Design Method for Building Automation Control Programs to Enable the Energetic Optimization of Industrial Supply Systems

Fuhrländer-Völker, Daniel; Weigold, Matthias

doi:10.1016/j.procir.2021.11.039

Cited by 8 publications

(1 citation statement)

References 9 publications

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“…Using several CFD simulations, which allow to calculate with a very good accuracy the way heat, air currents circulate in the air, we want to train a neural network that will allow intelligent control of the heating system by estimating the optimal positioning of air sources. This optimization is necessary because some tools with considerable volume in the hall are fixed but other components of the industrial flow, such as temporary processing machines or trucks (which can park for hours or days) can influence the heating of the industrial hall operating at low temperatures [23][24][25][26][27][28]…”

Section: Introductionmentioning

confidence: 99%

CFD Modeling and Simulation of an Industrial Hall

Marin

2021

Ann_UGAL_MMS

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The subject of this research is the use of artificial vision techniques to optimize the placement of hot air sources depending on the location of certain equipment in industrial halls operating at low temperatures. Low temperature industrial halls require optimization of the location of hot air sources to achieve low consumption and efficient heating, taking into account the fact that workplace safety standards require the halls are high and at a certain area of windows (to ensure a hall for this reason, it is necessary to optimize the location and hot air sources flow to ensure the heating of these halls.

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Section: Introductionmentioning

confidence: 99%

CFD Modeling and Simulation of an Industrial Hall

Marin

2021

Ann_UGAL_MMS

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Software Development Methodology of Hydrogen Generator Control System Based on User Interface

Moroz,

Gavriushin,

Murashov

et al. 2024

Lecture Notes in Electrical Engineering

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Automation architecture for harnessing the demand response potential of aqueous parts cleaning machines

Fuhrländer-Völker

Magin

Weigold

2023

Prod. Eng. Res. Devel.

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To reduce global greenhouse gas emissions, numerous new renewable power plants are installed and integrated in the power grid. Due to the volatile generation of renewable power plants large storage capacity has to be installed and electrical consumer must adapt to periods with more or less electrical generation. Industry, as one of the largest global consumers of electrical energy, can help by adjusting its electricity consumption to renewable production (demand response). Industrial aqueous parts cleaning machines offer a great potential for demand response as they often have inherent energy storage potential and their process can be adapted for energy-flexible operation. Therefore, this paper presents a method for implementing demand response measures to aqueous parts cleaning machines. We first determine the potential for shifting electrical consumption. Then, we adapt the automation program of the machine so that submodules and process steps with high potential can be energy-flexibly controlled. We apply the method to an aqueous parts cleaning machine in batch process at the ETA Research Factory.

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Design Method for Building Automation Control Programs to Enable the Energetic Optimization of Industrial Supply Systems

Cited by 8 publications

References 9 publications

CFD Modeling and Simulation of an Industrial Hall

CFD Modeling and Simulation of an Industrial Hall

Software Development Methodology of Hydrogen Generator Control System Based on User Interface

Automation architecture for harnessing the demand response potential of aqueous parts cleaning machines

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