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This repository holds a collections of various examples on how to build an energy system with oemof.

Examples are provided for each major oemof release specified by the directory they are in.

Download the repository using the green download button.

You need a working python3 environment to be able to run the examples. For more details see 'Installation and setup' section of the oemof documentation. Required packages to run each example are listed in the respective example header.

Everybody is welcome to contribute by adding their own example, fix documentation, bugs and typos in existing examples, etc via a pull request or by sending us an e-mail (see here for contact information). If you want to add your own example please provide a short description and required packages to run the example.

  • basic_example: Introduction to the basic usage of oemof.solph
    • basic optimisation with different solvers
    • initiate the logger
    • use the lp-file for debugging
    • show/hide output of the solver
    • store and process results
  • electrical: Linear Optimised Power Flow
  • emission constraint: Shows how to add an additional constraint to limit the overall emissions.
  • excel-reader (replacement for csv-reader) Shows how to define the input data in a customisable excel-file (libreoffice etc.)
  • flexible_modelling: Shows how to add an individual constraint to the oemof solph Model.
  • generic_chp: Illustrates how the custom component GenericCHP can be used...
    • bpt: ... to model a back pressure turbine.
    • ccet: ... to model a combined cycle extraction turbine.
    • mchp: ... to model a motoric chp.
  • installation test: Test your oemof installation and the connected solvers
  • invest_non_convex: This example illustrates a possible combination of solph.Investment and solph.NonConvex. Note that both options are added to different components of the energy system.
  • min_max_runtimes: Example that illustrates how to model min and max runtimes.
  • plotting_examples: The examples shows how to use oemof_visio with solph results.
  • simple_dispatch: Shows how to set up a dispatch model.
  • start_and_shutdown_costs: Example that illustrates how to model startup and shutdown costs attributed to a binary flow.
  • storage_investment: Variation of parameters for a storage capacity optimization.
  • variable_chp: Presents how a variable combined heat and power plant (chp) works in contrast to a fixed chp.
  • basic_example: Introduction to the basic usage of oemof.solph
    • basic optimisation with different solvers
    • initiate the logger
    • use the lp-file for debugging
    • show/hide output of the solver
    • store and process results
  • excel-reader (replacement for csv-reader) Shows how to define the input data in a customisable excel-file (libreoffice etc.)
  • flexible_modelling: Shows how to add an individual constraint to the oemof solph Model.
  • generic_chp: Illustrates how the custom component GenericCHP can be used...
    • bpt: ... to model a back pressure turbine.
    • ccet: ... to model a combined cycle extraction turbine.
    • mchp: ... to model a motoric chp.
  • sdewes_paper_2017: Examples from the SDEWES conference paper.
    • economic_dispatch
    • micro_grid_design_optimisation
    • unit_commitment_district_heating
  • sector_coupling: Jupyter notebook giving a simple example of how to couple the sectors power, heat and mobility.
  • simple_dispatch: Shows how to set up a dispatch model.
  • storage_investment: Variation of parameters for a storage capacity optimization.
  • variable_chp: Presents how a variable combined heat and power plant (chp) works in contrast to a fixed chp.
  • csv_reader:
    • dispatch: Dispatch optimisation using oemof's csv-reader.
    • investment: Investment optimisation using oemof's csv-reader.
  • flexible_modelling: Shows how to add an individual constraint to the oemof solph Model.
  • sector_coupling: Jupyter notebook giving a simple example of how to couple the sectors power, heat and mobility.
  • simple_dispatch: Shows how to set up a dispatch model.
  • storage_invest: Jupyter notebook of storage capacity optimization.
  • storage_investment: Example of storage capacity optimization.
  • variable_chp: Presents how a variable combined heat and power plant (chp) works in contrast to a fixed chp.

Coming soon

  • clausius_rankine: Basic example of the clausius rankine process.
  • clausius_rankine_chp: Backpressure turbine in district heating.
  • combined_cycle_chp: Combined cycle power plant with backpressure steam turbine.
  • combustion: Examples on how to work with combustion in TESPy.
  • custom_variables: Example on how to calculate the diameter of a pipe at a given pressure ratio.
  • district_heating: A small district heating systems with about 150 components.
  • heat_pump: An air to water and a water to water heat pump for power-to-heat applications.
  • solar_collector: An example to show, how the solar collector component can be implemented.
  • ModelChain example: A simple way to calculate the power output of wind turbines.

Copyright (C) 2017 oemof developing group

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

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  • Jupyter Notebook 61.3%
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