Open multi-energy system models are becoming increasingly more important for transitioning into a sustainable energy system. Open-source energy modelling tools like SpineOpt can provide such a transparent and flexible framework for performing complex and realistic case studies. In this paper, a short-term electricity and heat dispatch model with different types of Combined Heat and Power units and Power-to-Heat systems is implemented and simulated, using SpineOpt. The model’s performance and efficacy is evaluated against the commercial equation-based optimisation library GUROBIPY with good results. The model and the data are made openly available.

The Spine Toolbox is open-source software for defining, managing, simulating and optimising energy system models. It gives the user the ability to collect, create, organise, and validate model input data, execute a model with selected data and finally archive and visualise results/output data. Spine Toolbox has been designed and developed to support the creation and execution of multivector energy integration models. It conveniently facilitates the linking of models with different scopes, or spatio-temporal resolutions, through the user interface. The models can be organised as a direct acyclic graph and efficiently executed through the embedded workflow management engine. The software helps users to import and manage data, define models and scenarios and orchestrate projects. It supports a self-contained and shareable entity-relationship data structure for storing model parameter values and the associated data. The software is developed using the latest Python environment and supports the execution of plugins. It is shipped in an installation package as a desktop application for different operating systems.

The transition towards more sustainable energy systems poses new requirements on energy system models. New challenges include representing more uncertainties, including short-term detail in long-term planning models, allowing for more integration across energy sectors, and dealing with increased model complexities. SpineOpt is a flexible, open-source, energy system modelling framework for performing operational and planning studies, consisting of a wide spectrum of novel tools and functionalities. The most salient features of SpineOpt include a generic data structure, flexible temporal and spatial structures, a comprehensive representation of uncertainties, and model decomposition capabilities to reduce the computational complexity. These enable the implementation of highly diverse case studies. SpineOpt's features are presented through several publicly -available applications. An illustrative case study presents the impact of different temporal resolutions and stochastic structures in a co-optimised electricity and gas network. Using a lower temporal resolution in different parts of the model leads to a lower computational time (44%-98% reductions), while the total system cost varies only slightly (-1.22-1.39%). This implies that modellers experiencing computational issues should choose a high level of temporal accuracy only when needed.

Lack of openly available power system data due to market regulations or corporate policies hinders the development of models for power system planning and operation studies. This work presents an open source model of the Nordic synchronous area (the Nordic490 model), which can be used for power flow calculations. To reach an accurate modelling of the Nordic transmission grid, the production and consumption time series are disaggregated based on demographics, and the values of certain network parameters and generation characteristics are investigated, by crosschecking various data sources. The resulting model is validated using open market data. 

In this paper, we present the results from the development and the simulation of a hydro power model for Sweden and Norway, using SpineOpt software and openly available data. We employ (i) hydrological and market data from the Nordic region and (ii) the abstract representation of the multi-vector modelling and simulation engine SpineOpt, to compile an open-source model of a large portion of the hydro power plants of the Nordic region, for conducting realistic hydro power generation studies. We place the hydro power system operation within the structuring of the Nordic electricity market and study the effect that different objectives have on the operational results. By employing the SpineOpt functionalities for automating the transformation of the temporal resolution of the model, we explore the trade-of between its computational burden and accuracy.

Network reduction techniques are very useful for taming the complexity of simulating large interconnected power systems. In this paper, we present the implementation of a tool that performs a multi-area spatial network aggregation based on the generalized Radial Equivalent Independent (REI) methodology. The tool is integrated in Spine, an open source energy modelling framework currently under development. The main objective of Spine is to enable open, practical, flexible and realistic planning of future European energy grids. The validity and the efficacy of the reduction tool is investigated through a series of power flow scenarios for various test networks.

When analyzing power systems, it is often desirable to visualize the network of buses and branches. Here, a new algorithm for producing 2-D network layouts is proposed. The method consists of two steps: first, a matrix of desired distances between all bus-pairs is computed based on base voltages and branch reactances and, second, coordinates that minimize the errors between desired and actual distances are found. The parallelization used in the latter step is particularly beneficial for interpreted languages; it is shown that layouts for relatively large systems (a few thousand buses) can be produced within seconds on a standard laptop computer using Python or Matlab. Predefined coordinates for selected buses can optionally be given as input. This can be useful, e.g., when one wants to retain some geographical aspects of the system or wish to compare a full and reduced network model. Although the focus here is on power systems, the algorithm can also be used for other types of networks.

This paper presents the development and simulation of hydro power models in the open source energy modelling framework Spine. We study the market-based hourly operation of the Skellefte river in the Swedish hydro power system using the abstract representation of \textit{Spine Model}, in order to employ and demonstrate its available functionalities, focusing on the automated handling of the temporal resolution of the optimization model. The Spine temporal block is used for automating the transformation of the temporal resolution of the model in different time intervals, as well as the manipulation of various modelling parameters. After the mathematical formulation of the optimization problem and the detailed analysis of the modelling steps in Spine, various results are extracted discussing the added value of Spine.