Optimization framework flixOpt

Software for operational management optimization and dimensioning of generator parks

FlixOpt offers a software-supported decision-making aid

• in municipal heat planning
• for the transformation of the energy supply
• for comparing the variants of supply concepts
• to reduce operating costs and emissions
• to optimize the use of resources

Features

• Combined operational management and design optimization
• wide variety of models: conventional and renewable generators, storage, sector coupling, simplified grid structures, freely definable balancing groups
• Variable target criteria and internalization: costs, emissions, primary energy
• Reduction in calculation time through optional time series simplification or segmentation

Implementation

• Generic, modular implementation
• Solution using linear mixed integer optimization (MILP)
• uncomplicated, individual MILP solver connection (free and commercial)
• Performance increase through clustering method

Web application

Quick, installation-free access: FlixOptWeb

The web application enables the use of flixOpt directly in the web browser without installing additional software. In this version, however, the range of functions and performance is limited.
Free registration is required to use the web application. To get started, the following three examples are available for download:

Example 1:

• Operational management optimization of storage, boiler, CHP plant, electricity feed-in
• Heat load coverage
• Constant efficiency
• Constant feed-in tariff
• Complete optimization
• very short optimization period

Example 2:

• Operational management optimization of storage tank, boiler, CHP plant, electricity feed-in
• Design optimization of storage tank and boiler
• Heat load coverage
• Linearized efficiency of the CHP system in sections
• Constant feed-in tariff
• Complete optimization
• very short optimization period

Example 3:

• Operational management optimization of storage, boiler, CHP plant, electricity feed-in, electricity purchase
• Covering heat load and covering electricity load
• Constant efficiency levels
• Variable feed-in tariff and purchase prices
• Problem simplification through aggregation (variable)
• Long optimization period (1 year, every quarter of an hour)

Detailed description of the examples and information on their use: Quick guide

Python framework

Open source for download at: https://github.com/flixopt/

The Python framework offers the full range of functions, but requires a Python interpreter and the additional installation of an MILP solver. In this case, the software is script-based.

Developed as part of the project "SmartBioGrid - Options for the use of solid biomass in decarbonized heating networks" (FKZ: 03KB159B)

Download: https://github.com/flixopt/

For further information please contact Dr. rer. nat. Peter Stange,

Publication

F. Panitz, P. Stange, Investment optimization for district heating supply systems, EuroSun2022, Kassel, September 2022, https://doi.org/10.13140/RG.2.2.14948.24969

To the project overview