{ "cells": [ { "cell_type": "markdown", "metadata": { "toc": true }, "source": [ "# Table of contents\n", "1. [About Open Power System Data](#opsd)\n", "2. [About Jupyter Notebooks and GitHub](#jupyter)\n", "3. [About this datapackage](#datapackage)\n", "4. [Data sources](#sources)\n", "5. [Naming conventions](#naming)\n", "6. [License](#license)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", " Time series: Processing Notebook\n", " \n", "
This Notebook is part of the heating profiles data package contributed to Open Power System Data.\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "# 1. About Open Power System Data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook is a contribution to the project [Open Power System Data](http://open-power-system-data.org). Open Power System Data develops a platform for free and open data for electricity system modeling. We collect, check, process, document, and provide data that are publicly available but currently inconvenient to use. \n", "More info on Open Power System Data:\n", "- [Information on the project on our website](http://open-power-system-data.org)\n", "- [Data and metadata on our data platform](http://data.open-power-system-data.org)\n", "- [Data processing scripts on our GitHub page](https://github.com/Open-Power-System-Data)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "# 2. About Jupyter Notebooks and GitHub" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This file is a [Jupyter Notebook](http://jupyter.org/). A Jupyter Notebook is a file that combines executable programming code with visualizations and comments in markdown format, allowing for an intuitive documentation of the code. We use Jupyter Notebooks for combined coding and documentation. We use Python 3 as programming language. All Notebooks are stored on [GitHub](https://github.com/), a platform for software development, and are publicly available. More information on our IT-concept can be found [here](http://open-power-system-data.org/it). See also our [step-by-step manual](http://open-power-system-data.org/step-by-step) how to use the dataplatform." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "# 3. About this datapackage" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This dataset comprises national time series for representing building heat pumps in power system models. The heat demand of buildins and the coefficient of performance (COP) of heat pumps is calculated for 16 European countries from 2008 to 2013 in an hourly resolution. \n", "\n", "Heat demand time series for space and water heating are computed by combining gas standard load profiles with spatial temperature and wind speed reanalysis data, population geodata, and annual statistics on the final energy consumption for heating. \n", "\n", "COP time series for different heat sources – air, ground, and groundwater – and different heat sinks – floor heating and radiators, both combined with water heating – are calculated based on COP and heating curves, reanalysis temperature data, a spatial aggregation procedure with respect to the heat demand, and a correction procedure for part-load losses. \n", "\n", "All data processing as well as the download of relevant input data is conducted in python and pandas and has been documented in the processing notebook linked above." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "# 4. Data sources" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A complete list of data sources is provided on the [datapackage information website](http://data.open-power-system-data.org/when2heat/). They are also contained in the JSON file that contains all metadata." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "# 5. Naming conventions" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/html": [ "
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countryvariableattributedescription
ISO-2 digit country codeheat_demandtotalHeat demand for space and water heating
spaceHeat demand for space heating
waterHeat demand for water heating
space_SFHHeat demand for space heating in single-family houses
space_MFHHeat demand for space heating in multi-family houses
space_COMHeat demand for space heating in commercial buildings
water_SFHHeat demand for water heating in single-family houses
water_MFHHeat demand for water heating in multi-family houses
water_COMHeat demand for water heating in commercial buildings
heat_profilespace_SFHNormalized heat demand for space heating in single-family houses
space_MFHNormalized heat demand for space heating in multi-family houses
space_COMNormalized heat demand for space heating in commercial buildings
water_SFHNormalized heat demand for water heating in single-family houses
water_MFHNormalized heat demand for water heating in multi-family houses
water_COMNormalized heat demand for water heating in commercial buildings
COPASHP_floorCOP of air-source heat pumps with floor heating
ASHP_radiatorCOP of air-source heat pumps with radiator heating
ASHP_waterCOP of air-source heat pumps with water heating
GSHP_floorCOP of ground-source heat pumps with floor heating
GSHP_radiatorCOP of ground-source heat pumps with radiator heating
GSHP_waterCOP of ground-source heat pumps with water heating
WSHP_floorCOP of groundwater-source heat pumps with floor heating
WSHP_radiatorCOP of groundwater-source heat pumps with radiator heating
WSHP_waterCOP of groundwater-source heat pumps with water heating
\n", "
" ], "text/plain": [ "Empty DataFrame\n", "Columns: []\n", "Index: [(ISO-2 digit country code, heat_demand, total, Heat demand for space and water heating), (ISO-2 digit country code, heat_demand, space, Heat demand for space heating), (ISO-2 digit country code, heat_demand, water, Heat demand for water heating), (ISO-2 digit country code, heat_demand, space_SFH, Heat demand for space heating in single-family houses), (ISO-2 digit country code, heat_demand, space_MFH, Heat demand for space heating in multi-family houses), (ISO-2 digit country code, heat_demand, space_COM, Heat demand for space heating in commercial buildings), (ISO-2 digit country code, heat_demand, water_SFH, Heat demand for water heating in single-family houses), (ISO-2 digit country code, heat_demand, water_MFH, Heat demand for water heating in multi-family houses), (ISO-2 digit country code, heat_demand, water_COM, Heat demand for water heating in commercial buildings), (ISO-2 digit country code, heat_profile, space_SFH, Normalized heat demand for space heating in single-family houses), (ISO-2 digit country code, heat_profile, space_MFH, Normalized heat demand for space heating in multi-family houses), (ISO-2 digit country code, heat_profile, space_COM, Normalized heat demand for space heating in commercial buildings), (ISO-2 digit country code, heat_profile, water_SFH, Normalized heat demand for water heating in single-family houses), (ISO-2 digit country code, heat_profile, water_MFH, Normalized heat demand for water heating in multi-family houses), (ISO-2 digit country code, heat_profile, water_COM, Normalized heat demand for water heating in commercial buildings), (ISO-2 digit country code, COP, ASHP_floor, COP of air-source heat pumps with floor heating), (ISO-2 digit country code, COP, ASHP_radiator, COP of air-source heat pumps with radiator heating), (ISO-2 digit country code, COP, ASHP_water, COP of air-source heat pumps with water heating), (ISO-2 digit country code, COP, GSHP_floor, COP of ground-source heat pumps with floor heating), (ISO-2 digit country code, COP, GSHP_radiator, COP of ground-source heat pumps with radiator heating), (ISO-2 digit country code, COP, GSHP_water, COP of ground-source heat pumps with water heating), (ISO-2 digit country code, COP, WSHP_floor, COP of groundwater-source heat pumps with floor heating), (ISO-2 digit country code, COP, WSHP_radiator, COP of groundwater-source heat pumps with radiator heating), (ISO-2 digit country code, COP, WSHP_water, COP of groundwater-source heat pumps with water heating)]" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd; pd.read_csv('input/notation.csv', index_col=list(range(4)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "# 6. License" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook as well as all other documents in this repository is published under the [MIT License](LICENSE.md)." ] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python 3", "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": "3.7.2" }, "toc": { "nav_menu": { "height": "120px", "width": "252px" }, "number_sections": false, "sideBar": true, "skip_h1_title": false, "toc_cell": true, "toc_position": {}, "toc_section_display": "block", "toc_window_display": true }, "varInspector": { "cols": { "lenName": 16, "lenType": 16, "lenVar": 40 }, "kernels_config": { "python": { "delete_cmd_postfix": "", "delete_cmd_prefix": "del ", "library": "var_list.py", "varRefreshCmd": "print(var_dic_list())" }, "r": { "delete_cmd_postfix": ") ", "delete_cmd_prefix": "rm(", "library": "var_list.r", "varRefreshCmd": "cat(var_dic_list()) " } }, "types_to_exclude": [ "module", "function", "builtin_function_or_method", "instance", "_Feature" ], "window_display": false } }, "nbformat": 4, "nbformat_minor": 1 }