الفهرس 
PRINCIPLE OF OPERATION, TYPES AND POWER-QUALITY ISSUESOnly 14 pages are availabe for public view
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Abstract
This thesis focuses on the sophisticated modelling of Electric Arc Furnaces (EAFs), a crucial technology in the steel manufacturing sector, with a specific emphasis on both frequency-domain (FD) and time-domain (TD) modelling. Electric Arc Furnaces (EAFs) are well-known for their ability to efficiently melt scrap metal. However, they also pose significant power quality issues, including voltage swings, harmonic distortion, and flicker. These problems influence both the efficiency of the furnace and the stability of the surrounding electrical infrastructure.
The focus of this research is to investigate FD modelling, particularly using vector fitting, an advanced technique that is essential for accurately representing the frequency response of EAFs. This approach is crucial for analyzing EAF operations in terms of their steady-state behavior and harmonic analysis. Vector fitting proves to be highly effective in accurately reflecting the complex frequency characteristics of EAFs, providing valuable insights into identifying and reducing power quality concerns such as harmonics and resonance events.
The thesis emphasizes FD modelling and explores and introduces novel time-domain (TD) models. The capacity of TD models, such as the well-known Cassie-Mayr model, to represent dynamic behavior across time is being examined. This investigation aims to provide detailed insights into transient occurrences. The Cassie-Mayr model is thoroughly investigated for its efficacy in distinguishing between high and low current situations in EAFs. Numerical methods, including the Runge-Kutta methods such as ODE45, are used to solve the intricate differential equations essential for this TD modelling.
The study additionally combines Autoregressive Moving Average (ARMA) and ARMAX models to analyze and predict time series in EAF processes. These models contribute substantially to comprehending the linear dynamics and irregularities inside the time series data of EAF operation.
The thesis makes a significant contribution to the frequency-domain models by employing a novel method of modelling utilizing vector fitting, which establishes a higher level of accuracy in collecting and analyzing the frequency responses of EAFs, thus creating a new benchmark. This contribution is further enhanced by the investigation and validation of TD models, which improves the overall comprehension of EAF dynamics.
The models are thoroughly examined and verified using actual data collected from an Egyptian steel production, highlighting the crucial importance of precise modelling in the operation of Electric Arc Furnaces (EAF) and the management of power quality. The research is innovative because it employs a holistic strategy that integrates both FD and TD modelling approaches.
This methodology leads to substantial advancements in practical applications and academic knowledge within the steel manufacturing business. This study not only enhances the theoretical understanding in the subject but also provides significant and practical insights for industry professionals who are dealing with power quality difficulties in electric arc furnace (EAF) based steel production.