Calliope: a multi-scale energy systems (MUSES) modeling framework

v0.5.1 (Release history)

Calliope is a framework to develop energy system models using a modern and open source Python-based toolchain.

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This is the documentation for version 0.5.1. See the main project website for contact details and other useful information.

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Calliope is a framework to develop energy system models, with a focus on flexibility, high spatial and temporal resolution, the ability to execute many runs based on the same base model, and a clear separation of framework (code) and model (data).

A model based on Calliope consists of a collection of text files (in YAML and CSV formats) that define the technologies, locations and resource potentials. Calliope takes these files, constructs an optimization problem, solves it, and reports results in the form of xarray Datasets which in turn can easily be converted into Pandas data structures, for easy analysis with Calliope’s built-in tools or the standard Python data analysis stack.

Calliope is developed in the open on GitHub and contributions are very welcome (see the Development guide). See the list of open issues and planned milestones for an overview of where development is heading, and join us on Gitter to ask questions or discuss code.

Main features:

• Generic technology definition allows modeling any mix of production, storage and consumption
• Resolved in space: define locations with individual resource potentials
• Resolved in time: read time series with arbitrary resolution
• Model specification in an easy-to-read and machine-processable YAML format
• Able to run on computing clusters
• Easily extensible in a modular way: custom constraint generator functions and custom time mask functions
• Uses a state-of-the-art Python toolchain based on Pyomo, xarray, and Pandas
• Freely available under the Apache 2.0 license

User guide

• Introduction
  • Rationale
  • Acknowledgments
  • License
  • References
• Download and installation
  • Requirements
  • Recommended installation method
  • Solvers
  • Python module requirements
• Components to build a model
  • Terminology
  • Index sets
  • Technology types
  • Cost classes
  • Putting technologies and locations together: Nodes
  • Node energy balance
  • Linking locations
• Tutorials
  • Tutorial 1: national scale
  • Tutorial 2: urban scale
  • Files that define the model
  • The run configuration
  • Running a model and analyzing results
• Model formulation
  • Time-varying vs. constant model parameters
  • Decision variables
  • Objective function (cost minimization)
  • Basic constraints
  • Planning constraints
  • Optional constraints
• Model configuration
  • Technologies
  • Locations
  • Transmission links
  • Overriding technology options
  • Using time series data
  • Loading optional constraints
• Run configuration
  • Time resolution adjustment
  • Settings for parallel runs
• Running the model
  • Single runs with the command-line tool
  • Parallel runs
  • Running programmatically from other Python code
  • Extracting results from a completed model run
  • Debugging failing runs
• Analyzing results
  • The solution object
  • Reading solutions
  • Reading results from parallel runs
  • Analyzing solutions
• Configuration reference
  • YAML configuration file format
  • Model-wide settings
  • Technology
  • Technology constraints
  • Technology costs
  • Technology depreciation
  • Abstract base technologies
  • Run settings
• Built-in example models
  • National-scale example
  • Urban-scale example
• Development guide
  • Installing a development version
  • Creating modular extensions
  • Profiling
  • Checklist for new release

API documentation

Documents functions, classes and methods:

• API Documentation
• Index

Release history

Release history

License

Copyright 2013-2017 Calliope contributors listed in AUTHORS

Licensed under the Apache License, Version 2.0 (the “License”); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Next: Introduction