Backbone—An Adaptable Energy Systems Modelling Framework

Niina Helistö, Juha Kiviluoma, Jussi Ikäheimo, Topi Rasku, Erkka Rinne, Ciara O’Dwyer, Ran Li and Damian Flynn
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Niina Helistö: Smart Energy and Transport Solutions, VTT Technical Research Centre of Finland Ltd, FI-02044 VTT Espoo, Finland
Juha Kiviluoma: Smart Energy and Transport Solutions, VTT Technical Research Centre of Finland Ltd, FI-02044 VTT Espoo, Finland
Jussi Ikäheimo: Smart Energy and Transport Solutions, VTT Technical Research Centre of Finland Ltd, FI-02044 VTT Espoo, Finland
Topi Rasku: Smart Energy and Transport Solutions, VTT Technical Research Centre of Finland Ltd, FI-02044 VTT Espoo, Finland
Erkka Rinne: Smart Energy and Transport Solutions, VTT Technical Research Centre of Finland Ltd, FI-02044 VTT Espoo, Finland
Ciara O’Dwyer: School of Electrical and Electronic Engineering, University College Dublin, Belfield, Dublin 4, Ireland
Ran Li: School of Electrical and Electronic Engineering, University College Dublin, Belfield, Dublin 4, Ireland
Damian Flynn: School of Electrical and Electronic Engineering, University College Dublin, Belfield, Dublin 4, Ireland

Energies, 2019, vol. 12, issue 17, 1-34

Abstract: Backbone represents a highly adaptable energy systems modelling framework, which can be utilised to create models for studying the design and operation of energy systems, both from investment planning and scheduling perspectives. It includes a wide range of features and constraints, such as stochastic parameters, multiple reserve products, energy storage units, controlled and uncontrolled energy transfers, and, most significantly, multiple energy sectors. The formulation is based on mixed-integer programming and takes into account unit commitment decisions for power plants and other energy conversion facilities. Both high-level large-scale systems and fully detailed smaller-scale systems can be appropriately modelled. The framework has been implemented as the open-source Backbone modelling tool using General Algebraic Modeling System (GAMS). An application of the framework is demonstrated using a power system example, and Backbone is shown to produce results comparable to a commercial tool. However, the adaptability of Backbone further enables the creation and solution of energy systems models relatively easily for many different purposes and thus it improves on the available methodologies.

Keywords: energy systems; investment planning; modelling tools; modelling framework; open source; power systems; stochastic programming; unit commitment; variable renewable energy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

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