('n_gen', 10),\n", + " seed=1,\n", + " save_history=True,\n", + " verbose=True)\n", + "end = time.perf_counter()\n", + "print(f\"The simulation took {(end-start)/60:.3f} minutes.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's run the results through a dispatch model to calculate the final carbon emissions." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[WindTurbine: 6.333350714536953 MW,\n", + " NaturalGas_Conv: 2.8132440242425973 MW,\n", + " Battery: 0.5889705432873401 MW]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "'Max wind production: 6.333350714536953 MW'" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from osier import DispatchModel\n", + "\n", + "technology_list = []\n", + "for X,tech in zip(res_constraint.X,problem.technology_list):\n", + " tech.capacity = X*problem.max_demand\n", + " technology_list.append(tech)\n", + "display(technology_list)\n", + "# normalize the wind speed\n", + "wind_speed = (wind_speed / wind_speed.max()) * res_constraint.X[0]*problem.max_demand\n", + "net_dem = demand*MW - wind_speed\n", + "display(f\"Max wind production: {wind_speed.max()}\")\n", + "\n", + "model = DispatchModel(technology_list=technology_list[1:],\n", + " net_demand=net_dem)\n", + "model.solve(solver=solver)" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "model.results = pd.concat([pd.DataFrame({'WindTurbine':wind_speed}), model.results], axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [], + "source": [ + "lifecycle_co2 = annual_emission(technology_list=technology_list,\n", + " solved_dispatch_model = model)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Let's plot this value against our Pareto front from earlier!" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "with plt.style.context('dark_background'):\n", + " fig, ax = plt.subplots(1,1,figsize=(6,4))\n", + "\n", + " ax.scatter(res.F[:,0], res.F[:,1], edgecolors='red', facecolors='k', label='Pareto Front')\n", + " ax.set_ylabel(r\"Lifecycle CO$_2$ Emissions [MT/MWh]\")\n", + " ax.set_xlabel(r\"Total Cost [M\\$]\")\n", + " ax.grid(alpha=0.2)\n", + "\n", + " ax.scatter(res_constraint.F[0], lifecycle_co2, edgecolors='yellow', facecolors='None', s=30, label='Constrained Solution')\n", + " ax.axhline(y=co2_limit, label='co2_limit', color='white', linestyle='--')\n", + " ax.legend()\n", + "\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Analysis\n", + "\n", + "1. Only one solution is shown, here, since we simply converted the objective in a constraint and performed a single objective optimization.\n", + "2. This example shows that ``Osier`` respects constraints (though ``Pymoo`` is \"greedy\" and minimizes the constraint violation (CV) rather than strictly honoring a constraint).\n", + "3. The existence of a lower total cost and slightly higher CO$_2$ solution on the Pareto Front suggests that the simpler model is not fully converged (although, neither of the models can be considered \"fully converged\" since they used a small number of generations).\n", + "\n", + "## Applying two objectives and a constraint\n", + "\n", + "If we still wanted to see some tradeoff while applying a constraint to one of them -- we can! The next example demonstrates this." + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [], + "source": [ + "co2_limit = 2.5e-5\n", + "problem = CapacityExpansion(technology_list = technologies,\n", + " demand=demand*MW,\n", + " wind=wind_speed,\n", + " upper_bound= 1 / lib.wind.capacity_credit,\n", + " objectives = [total_cost, annual_emission],\n", + " constraints= {annual_emission:co2_limit},\n", + " solver=solver) # the objectives must be passed as a LIST of functions!" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "==========================================================================================\n", + "n_gen | n_eval | n_nds | cv_min | cv_avg | eps | indicator \n", + "==========================================================================================\n", + " 1 | 20 | 5 | 0.000000E+00 | 1.500000E+19 | - | -\n", + " 2 | 40 | 6 | 0.000000E+00 | 0.000000E+00 | 0.0654705631 | f\n", + " 3 | 60 | 7 | 0.000000E+00 | 0.000000E+00 | 0.2485795005 | ideal\n", + " 4 | 80 | 10 | 0.000000E+00 | 0.000000E+00 | 0.3049179277 | nadir\n", + " 5 | 100 | 11 | 0.000000E+00 | 0.000000E+00 | 1.3721450111 | nadir\n", + " 6 | 120 | 11 | 0.000000E+00 | 0.000000E+00 | 0.5801153169 | nadir\n", + " 7 | 140 | 15 | 0.000000E+00 | 0.000000E+00 | 0.0247543877 | nadir\n", + " 8 | 160 | 18 | 0.000000E+00 | 0.000000E+00 | 0.0367281977 | ideal\n", + " 9 | 180 | 20 | 0.000000E+00 | 0.000000E+00 | 0.0147077342 | f\n", + " 10 | 200 | 20 | 0.000000E+00 | 0.000000E+00 | 0.0072011434 | nadir\n", + "The simulation took 1.095 minutes.\n" + ] + } + ], + "source": [ + "algorithm = NSGA2(pop_size=20)\n", + "\n", + "import time\n", + "start = time.perf_counter()\n", + "res_constraint_2 = minimize(problem,\n", + " algorithm,\n", + " termination=('n_gen', 10),\n", + " seed=1,\n", + " save_history=True,\n", + " verbose=True)\n", + "end = time.perf_counter()\n", + "print(f\"The simulation took {(end-start)/60:.3f} minutes.\")" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "with plt.style.context('dark_background'):\n", + " fig, ax = plt.subplots(1,1,figsize=(6,4))\n", + "\n", + " ax.scatter(res.F[:,0], res.F[:,1], edgecolors='red', facecolors='k', label='Pareto Front')\n", + " ax.set_ylabel(r\"Lifecycle CO$_2$ Emissions [MT/MWh]\")\n", + " ax.set_xlabel(r\"Total Cost [M\\$]\")\n", + " ax.grid(alpha=0.2)\n", + "\n", + " ax.scatter(res_constraint.F[0], lifecycle_co2, edgecolors='yellow', \n", + " facecolors='None', marker='s', s=30, label='Single-objective Constrainted')\n", + " ax.scatter(res_constraint_2.F[:,0], res_constraint_2.F[:,1], \n", + " edgecolors='lime', facecolors='None', marker='*', s=30, label='Multi-objective Constrained')\n", + " ax.axhline(y=co2_limit, label='CO$_2$ Limit', color='white', linestyle='--')\n", + " ax.legend()\n", + "\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Analysis\n", + "\n", + "Once again, it looks like the constrained model is not quite as \"converged\" as the unconstrained model since the latter shows some cheaper and lower emissions solutions. The example further illustrates how ``Osier`` can use \"objective\" functions as objectives and/or constraints!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "2025-dotson-thesis", + "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": "3.11.11" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/docs/source/examples/index.md b/docs/source/examples/index.md index 71c0360..7ca94a2 100644 --- a/docs/source/examples/index.md +++ b/docs/source/examples/index.md @@ -12,5 +12,6 @@ getting_started tech_tutorial dispatch_tutorial capacity_expansion_tutorial +constraint_tutorial mga_tutorial ``` \ No newline at end of file