Bottecchia, L., Lubello, P., Zambelli, P., Carcasci, C., & Kranzl, L. (2021). The Potential of Simulating Energy Systems: The Multi Energy Systems Simulator Model. Energies, 14(18), Article 5724. https://doi.org/10.3390/en14185724
E370-03 - Forschungsbereich Energiewirtschaft und Energieeffizienz
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Journal:
Energies
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ISSN:
1996-1073
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Date (published):
11-Sep-2021
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Number of Pages:
26
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Publisher:
MDPI
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Peer reviewed:
Yes
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Keywords:
Electrical and Electronic Engineering; Control and Optimization; Renewable Energy; Energy Engineering and Power Technology; Energy; Engineering; Sustainability and the Environment
en
Abstract:
Energy system modelling is an essential practice to assist a set of heterogeneous stakeholders in the process of defining an effective and efficient energy transition. From the analysis of a set of open-source energy system models, it emerged that most models employ an approach directed at finding the optimal solution for a given set of constraints. On the contrary, a simulation model is a representation of a system used to reproduce and understand its behaviour under given conditions without seeking an optimal solution. In this paper, a new open-source energy system model is presented. Multi Energy Systems Simulator (MESS) is a modular, multi-energy carrier, multi-node model that allows the investigation of non optimal solutions by simulating an energy system. The model was built for urban level analyses. However, each node can represent larger regions allowing wider spatial scales to be represented as well. In this work, the tool’s features are presented through a comparison between MESS and Calliope, a state of the art optimization model, to analyse and highlight the differences between the two approaches, the potentialities of a simulation tool and possible areas for further development. The two models produced coherent results, showing differences that were tracked down to the different approaches. Based on the comparison conducted, general conclusions were drawn on the potential of simulating energy systems in terms of a more realistic description of smaller energy systems, lower computational times and increased opportunity for participatory processes in planning urban energy systems.