Energie · Gebäude · Umwelt (EGU)
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- 2021 (3) (entfernen)
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- Energiesystemmodellierung (1)
- Multi-Energiesystem (1)
- PIV (1)
- energy system modeling (1)
- modeling tools (1)
- multi-energy system (MES) (1)
- optimization (1)
- sinusoidal varied airflow (1)
- unsteady ventilation (1)
- urban districts (1)
The effects of different unsteady ventilation strategies on flow-structures in a room are investigated and compared to steady ventilation with the same mean exchange rate. For this, whole-field optical flow measurements were executed by means of a particle image velocimetry system (PIV) in a Reynolds-scaled room model in water. In a first series of experiments, sinusoidal varied supply flows with different frequencies were analysed; two equally supplied simple nozzles in the ceiling were used as inlets. The setup was validated by comparing jet velocities with literature values.
Typically, room airflows are investigated with punctual measurement techniques (e.g.
anemometers), which have an impact on the flow field, or with smoke gas experiments. By using PIV, the flow can be analysed without any influence of sensors or stands/traverses and whole-field measurement data with high spatial resolution and detailed information on the flow field can be collected.
Local and time-averaged velocities and standard deviations were calculated for all scenarios. Unsteady conditions were created by a sinusoidal variation of the supply flow rate with frequencies between 0.025 1/s and 0.050 1/s, an offset of about 1.1 m3/h and an amplitude of about ±1.0 m3/h, which leads to a mean exchange rate of 3.5 1/h. Although averaged velocity fields only show slight differences between steady and unsteady conditions, single pictures vary widely. First effects of unsteady ventilation on flow structures can be recognized. Steady structures are destroyed, and velocities change rapidly.
The inlets will be changed to small-scale ceiling-diffusors in future experiments to create more realistic room ventilation conditions. Other types of unsteady supply flows will be implemented, and parameters will be varied. The results of the PIV-measurements can be used to validate CFD simulations and to derive dimensioning rules and application recommendations.
About 75% of the world's energy consumption takes place in cities. Although their large energy consumption attracts a large number of research projects, only a small fraction of them deal with approaches to model energy systems of city districts. These are particularly complex due to the existence of multiple energy sectors (multi-energy systems, MES), different consumption sectors (mixed-use), and different stakeholders who have many different interests.
This contribution is a review of the characteristics of energy system models and existing modeling tools. It evaluates current studies and identifies typical characteristics of models designed to optimize MES in mixed-use districts. These models operate at a temporal resolution of at least 1 h, follow either bottom-up or hybrid analytical approaches and make use of mixed-integer programming, linear or dynamic.
These characteristics were then used to analyze minimum requirements for existing modeling tools. Thirteen of 145 tools included in the study turned out to be suitable for optimizing MES in mixed-use districts. Other tools where either created for other fields of application (12), do not include any methodology of optimization (39), are not suitable to cover city districts as a geographical domain (44), do not include enough energy or demand sectors (20), or operate at a too coarse temporal resolution (17). If additional requirements are imposed, e.g. the applicability of non-financial assessment criteria and open source availability, only two tools remain.
Overall it can be stated that there are very few modeling tools suitable for the optimization of MES in mixed-use districts.
Rund 75 % des weltweiten Energieverbrauchs findet innerhalb urbaner Energiesysteme statt. Solche Systeme beinhalten mehrere Energiesektoren (Elektrizität, Wärme, Kälte, …), Verbrauchssektoren (Wohnen, Gewerbe, Industrie, Landwirtschaft, Mobilität, …) und Interessensgruppen und sind deshalb besonders komplex. Durch den Einsatz von Methoden der Energiesystemmodellierung können diese komplexen Systeme simuliert, analysiert und optimiert werden. Mit Simulationsmodellen können Kosten, Emissionen und verschiedene andere Systemparameter prognostiziert werden. Mithilfe von Optimierungsalgorithmen können Technologien miteinander verglichen, Anlagen dimensioniert und Betriebsweisen optimiert werden. Die Erkenntnisse aus Energiesystemmodellen können zur Einhaltung verschiedener politischer und sozialer Ziele, wie beispielsweise die Reduktion von Treibhausgasemissionen, der Bedarf nach kostengünstiger Energieversorgung oder auch die Stärkung der regionalen Wirtschaft, beitragen.
Im Projekt R2Q werden Ansätze der Energiesystemmodellierung für den Einsatz in der Planung urbaner Energiesysteme aufgearbeitet, angepasst und für städteplanerische Prozesse verfügbar gemacht. In ersten Modelldurchläufen für ein Testgebiet in Herne konnte durch die Kombination verschiedener Technologien eine rechnerische Minimierung der monetären Kosten um 19 % bei gleichzeitiger Reduktion der CO2-Emissionen um 36 % ermittelt werden. Durch ein emissionsoptimiertes Szenario können die CO2-Emissionen um 47 % reduziert werden, was jedoch mit einer Steigerung der Kosten um 29 % einhergeht.