Optimisation modelling of industrial energy systems using MIND introducing the effect of material storage

2002 ◽  
Vol 142 (2) ◽  
pp. 419-433 ◽  
Author(s):  
Mehrdad Heidari Tari ◽  
Mats Söderström
Keyword(s):  
Energy Systems ◽  
Industrial Energy

scholarly journals Decarbonization of Industrial Energy Systems: A Case Study of Printed Circuit Board manufacturing

2021 ◽  
Author(s):  
Carles Ribas Tugores ◽  
Gerald Birngruber ◽  
Jürgen Fluch ◽  
Angelika Swatek ◽  
Gerald Schweiger
Keyword(s):  
Printed Circuit Board ◽  
Energy Systems ◽  
Circuit Board ◽  
Printed Circuit ◽  
Printed Circuit Board Manufacturing ◽  
Industrial Energy

Simulation und Optimierung kombiniert/A simulation-based framework for operational optimization of industrial energy systems

2020 ◽  
Vol 110 (01-02) ◽  
pp. 12-17
Author(s):  
Niklas Panten ◽  
Heiko Ranzau ◽  
Thomas Kohne ◽  
Daniel Moog ◽  
Eberhard Abele ◽  
...  
Keyword(s):  
Synthetic Data ◽  
Cost Savings ◽  
Energy Systems ◽  
Decisive Role ◽  
Optimization Methods ◽  
Energy System ◽  
Significant Cost ◽  
Operational Optimization ◽  
Simulation Based ◽  
Industrial Energy

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.

Digital Twins for Flexibility Service Provision from Industrial Energy Systems

2021 ◽  
Author(s):  
Yue Zhou ◽  
Pengfei Su ◽  
Jianzhong Wu ◽  
Wenqiang Sun ◽  
Xiandong Xu ◽  
...  
Keyword(s):  
Service Provision ◽  
Energy Systems ◽  
Digital Twins ◽  
Industrial Energy

scholarly journals Assessing Swedish Foundries Energy Management Program

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2780 ◽  
Author(s):  
Aida Sa ◽  
Patrik Thollander ◽  
Enrico Cagno ◽  
Majid Rafiee
Keyword(s):  
Energy Efficiency ◽  
Energy Management ◽  
Energy Systems ◽  
Management Program ◽  
Energy Strategy ◽  
Maturity Level ◽  
Industrial Energy ◽  
Shed Light ◽  
Do So

With regard to increased sustainability, managers not only need to know WHAT is needed for their company to improve, but also HOW to do so in detail is equally important. Energy management (EnM) is a pillar to the transformation of industrial energy systems towards enhanced energy efficiency and increased sustainability. One way to develop more and improve EnM both practically and theoretically is to shed light on how the combination of techniques and operation can contribute to successful EnM. This paper, therefore, through investigation of 10 Swedish foundries aims to present the structure of the energy strategy and associated practices at first; second, to assess industry’s EnM program and maturity level; and third, to identify and understand the nature of energy efficiency promoting factors within studied cases.

scholarly journals Generic Digital Twin Architecture for Industrial Energy Systems

2020 ◽  
Vol 10 (24) ◽  
pp. 8903
Author(s):  
Gernot Steindl ◽  
Martin Stagl ◽  
Lukas Kasper ◽  
Wolfgang Kastner ◽  
Rene Hofmann
Keyword(s):  
Industry 4.0 ◽  
Energy Systems ◽  
Energy Transition ◽  
Packed Bed ◽  
Reference Architecture ◽  
Semantic Web Technologies ◽  
Architecture Model ◽  
Digital Twin ◽  
Digital Twins ◽  
Industrial Energy

Digital Twins have been in the focus of research in recent years, trying to achieve the vision of Industry 4.0. In the domain of industrial energy systems, they are applied to facilitate a flexible and optimized operation. With the help of Digital Twins, the industry can participate even stronger in the ongoing renewable energy transition. Current Digital Twin implementations are often application-specific solutions without general architectural concepts and their structures and namings differ, although the basic concepts are quite similar. For this reason, we analyzed concepts, architectures, and frameworks for Digital Twins in the literature to develop a technology-independent Generic Digital Twin Architecture (GDTA), which is aligned with the information technology layers of the Reference Architecture Model Industry 4.0 (RAMI4.0). This alignment facilitates a common naming and understanding of the proposed architectural structure. A proof-of-concept shows the application of Semantic Web technologies for instantiating the proposed GDTA for a use case of a Packed-Bed Thermal Energy Storage (PBTES).

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