Both rising and more volatile energy prices are strong incentives for manufacturing companies to become more energy-efficient and flexible. A promising approach is the intelligent control of Industrial Energy Supply Systems (IESS), which provide various energy services to industrial production facilities and machines. Due to the high complexity of such systems widespread conventional control approaches often lead to suboptimal operating behavior and limited flexibility. Rising digitization in industrial production sites offers the opportunity to implement new advanced control algorithms e. g. based on Mixed Integer Linear Programming (MILP) or Deep Reinforcement Learning (DRL) to optimize the operational strategies of IESS.This paper presents a comparative study of different controllers for optimized operation strategies. For this purpose, a framework is used that allows for a standardized comparison of rule-, model- and data-based controllers by connecting them to dynamic simulation models of IESS of varying complexity. The results indicate that controllers based on DRL and MILP have a huge potential to reduce energy-related cost of up to 50% for less complex and around 6% for more complex systems. In some cases however, both algorithms still show unfavorable operating behavior in terms of non-direct costs such as temperature and switching restrictions, depending on the complexity and general conditions of the systems.

The increasing share of volatile, renewable energies, such as wind and solar power, leads to challenges in the stabilization of power grids and requires more flexibility in future energy systems. This article addresses the flexibilization of the consumer side and presents a simulation-based method for the technical and economic investigation of energy flexibility measures in industrial steam supply systems. The marketing of three different energy-flexibility measures—bivalence, inherent energy storage and adjusting process parameters—both at the spot market and at the balancing power market, are investigated from a technical as well as an economic point of view. Furthermore, the simulation-based methodology also considers pressure and temperature fluctuation induced by energy-flexibility measures. First, different energy-flexibility measures for industrial steam supply systems are introduced. Then, the physical modeling of the steam generation, distribution, and consumption as well as measure-specific control strategies will be discussed. Finally, the methodology is applied to a steam supply system of a chemical company. It is shown that the investigated industrial steam supply system shows energy-flexibility potentials up to 10 MW at peak and an annual average of 5.6 MW, which highly depend on consumer behavior and flexibility requirements.

Industrial companies are undergoing a transformation to decrease energy costs and reduce emissions. The integration of renewables, sector coupling technologies, and industrial waste heat lead to complex interconnected industrial energy systems. As district heating systems play a decisive role for the integration of industrial waste heat in the building sector, barriers must be analyzed to overcome the gap between waste heat potential and waste heat use. Although data from production systems and their on-site energy supply are becoming available in the ongoing process of digitization, information deficits can be identified as one of the main barriers to couple industrial energy systems with district heating. We present a data-based methodology to evaluate the potential of industrial energy systems for connecting to district heating systems. Data from production systems, energy converters, thermal networks and necessary parameters of district heating systems are merged into a data model to determine a cascaded heat merit order and indicators for the energetic, economic and ecological potential. To set up the cascaded heat merit order, an algorithm for balancing complex industrial energy systems is integrated within the data model. In a case study, we apply the methodology to data of an industrial site. Besides increasing transparency through visualization of the cascaded heat merit order and corresponding indicators, the results show a base load potential of up to 0.8 MW over a year.

In der Online-Zeitschrift für Forschung und Entwicklung in der Produktion – wt Werkstattstechnik online – werden die aktuellsten Forschungsergebnisse aus Wissenschaft, Technischer Hochschule und Industrie veröffentlicht - praxisbezogen und zukunftsorientiert. Die wt Werkstattstechnik online erscheint inklusive neun produktionsspezifischen Ausgaben pro Jahr unter der Internetadresse www.werkstattstechnik.de. Die in der wt Werkstattstechnik veröffentlichten Fachaufsätze sind wissenschaftlich-methodisch aufbereitet und grundsätzlich Erstveröffentlichungen. Viele Fachaufsätze sind peer-reviewed: von Experten auf diesem Gebiet – anonym sowie unabhängig von den Autoren – wissenschaftlich begutachtet und freigegeben. Die wt Werkstattstechnik online ist Organ der VDI-Gesellschaft Produktion und Logistik (GPL) sowie der wissenschaftlichen Gesellschaft für Produktionstechnik (WGP). Schwankende Strompreise erhöhen den Bedarf an Systemen zur elektrischen Lastprognose für Industrieunternehmen. Zur Bereitstellung eines Prognoseservice sind Kenntnisse über gängige Methoden, die spezifischen Anforderungen und die Einflussfaktoren erforderlich. Je nach Anwendung erzielen Prognosemethoden unterschiedliche Genauigkeiten. Dieser Beitrag beschreibt ein Vorgehen, das mit einem Benchmark die Genauigkeit einer Prognosemethode evaluiert, so dass diese einheitlich mit anderen Methoden verglichen werden kann. Fluctuating electricity prices increase the need for electrical load forecasting systems for industrial companies. To provide a forecasting service, knowledge of common methods, the specific requirements and influencing factors is required. Depending on the application, forecasting methods achieve different prediction performance indicators. This contribution presents an approach that uses a benchmark to evaluate the accuracy of a forecasting method and compare it consistently with other methods. Durch die Dekarbonisierung industrieller Produktionssysteme und die Stabilisierung der Stromnetze wird die Bereitstellung von Energieflexibilität immer wichtiger. Der Energiebedarf elektrisch betriebener Kompressionskältemaschinen (KKM) kann in Kombination mit thermischen Kältespeichern auf die fluktuierende Erzeugung von erneuerbaren Energien angepasst werden und somit Energieflexibilität bereitstellen. Diese Arbeit bewertet die Funktionalität eines energieeffizienten und energieflexiblen Kältedemonstrators, der diesen Anwendungsfall abbilden soll. The decarbonization of industrial production systems and stabilization of electricity grids increases the importance of energy flexibility. Electrically operated compression chillers (CCM) can be adapted to the fluctuating generation of renewable energies in combination with a thermal cold storage to provide energy flexibility. This work evaluates the functionality of a laboratory-scale energy-flexible refrigeration demonstrator designed to replicate this use case. In der metallverarbeitenden Industrie wächst mit steigenden Qualitätsanforderungen die Bedeutung der Bauteilreinigung und -trocknung in der Wertschöpfungskette. Vor dem Hintergrund steigender Energiepreise und klimapolitischer Ziele besteht die Motivation, die Energieeffizienz der Bauteiltrocknung zu steigern. Zu diesem Zweck sollen neben einem Referenzfall die Infrarot- und die Induktionstrocknung als alternative Trocknungstechnologien untersucht sowie deren Energieeinsparpotenzial ermittelt werden. Higher quality requirements in the metal-processing industry are increasing the importance of processes such as parts cleaning and drying along the value chain. Rising energy prices and climate policy goals provide an incentive to improve energy efficiency in parts drying. This paper assesses infrared and induction drying as alternative drying technologies aginst a reference case, and determines the energy-saving potentials of these technologies. Die Mikrotextur von Oberflächen im tribologischen Kontakt beeinflusst das Tribosystem und kann durch die Stellgrößen beim Drehen eingestellt werden. Die begrenzte Dynamik der Werkzeugmaschine beschränkt dies jedoch und erlaubt nur eine Einstellung über die kinematische Rauheit. In diesem Beitrag wird die Auslegung eines neuartigen piezoelektrischen Werkzeugsystems vorgestellt. Es ermöglicht eine hochdynamische Positionierung von Zerspanungswerkzeugen zur Oberflächentexturierung durch plastische Verformung. The microtexture of surfaces in tribological contact influences the tribosystem and can be adjusted by the actuating variables during turning. However, the limited dynamics of the machine tool restrict this and usually only allow adjustment by kinematic roughness. This work presents the design of a novel piezoelectric tool system that enables highly dynamic positioning of cutting tools for surface texturing by plastic deformation. Um thermische Spritzschichten mit erhöhter Haftfestigkeit zu realisieren, erfolgte am Institut für Spanende Fertigung (ISF) der Technischen Universität Dortmund und dem Institut für Werkstoffkunde (IW) der Leibniz Universität Hannover die Entwicklung einer innovativen Verfahrenskombination. Darauf aufbauend wurde untersucht, ob die Schichteigenschaften durch einen zusätzlichen Prozessschritt weiter optimierbar sind, um zukünftig Verschleißschutzbeschichtungen ohne eine Substrataktivierung durch Strahlen zu ermöglichen. To enable thermal sprayed coatings with increased adhesion, the Institute of Machining Technology (ISF) of TU Dortmund University together with the Institute of Materials Science (IW) of Leibniz Universität Hannover developed an innovative process combination. This serves as a basis for investigating whether the coating properties can be further optimized by an additional process step to allow for the...

Germany has become one of the leading players in the transformation of the electricity sector, now having up to 42% of electricity coming from renewable sources. However, the transformation of the heating sector is still in its infancy, and especially the provision of industrial process heating is highly dependent on unsustainable fuels. One of the most promising heating technologies for renewable energies is power-to-heat, especially heat pump technology, as it can use renewable electricity to generate heat efficiently. This research explores the economic and technical boundary conditions regarding the integration of heat pumps into existing industrial thermohydraulic heating and cooling networks. To calculate the optimum design and control of heat pumps, a mixed-integer linear programming model (MILP) is developed. The model seeks the most cost-efficient configuration of heat pumps and stratified thermal storage tanks. Additionally, it optimizes the operation of all energy converters and stratified thermal storage tanks to meet a specified heating and cooling demand over one year. The objective function is modeled after the net present value (NPV) method and considers capital expenditures (costs for heat pumps and stratified thermal storage tanks) and operational expenditures (electricity costs and costs for conventional heating and cooling). The comparison of the results via a simulation model reveals an accuracy of more than 90%.