Ein Kennzahlensystem zur systematischen Bewertung von Simulationsergebnissen als Grundlage zur energieeffizienten Industrieclusteroptimierung
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen
Beitragende
Abstract
Current crises such as globally disrupted supply chains, rising energy prices and, of course, climate change demonstrate once again how important it is to use resources, and energy in particular, efficiently. Industrial symbiosis (IS) aims at increasing resource efficiency by means of energy-material exchange relationships within Eco-Industrial Parks (EIP) and thus contributes to the reduction of the problems mentioned above. In the literature, there is a variety of approaches to investigate and optimize IS measures. These differ significantly in terms of their scope of consideration and the level of detail with which the individual processes are analyzed or planned. Due to the complexity of the interrelationships within an EIP, simulations are helpful. However, these are usually designed for a specific EIP and cannot be applied to other EIPs without further effort. In the context of successive EIP projects at the TU Dresden, simulation models and an automated optimization of the exchange relationships are therefore being developed for application to different EIPs. The evaluation of simulation results is essential for optimization. For this reason, this paper presents a method for the systematic evaluation of simulation runs of possible constellations of symbioses. In this context, different focus areas are also taken into consideration by weighting the evaluation parameters.
Details
Originalsprache | Deutsch |
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Titel | Logistics Journal: Proceedings |
Band | 2022 |
Publikationsstatus | Veröffentlicht - 2022 |
Peer-Review-Status | Nein |
Externe IDs
ORCID | /0000-0002-1484-7187/work/142243127 |
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Scopus | 85141049697 |
Schlagworte
Ziele für nachhaltige Entwicklung
ASJC Scopus Sachgebiete
Schlagwörter
- Eco-Industrial Park, Industrial Cluster Optimization, Industrial Symbiosis, Simulation