4.5 Article

Backbone-An Adaptable Energy Systems Modelling Framework

Journal

ENERGIES
Volume 12, Issue 17, Pages -

Publisher

MDPI
DOI: 10.3390/en12173388

Keywords

energy systems; investment planning; modelling tools; modelling framework; open source; power systems; stochastic programming; unit commitment; variable renewable energy

Categories

Funding

  1. Academy of Finland project Improving the value of variable and uncertain power generation in energy systems (VaGe), New Energy programme [284973]
  2. Strategic Research Council at the Academy of Finland, project Transition to a resource efficient and climate neutral electricity system (EL-TRAN) [314319]
  3. Jenny and Antti Wihuri Foundation
  4. European Union Horizon 2020 research and innovation programme [773505]
  5. Science Foundation Ireland under the Strategic Partnership Programme [SFI/15/SPP/E3125]
  6. Academy of Finland (AKA) [284973, 284973] Funding Source: Academy of Finland (AKA)

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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.

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