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Decomposition of a Cooling Plant for Energy Efficiency Optimization Using OptTopo

2022 , Thiele, Gregor , Johanni, Theresa , Sommer, David , Krüger, Jörg

The operation of industrial supply technology is a broad field for optimization. Industrial cooling plants are often (a) composed of several components, (b) linked using network technology, (c) physically interconnected, and (d) complex regarding the effect of set-points and operating points in every entity. This leads to the possibility of overall optimization. An example containing a cooling tower, water circulations, and chillers entails a non-linear optimization problem with five dimensions. The decomposition of such a system allows the modeling of separate subsystems which can be structured according to the physical topology. An established method for energy performance indicators (EnPI) helps to formulate an optimization problem in a coherent way. The novel optimization algorithm OptTopo strives for efficient set-points by traversing a graph representation of the overall system. The advantages are (a) the ability to combine models of several types (e.g., neural networks and polynomials) and (b) an constant runtime independent from the number of operation points requested because new optimization needs just to be performed in case of plant model changes. An experimental implementation of the algorithm is validated using a simscape simulation. For a batch of five requests, OptTopo needs 61 (Formula presented.) while the solvers Cobyla, SDPEN, and COUENNE need 0.3 min, 1.4 min, and 3.1 min, respectively. OptTopo achieves an efficiency improvement similar to that of established solvers. This paper demonstrates the general feasibility of the concept and fortifies further improvements to reduce computing time.

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Multi-disciplinary strategic research agenda for ICT-enabled energy efficiency

2012 , Ellis, Keith , Hassan, Tarek

Das EU-geförderte Projekt REViSITE (Roadmap Enabling Vision and Strategy in ICT-Enabled Energy Efficiency) identifiziert branchenübergreifende Synergien m Verständnis, welche Technologien zur Nachhaltigkeit beitragen. Zudem werden branchenübergreifend Forschungsprioritäten identifiziert aus den Bereichen Stromnetz, Gebäude, Produktion und Beleuchtung.

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Energy Efficiency Optimization using AutomationML modeling and an EnPI methodology

2019 , Thiele, Gregor , Khorsandi, Niloufar , Krüger, Jörg

Industrial facilities are complex and heterogeneous systems in permanent technological change. The ambitions towards smart factories heighten the requirements for the flexible interconnection of various devices. These industrial entities are controlled, observed and optimized by many services. The tuning of process parameters of several linked components in order to boost the overall energy efficiency is one example of such services. AutomationML (AML) provides a hierarchical description language for industrial systems considering both structure and properties. An extension of the established standard allows for intuitive modeling of energy optimization problems. An approved energy performance indicator (EnPI) methodology was integrated in the libraries of AML in order to simplify and shorten the modeling procedure for the optimization task. The procedure is demonstrated using the example of an industrial cooling system.

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Implementation of an Energy Metering System for Smart Production

2019 , Halstenberg, Friedrich A. , Lindow, Kai , Stark, Rainer

Digitization is consecutively changing more and more areas of human living. Many products are designed increasingly ""smart"" and connected to their environment. Not only products but also the necessary production facilities and systems are subject to digital change. The goal is to achieve a wide range of improvements and increase the efficiency and flexibility of the interlinked production systems. In Industry 4.0, important production parameters are measured and monitored with the help of sensors. Based on analyses of those data, adjustments and improvements of the production system can be performed. This paper presents the concept and physical implementation of an advanced energy metering system on a factory demonstrator, the so-called SmartFactory 4.0. It produces beverage coasters, which can be designed freely by the customer in shape, material and colour and is produced directly or remotely through a web application. The SmartFactory 4.0 consists of three production modules, which are connected to one another by means of media and information technology. The advanced energy metering system is designed in order to measure and monitor energy consumptions in various production steps. Those data are compared to previous simulations. Steps for the improvement of the energy efficiency of the SmartFactory 4.0 are derived. This paper presents first test results from the application of the system. For different individualized gravures and two different colours (green and orange) with various depths of the produced beverage coaster, energy consumptions of the production have been metered over time. The measured data are analysed and evaluated, and suitable steps for improvement are given. Finally, this research provides suggestions for scaling the energy metering system to larger production systems, and a systematic procedure for implementation is given. This research constitutes one step in the direction of utilizing the concept of the digital factory twin for the improvement of energy efficiency and sustainability of production systems.