Renewable power plants: Main notebook
This notebook is part of the Renewable power plants Data Package of Open Power System Data.

About Open Power System Data

This Notebook is part of the project Open Power System Data. 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. More info on Open Power System Data:

About Jupyter Notebooks and GitHub

This file is a Jupyter Notebook. 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, a platform for software development, and are publicly available. More information on our IT-concept can be found here. See also our step-by-step manual how to use the dataplatform.

About this Data Package

We provide data in different chunks, or Data Packages. The one you are looking at right now, Renewable power plants, contains

  • lists of renewable energy power plants of selected countries in Europe
  • daily time series of cumulated installed capacity per energy source type for Germany.

Due to differing data availability, the power plant lists are of variable accuracy and partly provide different power plant parameters. Therefore the lists are provided in addition to the overall European list also as separate CSV files per country and as separate sheets in the Excel file, which contain more information than the European list.

Set up the notebook

Import packages and modules needed to automatically generate parts of this notebook.

In [1]:
import importlib
import os
import json
import matplotlib as plt
from IPython.display import display
import os
import pandas as pd
import util.helper
import util.visualizer

version = '2020-08-25'

Countries

In [2]:
country_list_filepath = os.path.join('input', 'countries.csv')
countries_df = pd.read_csv(country_list_filepath)
util.visualizer.visualize_countries(countries_df['full_name'].tolist())