Suchergebnisse

The exit from nuclear and fossil-fuel energy and the turbulent developments in the technology sector are increasingly influencing the factory's energy system. Its design can no longer be based on a quasi-constant environment. The short decision-making cycles of politics as well as the rapid development cycles of technologies demand an energy system which has a corresponding agility so that the factory can be operated economically in the future in the field of energy. This initial situation leads to the research question of how an agile energy supply system can be designed in factories. An answer to this question is provided by the method for designing energy-agile energy supply systems in factories. The method is based on the basic concepts of agility of factories and transfers these approaches to the energy supply system. The interdependencies between the energy supply, the used production technology and the products are being discussed with respect to the agility drivers and the agility enabling actions. The method is divided into five steps. In the first step, the direct and indirect agility drivers are analysed. This analysis involves the characterization and evaluation of the agility drivers from the individual factory perspective. In addition to a prioritization of the agility drivers, a definition of conversion limits and their probability distribution is required. In the following step, agility enabling options are derived. These options for action are generally formulated and assessed on the basis of the agility criteria. A comparison of individual agility driver assessments and possible agility enabling options creates a package of measures from a company perspective, which will be assessed below. The third step of the method involves modelling. An agent-based modelling approach is developed that allows the energy system to be mapped generically. Individual, special control algorithms, for example for storage control, can be added as needed. With the help of Monte Carlo simulation, in the fourth step, the evaluation variables are determined as a function of agility drivers and agility enabling options, taking uncertainties into account. The subsequent regression analysis allows to determine the advantage of an agility enabling action. In the final step of the method, conclusions can be drawn as to when and to what extent agility enabling options should be used.

Die Energiewende sowie die turbulenten Entwicklungen im Technologiesektor beeinflussen zunehmend das Energiesystem der Fabrik. Die kurzen Entscheidungszyklen der Politik sowie die schnellen Entwicklungszyklen von Technologien fordern von dem Energiesystem eine entsprechende Wandlungsfähigkeit, damit die Fabrik in Zukunft in dem Bereich der Energie wirtschaftlich betrieben werden kann. Diese Ausgangssituation führt zu der Forschungsfrage, wie ein wandlungsfähiges Energieversorgungssystem in Fabriken gestaltet werden kann. Eine Antwort auf diese Frage bietet die Methode zur Gestaltung energetisch wandlungsfähiger Energieversorgungssysteme in Fabriken. Die Methode beruht auf den Grundkonzepten der Wandlungsfähigkeit von Fabriken und überträgt diese Ansätze auf das Energieversorgungssystem. Fokussiert werden die Wirkzusammenhänge zwischen der Energieversorgung und der eingesetzten Produktionstechnik im Zusammenspiel mit Wandlungstreibern und wandlungsbefähigenden Handlungsoptionen. Die Methode gliedert sich in fünf Schritte. Im ersten Schritt werden die Wandlungstreiber analysiert. Diese Analyse umfasst die Charakterisierung und Bewertung der Wandlungstreiber aus der individuellen Fabriksicht. Im darauffolgenden Schritt werden wandlungsbefähigende Handlungsoptionen abgeleitet. Diese Handlungsoptionen werden allgemein formuliert und anhand der Kriterien für Wandlungsfähigkeit bewertet. Durch die Gegenüberstellung von individuellen Wandlungstreibereinschätzungen und möglichen wandlungsbefähigenden Handlungsoptionen entsteht ein Maßnahmenbündel aus Unternehmensperspektive. Der dritte Schritt der Methode umfasst die Modellerstellung. Es wird ein agentenbasierter Modellierungsansatz entwickelt, der es erlaubt, das Energiesystem generisch abzubilden. Individuelle, spezielle Steuerungsalgorithmen, beispielsweise zur Speichersteuerung, können bei Bedarf ergänzt werden. Mit Hilfe der Monte-Carlo-Simulation werden im vierten Schritt die Bewertungsgrößen in Abhängigkeit von Wandlungstreibern und wandlungsbefähigenden Handlungsoptionen unter Berücksichtigung von Unsicherheiten ermittelt. Die anschließende Regressionsanalyse erlaubt die Untersuchung der Vorteilhaftigkeit einer wandlungsbefähigenden Handlungsoption. Daraus lassen sich im letzten Schritt der Methode Schlüsse ziehen, zu welchem Zeitpunkt in welchem Umfang wandlungsbefähigende Handlungsoptionen einzusetzen sind. ; The exit from nuclear and fossil-fuel energy and the turbulent developments in the technology sector are increasingly influencing the factory's energy system. Its design can no longer be based on a quasi-constant environment. The short decision-making cycles of politics as well as the rapid development cycles of technologies demand an energy system which has a corresponding agility so that the factory can be operated economically in the future in the field of energy. This initial situation leads to the research question of how an agile energy supply system can be designed in factories. An answer to this question is provided by the method for designing energy-agile energy supply systems in factories. The method is based on the basic concepts of agility of factories and transfers these approaches to the energy supply system. The interdependencies between the energy supply, the used production technology and the products are being discussed with respect to the agility drivers and the agility enabling actions. The method is divided into five steps. In the first step, the direct and indirect agility drivers are analysed. This analysis involves the characterization and evaluation of the agility drivers from the individual factory perspective. In addition to a prioritization of the agility drivers, a definition of conversion limits and their probability distribution is required. In the following step, agility enabling options are derived. These options for action are generally formulated and assessed on the basis of the agility criteria. A comparison of individual agility driver assessments and possible agility enabling options creates a package of measures from a company perspective, which will be assessed below. The third step of the method involves modelling. An agent-based modelling approach is developed that allows the energy system to be mapped generically. Individual, special control algorithms, for example for storage control, can be added as needed. With the help of Monte Carlo simulation, in the fourth step, the evaluation variables are determined as a function of agility drivers and agility enabling options, taking uncertainties into account. The subsequent regression analysis allows to determine the advantage of an agility enabling action. In the final step of the method, conclusions can be drawn as to when and to what extent agility enabling options should be used.

The industrial energy supply of the production with direct current offers the chances of higher energy efficiency, better integration of generative energy and at the same time robust power supply. In addition to the technological challenges for electrical devices, an intelligent grid management, which regulates the load flow between the participants, is crucial. The distributed grid management supports a scalable, modular network with a hierarchical structure. The paper defines a direct current (DC) grid management by the different roles of every participant. Each role provides special services, needed for a stable grid operation. These services are described and a simulative analysis is carried out. The simulation shows that network stability is ensured and at the same time, the possibility of optimizing the operation management is maintained. The presented results are part of the DC-INDUSTRIE research project, funded by the German government.