Conference Agenda

This study investigates the relationship between energy supply and production processes, with a focus on energy-flexibility. The main goal is to exploit the economic and ecological potential of flexible production facilities in manufacturing. Expanding on this, the research evaluates how optimized factory layouts can influence the integration of renewable energy sources. Our study advances by employing a mathematical optimization model, specifically a Mixed-Integer Linear Programming (MILP) approach. This model aims to assess the correlation between the energy consumption of production processes and the residual load, optimizing what we refer to as the "Relocation Coefficient." It indicates the proximity of the energy usage profile to the residual load, incorporating our use of a linearized version of the Blarke coefficient as the objective function. To illustrate the application of this model, we focus on a specific case study involving an electrolyzer manufacturer. Within their energy-intensive production processes, we specifically analyze the galvanization of components. We consider a period of one month as the scenario, with simulated energy generation data in the vicinity of the production facilities under consideration, with a temporal resolution of 15 minutes. Subsequently, the order volume and layouts can be varied to achieve production optimization, with the Blarke coefficient serving as an evaluation criterion. By systematically examining different layouts and production scenarios, we were able to achieve and demonstrate optimization in the correlation between residual load and energy consumption during production. This optimization signifies an enhancement in the utilization of renewable energy sources.

Hydrogen-based propulsion concepts for aircraft are considered a promising technology towards the decarbonization of aviation. While the development of respective aircraft models is in progress, questions regarding the supply network of green hydrogen are arising. We present a multi-period mixed-integer programming model for the hydrogen supply chain network design problem focusing on the aviation sector. The model minimizes the total network cost by making strategic decisions (e.g. suppliers, locations, capacities, transportation infrastructure) and tactical decisions (e.g. hydrogen flows, storage quantities) at different temporal resolutions. Our model formulation considers the spatially and temporally varying supply and demand of hydrogen, the techno-economic characteristics of hydrogen storage, liquefaction and transportation (e. g., economies of scale), as well as the specific requirements of hydrogen handling (e.g., losses). Model application is illustrated for German airports with local production and hydrogen import options, considering the projected development of the European Hydrogen Backbone pipeline infrastructure. Optimal network designs and results are presented and analyzed for different hydrogen supply and demand scenarios.

Although the expansion of renewable electricity generation has significantly progressed in Europe, the shift to renewable heating technologies has been slower. Heat pumps provide the possibility to exploit synergies between the electricity and heating sectors. As it is imperative to reduce carbon emissions as quickly as possible, one solution can be integrated energy system flexibility options when using heat pumps. This will allow for the utilisation of electricity when there are many renewable energy sources available in the electricity mix, resulting in fewer carbon emissions.

Therefore, the research questions of this work are: How much can the operation of heat pumps reduce carbon emissions and decouple energy demand and supply by making the heating demand of building occupants more flexible, such as through the thermal mass of buildings? Additionally, how do geographical variations, e.g. between Ireland as one of the northern islands of Europe and Germany as a country on the European mainland, affect the potential for carbon emission reductions?

A detailed energy system model for residential buildings in Ireland and Germany is developed using the open-source optimisation framework called Backbone. The model considers typical parameters for residential buildings in both countries to create a building structure and generate endogenous heating demands. The thermal flexibility of building masses will be analysed to shift heating demands based on variable electricity emission factors. By evaluating emission reduction potentials, insights into the path to climate neutrality are gained.