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Modelling Grid Constraints in a Multi-Energy Municipal Energy System Using Cumulative Exergy Consumption Minimisation

Authors: Lukas Kriechbaum; Philipp Gradl; Romeo Reichenhauser; Thomas Kienberger;

Modelling Grid Constraints in a Multi-Energy Municipal Energy System Using Cumulative Exergy Consumption Minimisation

Abstract

Efficiency measures and the integration of renewable energy sources are key to achieving a sustainable society. The cumulative exergy consumption describes the resource consumption of a product from the raw material to the final utilisation. It includes the exergy expenses for energy infrastructure as well as the imported energy. Since consumers and renewable potentials are usually in different locations, grid restrictions and energy flows have a significant impact on the optimal energy system design. In this paper we will use cumulative exergy minimisation together with load flow calculations to determine the optimal system design of a multi-cell municipal energy system. Two different load flow representations are compared. The network flow model uses transmission efficiencies for heat, gas and electricity flows. The power flow representation uses a linear DC approximated load flow for electricity flows and a MILP (mixed integer linear programming) representation for heat and gas flows to account for the nonlinear pressure loss relation. Although both representations provide comparable overall results, the installed capacities in the individual cells differ significantly. The differences are greatest in well meshed cells, while they are small in stub lines.

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Keywords

municipal energy systems, cumulative-exergy consumption minimisation, Technology, T, multi-energy systems, optimal power flow, energy systems optimisation, energy-system design, exergy analysis

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
gold