Due to the high share of industry in total electricity consumption, industrial demand-side management can make a relevant contribution to the stability of power systems. At the same time, companies get the opportunity to reduce their electricity procurement costs by taking advantage of increasingly fluctuating prices on short-term electricity markets, the provision of system services on balancing power markets, or by increasing the share of their own consumption from on-site generated renewable energy. Demand-side management requires the ability to react flexibly to the power supply situation without negatively affecting production targets. It also means that the management and operation of production must consider not only production-related parameters but also parameters of energy availability, which further increase the complexity of decision-making. Although simulation studies are a recognized tool for supporting decision-making processes in production and logistics, the simultaneous simulation of material and energy flows has so far been limited mainly to issues of energy efficiency as opposed to energy flexibility, where application-oriented experience is still limited. We assume that the consideration of energy flexibility in the simulation of manufacturing systems will amplify already known pitfalls in conducting simulation studies. Based on five representative industrial use cases, this article provides practitioners with application-oriented experiences of the coupling of energy and material flows in simulation modeling of energy-flexible manufacturing, identifies challenges in the simulation of energy-flexible production systems, and proposes approaches to face these challenges. Seven pitfalls that pose a particular challenge in simulating energy-flexible manufacturing have been identified, and possible solutions and measures for avoiding them are shown. It has been found that, among other things, consistent management of all parties involved, early clarification of energy-related, logistical, and resulting technical requirements for models and software, as well as the application of suitable methods for validation and verification are central to avoiding these pitfalls. The identification and characterization of challenges and the derivation of recommendations for coping with them can raise awareness of typical pitfalls. This paper thus helps to ensure that simulation studies of energy-flexible production systems can be carried out more efficiently in the future.
Die optimierte Betriebsweise von industriellen Energiesystemen ist eine Schlüsseltechnologie, um signifikante Kosteneinsparpotenziale durch Steigerung der Energieeffizienz und -flexibilität zu heben. Weil dabei eine Vielzahl dynamischer und stochastischer Einflüsse berücksichtigt werden müssen, spielt die Simulation des Energiesystems eine entscheidende Rolle. Zur Evaluierung unterschiedlicher Betriebsoptimierungsverfahren wird ein simulationsgestütztes Framework vorgestellt, welches bei KI (Künstliche Intelligenz)-Algorithmen unter anderem für das Anlernen mit synthetischen Daten verwendet werden kann. The optimized operation of industrial energy systems is a key technology to unlock significant cost savings by increasing energy efficiency and flexibility. Since a variety of dynamic and stochastic influences must be considered, the simulation of the energy system plays a decisive role. A simulation-based framework is presented for evaluating various operational optimization methods, which can also be used for learning based on synthetic data with AI (artificial intelligence) algorithms.
Kurzfassung Der zunehmende Anteil erneuerbarer Energien an der Stromerzeugung stellt die Energieversorgung in Deutschland vor große Herausforderungen. Insbesondere steigt durch den Ausbau regenerativer Energieträger wie Sonnen- und Windkraft die Volatilität in der Stromerzeugung. Durch Ausnutzung dieser volatilen Energieverfügbarkeit bietet sich produzierenden Unternehmen die Möglichkeit, Energiekosten durch einen an die Erzeugungssituation angepassten Energiebezug einzusparen. Wesentlich für die Umsetzung einer energieflexiblen Betriebsweise der Versorgungs- und Produktionstechnik ist die Erfassung und Bewertung bestehender Flexibilitätspotenziale. In diesem Beitrag wird eine quantitative Erfassungs- und Bewertungsmethodik für technische Energieflexibilitätspotenziale industrieller Anlagen und Fabriken sowie ein dazugehöriges praxisorientiertes Softwaretool präsentiert.
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