Abstract
In future energy scenarios with a high share of renewable energies within the electricity system, power-to-heat technologies could play a crucial role for achieving the climate goals in the heating sector. District heating systems can integrate volatile wind and photovoltaic energy sources and resolve congestions within the electricity grid, leading to curtailment of renewable electricity generation. This paper presents a design approach for setting up system-beneficial power-to-heat-based district energy systems. Within the scope of the project QUARREE100 an existing district in the provincial town Heide in Northern Germany is examined. A linear investment and unit commitment optimization model is applied. By considering local dynamic emission factors for grid-sourced electricity, which contain information on local wind energy curtailment as well as the emission intensity of the overall electricity generation, a renewable and system-beneficial design can be derived. With this method, the minimal rated power and capacity of energy converter and storage units can be determined to achieve emission reductions with respect to minimum costs. The approach of using different methods for the consideration of the emissions of grid-sourced electricity is analyzed based on different scenarios. By using a dynamic emission factor for grid-sourced electricity, lower emissions with fewer costs can be achieved. It is shown that a dynamic assessment leads to different design decisions and far-reaching deviations in the unit commitment. The results clearly show that a constant emission factor is no longer an option for grid-sourced electricity in urban energy system models.
Highlights
Introduction of the Applied OptimizationMethod and Case StudyFirst, the general model and the mathematical background of the applied method of an investment and unit commitment model are described
The following sections present the results of the comparison of dynamic and constant emission factors for grid-sourced electricity in investment and unit commitment models of urban energy systems
It is shown that a dynamic assessment leads to different design decisions, especially in the local emission factor scenario, and far-reaching differences in the unit commitment, which can be shown by the example of Section 3.3
Summary
Introduction of the Applied OptimizationMethod and Case StudyFirst, the general model and the mathematical background of the applied method of an investment and unit commitment model are described. The problem statement for this energy system investment and unit commitment optimization is: Given are the heat and electricity demand of an urban district, energy converter and storage options and energy commodity sources. The heat and electricity demand are represented by aggregated load profiles, which include grid losses for distribution in case of the heat demand. The technical parameters, such as conversion factors and energy losses, and the economic parameters, such as capital and operation costs, are given for each energy converter and storage unit. The commodity sources are natural gas and electricity from the upstream electricity system Both are characterized by energy-specific costs and an emission factor. The optimization problem is concerned with deciding on how to dimension and how to commit the energy converter and storage units, while minimizing the costs and meeting a given emission limit and finding the solution with minimum emissions
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