{ "cells": [ { "cell_type": "markdown", "id": "49bfe11b", "metadata": {}, "source": [ "# PyProdrisk: Basic example\n", "\n", "In this example, we build a simple Prodrisk model containing one module, add dummy price and inflow data, and run a simulation over three years.\n", "\n", "Here, all input is directly given through the API without any input file parsing.\n", "\n", "While the model in this example is quite simple, it can serve as a good reference when designing your own models. It illustrates an intuitive way of designing models using pyProdrisk by incrementally initializing new objects like modules, inflowSeries, area and setting, and setting their key attributes. The model is then optimized, before the results are retrieved and presented through plots.\n", "\n", "## Imports and settings\n", "\n", "The first thing we do is to import the needed packages. You can import whichever packages you like, however we use the following ones for this example:\n", "\n", "- pandas and numpy to structure our data\n", "- pyprodrisk in order to create a Prodrisk session" ] }, { "cell_type": "code", "execution_count": 1, "id": "5fe521e1", "metadata": { "Collapsed": "false" }, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "from pyprodrisk import ProdriskSession" ] }, { "cell_type": "markdown", "id": "63eeefd8", "metadata": {}, "source": [ "## Building the model\n", "\n", "In this example we define the entire topology and generate all its parameters via Python and the API. Below are simple examples on how to define the most common topology objects needed in order to run Prodrisk.\n", "\n", "### Instancing Prodrisk\n", "\n", "In order to have Prodrisk receive our inputs, run the model we create and give us results, we need to create an active, running Prodrisk session.\n", "\n", "You may create multiple Prodrisk sessions simultaneously if needed." ] }, { "cell_type": "code", "execution_count": 2, "id": "00033618", "metadata": { "Collapsed": "false" }, "outputs": [], "source": [ "# --- create a new session ---\n", "\n", "prodrisk = ProdriskSession(license_path='/prodrisk', solver_path='/pyprodrisk', silent=False, log_file='')" ] }, { "cell_type": "markdown", "id": "04d9efc6", "metadata": {}, "source": [ "### Setting time resolutions and settings for the model\n", "\n", "We set the time resolution for the model ourselves, as we generate all input as we go.\n", "\n", "The time resolution is set by the price_periods time series (only input data from the first 168 hours is used). This input group the hours during the week into blocks with identical price, which not necessarily have to be sequential. This example use daily time resolution. Prodrisk may be run with hourly resolution, but for most cases this will lead to a long computation time." ] }, { "cell_type": "code", "execution_count": 3, "id": "b476766e", "metadata": { "Collapsed": "false" }, "outputs": [], "source": [ "# --- configure settings for the session ---\n", "\n", "prodrisk.set_optimization_period(\n", " pd.Timestamp(\"2021-01-04\"),\n", " n_weeks = 156\n", ")\n", "\n", "prodrisk.n_scenarios = 10\n", "prodrisk.use_coin_osi = False\n", "prodrisk.command_line_option = \"-sekv\"\n", "prodrisk.min_iterations = 1 # default 1\n", "prodrisk.max_iterations = 3 # default 10\n", "prodrisk.min_iterations_first_run = 1 # default 1\n", "prodrisk.max_iterations_first_run = 3 # default 10\n", "prodrisk.n_price_levels = 7 # number of levels in discrete price model (include max and min)\n", "prodrisk.n_processes = 1 # number of mpi processes\n", "prodrisk.price_periods = pd.Series(\n", " index = [prodrisk.start_time + pd.Timedelta(days=i) for i in range(7)],\n", " data=[1, 2, 3, 4, 5, 6, 7]\n", ")\n", "\n", "prodrisk.deficit_power_cost = 500.0\n", "prodrisk.surplus_power_cost = 0.02\n", "prodrisk.water_ration_cost = 1000.0\n", "\n", "# Use new result writing\n", "prodrisk.supress_seq_res = 0\n", "prodrisk.aggregated_price_period_start_week = 104\n", "prodrisk.sequential_price_period_start_week = 1\n", "prodrisk.sequential_price_period_end_week = 40\n", "prodrisk.reservoir_balance_option = 1\n", "\n", "prodrisk.temp_dir = \"/work/temp\"\n", "prodrisk.log_file_path = \"/work/logfiles\"\n", "prodrisk.prodrisk_path = \"/prodrisk\"\n", "prodrisk.prodrisk_variant = \"prodrisk_cplex\"" ] }, { "cell_type": "markdown", "id": "952bb7f4", "metadata": {}, "source": [ "### Module\n", "\n", "First, we start of by creating our module object, and add some identifier attributes" ] }, { "cell_type": "code", "execution_count": 4, "id": "02504c07", "metadata": { "Collapsed": "false" }, "outputs": [], "source": [ "# --- add a module to the session ---\n", "\n", "mod = prodrisk.model.module.add_object('ModuleA')\n", "mod.name.set('ModuleA')\n", "mod.plantName.set('PlantA')\n", "mod.number.set(1001)\n", "mod.ownerShare.set(1.0)\n", "mod.regulationType.set(1)" ] }, { "cell_type": "markdown", "id": "5d686d8a", "metadata": {}, "source": [ "We then add the reservoir specific attributes:" ] }, { "cell_type": "code", "execution_count": 5, "id": "fdd0f158", "metadata": { "Collapsed": "false" }, "outputs": [], "source": [ "mod.rsvMax.set(200.0)\n", "mod.connectedSeriesId.set(1)\n", "mod.meanRegInflow.set(630.0)\n", "mod.meanUnregInflow.set(0.0)\n", "mod.nominalHead.set(700.0)\n", "mod.submersion.set(0.0)\n", "mod.volHeadCurve.set(pd.Series(name=0.0, index=[0.0, 200.0], data=[600.0, 1000.0]))" ] }, { "cell_type": "markdown", "id": "0722bb42", "metadata": {}, "source": [ "The refVol attribute is used as as steering curve for buffer reservoirs. In addition, this attribute is used as the reference volume for the head correction in the backward iterations of the \"first main iteration\". Default value for this attribute is a typical series (based on the start date) with high volume in fall and low volume in spring." ] }, { "cell_type": "code", "execution_count": 6, "id": "df868f90", "metadata": { "Collapsed": "false" }, "outputs": [], "source": [ "mod.refVol.set(pd.Series(name=0.0,\n", " index = [prodrisk.start_time + pd.Timedelta(weeks=i) for i in [0,18,24,52,70,76,104,122,128,156]],\n", " data=[45.0, 10.0, 90.0, 100.0, 10.0, 90.0, 100.0, 10.0, 90.0, 100.0]))" ] }, { "cell_type": "markdown", "id": "6fb66ea5", "metadata": {}, "source": [ "The plant specific attributes:" ] }, { "cell_type": "code", "execution_count": 7, "id": "070f0254", "metadata": { "Collapsed": "false" }, "outputs": [], "source": [ "mod.PQcurve.set(pd.Series(name=50.0, index=[0, 20.0, 40.0, 80.0], data=[0, 20.0, 30.0, 65.0]))\n", "mod.energyEquivalentConst.set(0.341)\n", "mod.maxDischargeConst.set(65.0)\n", "mod.maxProd.set(80.0)\n", "mod.maxBypassConst.set(10000.0)" ] }, { "cell_type": "markdown", "id": "aaabb6a4", "metadata": {}, "source": [ "The water routes out of the module are described by the topology list, which should be a list of three module numbers (e.g. 1001, 1002, 1003) describing which module(s) in the system the discharge, bypass and spillage from “Module A” should end up in. In this example there is only one module, and all discharged water goes to the ocean (module number 0)." ] }, { "cell_type": "code", "execution_count": 8, "id": "ee4638c0", "metadata": { "Collapsed": "false" }, "outputs": [], "source": [ "mod.topology.set([0, 0, 0])" ] }, { "cell_type": "markdown", "id": "f194886b", "metadata": {}, "source": [ "Finally, we add the initial state for our reservoir:" ] }, { "cell_type": "code", "execution_count": 9, "id": "ab4860a7", "metadata": { "Collapsed": "false" }, "outputs": [], "source": [ "mod.startVol.set(90.0)" ] }, { "cell_type": "markdown", "id": "57fa8e5d", "metadata": {}, "source": [ "### Inflow serie\n", "\n", "An inflow series object is created to represent the inflow profile to our module:" ] }, { "cell_type": "code", "execution_count": 10, "id": "5f6c18d9", "metadata": { "Collapsed": "false" }, "outputs": [], "source": [ "# --- add inflow series to the session ---\n", "\n", "y1 = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 100, 100, 100, 30, 30, 30, 30, 30, 30, 30, 30, 30,\n", " 30, 30, 30, 30, 30, 30, 30, 30, 30, 45, 45, 45, 30, 30, 30, 30, 30, 30, 30, 30, 10, 10]\n", "y2 = [5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 50, 50, 50, 50, 10, 10, 10, 10, 10, 10, 10, 10,\n", " 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 1, 1, 1, 1, 1]\n", "y3 = [10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 60, 60, 60, 60, 15, 15, 15, 15, 15, 15,\n", " 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5]\n", "\n", "inflow_df = pd.DataFrame(\n", " index=[prodrisk.start_time + pd.Timedelta(weeks=i) for i in range(prodrisk.n_weeks)],\n", " data={\n", " \"scen0\": y1 + y2 + y3,\n", " \"scen1\": y2 + y3 + y1,\n", " \"scen2\": y3 + y1 + y2,\n", " \"scen3\": y1 + y1 + y2,\n", " \"scen4\": y1 + y2 + y2,\n", " \"scen5\": y2 + y2 + y3,\n", " \"scen6\": y2 + y3 + y3,\n", " \"scen7\": y3 + y1 + y1,\n", " \"scen8\": y3 + y3 + y1,\n", " \"scen9\": y2 + y1 + y3,\n", " },\n", ")\n", "\n", "ser = prodrisk.model.inflowSeries.add_object('Serie1')\n", "ser.seriesId.set(1)\n", "ser.inflowScenarios.set(inflow_df)" ] }, { "cell_type": "markdown", "id": "7fce4953", "metadata": {}, "source": [ "We use three hardcoded years with weekly inflow input (52 values) as a base, and create 10 different scenarios with timespan 3 years (156 weeks) as different sequential combinations of these three “inflow years”.\n", "\n", "The inflow series has already been connected to our module by setting the “module” attribute “connectedSeriesId” for “ModuleA” equal to the “seriesId” for our inflowSeries “Serie1” (the id is 1).\n", "\n", "The local inflow to ModuleA is calculated as inflowScenarios * meanRegInflow / histAverageInflow, where “meanRegInflow” is an attribute must be set on the module object ModuleA, and “histAverageInflow” is an attribute which may be set on the inflow series object Serie1. If “histAverageInflow” is not set, it is calculated as an average over the last 52 weeks of all inflowScenarios.\n", "\n", "### Area\n", "\n", "An area object ‘my_area’ is created to provide input price and water values:" ] }, { "cell_type": "code", "execution_count": 11, "id": "427bf0ab", "metadata": { "Collapsed": "false" }, "outputs": [], "source": [ "# --- add area object (price and watervalue) to the session ---\n", "\n", "area = prodrisk.model.area.add_object('my_area')\n", "seasonPrice = [20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 15, 15, 15, 15, 15, 15, 8, 8, 8, 8, 8, 8, 8, 8,\n", " 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 10, 10, 10, 10, 10]\n", "np.random.seed(5)\n", "randomPrice = np.random.rand(prodrisk.n_scenarios * prodrisk.n_weeks, 1)\n", "priceScenarios = [0.3 * randomPrice[i] * seasonPrice[i % 52] for i in range(len(randomPrice))]\n", "\n", "priceScenIndexed = np.array(priceScenarios).reshape((prodrisk.n_scenarios, prodrisk.n_weeks))\n", "price_df = pd.DataFrame(\n", " index=[prodrisk.start_time + pd.Timedelta(weeks=i) for i in range(prodrisk.n_weeks)],\n", " data={\n", " f\"scen{i}\": ps for i, ps in enumerate(priceScenIndexed)\n", " },\n", ")\n", "area.price.set(price_df)\n", "\n", "# --- add simple water value matrix to the session ---\n", "refs = []\n", "nPoints = []\n", "x = []\n", "y = []\n", "\n", "for i in range(7):\n", " refs.append(i)\n", " nPoints.append(51)\n", "\n", " for n in range(51):\n", " x.append(np.real(100 - n * 2))\n", " y.append(np.real((10.0 + n * 0.3) * i * 0.5))\n", "\n", "\n", "x_values = np.array(x).reshape((7, 51))\n", "y_values = np.array(y).reshape((7, 51))\n", "area.waterValue.set([\n", " pd.Series(name=ref, index=x_val, data=y_val) for ref, x_val, y_val in zip(refs, x_values, y_values)\n", "])" ] }, { "cell_type": "markdown", "id": "d065cb00", "metadata": {}, "source": [ "# Running Prodrisk\n", "\n", "The command run() will generate a temporary folder of input files, run Prodrisk and extract the results from the result files. The temporary folder is deleted when python exit the scope where the ProdriskSession exits, unless the setting keep_working_directory is set to True." ] }, { "cell_type": "code", "execution_count": 12, "id": "76cc9e80", "metadata": { "Collapsed": "false" }, "outputs": [], "source": [ "# --- run prodrisk session ---\n", "\n", "status = prodrisk.run()" ] }, { "cell_type": "markdown", "id": "81018242", "metadata": {}, "source": [ " \n", "\n", "# Results\n", "\n", "Finally we plot and print and plot some results.\n", "\n", "## Expected objective value" ] }, { "cell_type": "code", "execution_count": 13, "id": "ba313791", "metadata": { "Collapsed": "false" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Expected objective value: 21009.885 kkr\n" ] } ], "source": [ "my_area = prodrisk.model.area[\"my_area\"]\n", "\n", "expected_objective_val_kkr = my_area.expected_objective_value.get()\n", "print(f\"Expected objective value: {expected_objective_val_kkr} kkr\")" ] }, { "cell_type": "markdown", "id": "9bc2f1c1", "metadata": {}, "source": [ " \n", "\n", "## Stochastic time series of price" ] }, { "cell_type": "code", "execution_count": 14, "id": "a61499f6", "metadata": { "Collapsed": "false" }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "price = my_area.price.get()\n", "\n", "f = plt.figure(0)\n", "ax = plt.subplot(111)\n", "ax.fill_between(price.index, np.percentile(price.values[:,:],0,axis=1),np.percentile(price.values[:,:],100,axis=1),alpha=0.2)\n", "ax.plot(price.mean(axis=1))\n", "ax.set(ylabel='Price [EUR/MWh]')\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "0f14ce9b", "metadata": {}, "source": [ "## Stochastic time series of production from ModuleA" ] }, { "cell_type": "code", "execution_count": 15, "id": "d5693f65", "metadata": { "Collapsed": "false" }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "production = mod.production.get()\n", "\n", "f = plt.figure(1)\n", "ax = plt.subplot(111)\n", "ax.fill_between(production.index, np.percentile(production.values[:,:],0,axis=1),np.percentile(production.values[:,:],100,axis=1),alpha=0.2)\n", "ax.plot(production.mean(axis=1))\n", "ax.set(ylabel='Production [MW]')\n", "plt.show()" ] } ], "metadata": { "jupytext": { "text_representation": { "extension": ".md", "format_name": "myst", "format_version": 0.13, "jupytext_version": "1.13.8" } }, "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.11.9" }, "source_map": [ 12, 30, 38, 51, 57, 66, 105, 112, 123, 128, 138, 143, 149, 154, 162, 167, 171, 176, 180, 187, 218, 231, 272, 279, 286, 296, 304, 309, 320, 325 ] }, "nbformat": 4, "nbformat_minor": 5 }