Accurate wind flow prediction is essential for various applications, including the placement of wind turbines and a multitude of environmental assessments. Traditionally this can be achieved by using time-consuming computational fluid dynamics (CFD) simulations on reanalysis data. This study explores the performance of an autoencoder (AE) and a variational autoencoder (VAE) in approximating downscaled wind speed and direction using real-world reanalysis data and reference geo- and vegetation data. The AE model was trained for 2000 epochs and demonstrates the ability to replicate wind patterns with a mean absolute error (MAE) of approximately −0.9. However, the AE model exhibited a consistent underestimation of wind speeds and a directional shift of approximately 10 degrees compared to CFD reference simulations. The VAE model produced visually improved results, capturing complex wind flow structures more accurately than the AE model. It mainly achieves better local accuracy and a reduced variance of the results. The overall result suggests that while autoencoders can approximate wind flow patterns, challenges remain in capturing the full variability of wind speeds and directions with sufficient precision. The study highlights the importance of balancing reconstruction accuracy and latent space regularization in VAE models. Future work should focus on optimizing model architecture and training strategies to enhance accuracy, prediction reliability and generalizability across diverse wind conditions and various locations.

This study describes the development of an operation-independent simulation model for electrified die-casting foundries which use a smart grid system to cover their energy requirements. The model uses real weather and electricity price exchange data for the simulation period. It can be used to determine and compare electricity costs for production at specific times of day and year, as well as the economic efficiency of different photovoltaic (PV) system and electricity storage variants. It also enables the proportion of different energy sources for each configuration to be analysed. This can be carried out using the model for locations throughout Germany. Additionally, this paper presents exemplary simulation studies that demonstrate the model’s wide range of applications. The results provide an initial overview of the potential savings and optimisation. In the future, the model will provide a basis for determining optimum plant layouts and production times using simulation-based optimisation.

Diese Studie beschreibt die Entwicklung eines betriebsunabhängigen Simulationsmodells für elektrifizierte Druckgießereien, die ihren Energiebedarf mit Hilfe eines Smart Grid Systems decken. Das Modell verwendet reale Wetter- und Börsenstrompreisdaten für den Simulationszeitraum. Mit Hilfe des Modells können die Stromkosten für eine Produktion zu einem bestimmten Zeitpunkt (Tages- und Jahreszeit) sowie die Wirtschaftlichkeit verschiedener PV-Anlagen- und Stromspeichervarianten ermittelt und verglichen werden. Zudem ermöglicht es die Untersuchung des Anteils der verschiedenen Energieträger für die jeweilige Konfiguration. Dies kann mit Hilfe des Modells für Standorte in ganz Deutschland durchgeführt werden. Darüber hinaus werden in dieser Arbeit beispielhafte Simulationsstudien vorgestellt, die den breiten Anwendungsbereich des Modells aufzeigen. Aus den Ergebnissen kann ein erster Überblick über Einsparungs- und Optimierungsmöglichkeiten gewonnen werden. Perspektivisch stellt das Modell eine Grundlage dar, um mittels simulationsgestützter Optimierung optimale Anlagenlayouts und Produktionszeitpunkte zu ermitteln.

This study describes the development of an operation-independent simulation model for an electrified die-casting foundry that uses a smart grid system to meet its energy needs. The model uses real weather and stock exchange electricity price data for the simulation period. The model can be used to determine and compare the cost of electricity for production at a given time (time of day and season) as well as the economics of different PV system and electricity storage options. It is also possible to analyze the share of different energy sources for each configuration. This can be done for sites throughout Germany. In addition, exemplary simulation studies are presented in this paper which demonstrate the wide range of applications of the model. The results provide an initial overview of the potential for savings and optimization. In the future, the model will provide a basis for determining optimum plant layouts and production times by means of simulation-based optimization.

The current energy crisis and high fossil fuel costs are challenging energy intensive industries such as non- ferrous foundries. It is therefore important to promote the transition to renewable energy sources with the electrification of melting units. This pilot study is the first to simulate the transition of conventional foundries to sustainable technologies. For this purpose, a simulation model based on a selected example company is developed. It takes into account the energy consumption and the logistical effects of a converted operation. The simulation model is implemented as a hybrid simulation combining a discrete event simulation at the plant level and a process simulation within the furnaces. The study shows how a sustainable energy supply can be achieved in foundries. The effects of efficiency as well as energy costs and emissions are also taken into account.

The current energy crisis and the high cost of fossil fuels pose major challenges for energy-intensive industries such as the non-ferrous foundry industry. Therefore, it is important to promote the transition to renewable energy sources with the help of the electrification of the melting units. In this pilot study, for the first time the conversion of conventional foundries to sustainable technologies is simulated. For this purpose, a simulation model is developed based on a selected example company. It considers the energy consumption and the logistical effects of a converted operation. The simulation model is implemented as a hybrid simulation combining a discrete
event simulation at the plant level and a process simulation within the furnaces. The study shows how a sustainable energy supply can be achieved in foundries. It also considers the impact of efficiency, energy costs and emissions.