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Open AccessArticle

Backbone—An Adaptable Energy Systems Modelling Framework

1
Smart Energy and Transport Solutions, VTT Technical Research Centre of Finland Ltd, FI-02044 VTT Espoo, Finland
2
School of Electrical and Electronic Engineering, University College Dublin, Belfield, Dublin 4, Ireland
*
Author to whom correspondence should be addressed.
Energies 2019, 12(17), 3388; https://doi.org/10.3390/en12173388
Received: 13 June 2019 / Revised: 16 August 2019 / Accepted: 24 August 2019 / Published: 2 September 2019
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. View Full-Text
Keywords: energy systems; investment planning; modelling tools; modelling framework; open source; power systems; stochastic programming; unit commitment; variable renewable energy energy systems; investment planning; modelling tools; modelling framework; open source; power systems; stochastic programming; unit commitment; variable renewable energy
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Helistö, N.; Kiviluoma, J.; Ikäheimo, J.; Rasku, T.; Rinne, E.; O’Dwyer, C.; Li, R.; Flynn, D. Backbone—An Adaptable Energy Systems Modelling Framework. Energies 2019, 12, 3388.

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