The impact of power system characteristics on the energy consumption of a steel plant

\nThis paper presents a comprehensive analysis of the relationships between energy consumption and various factors affecting the operation of the power system of a steel plant. Given the growing demand for electricity and the necessity to transition to sustainable energy sources, studying these relationships is becoming increasingly relevant. The main methods used in the research include correlation and factor analysis, which help identify key dependencies and patterns in the behavior of power systems. The study covers parameters such as reactive power, load type, and temporal factors, including the day of the week and the day's status. The results of the correlation analysis reveal a strong relationship between energy consumption and lagging reactive power, as well as significant connections with other variables, such as load type and temporal characteristics. These dependencies highlight the importance of considering various factors in energy resource management. Factor analysis identifies several key factors influencing energy consumption, opening new opportunities for process optimization in power systems. The findings emphasize the need for a comprehensive data analysis approach to effectively manage energy consumption and enhance the resilience of power supply systems. This work is of practical significance for energy companies and specialists in energy management, as the results can be used to develop strategies for optimizing energy consumption, improving planning, and ensuring supply reliability. Overall, this study contributes to the understanding of power system dynamics and lays the foundation for future research in the field of sustainable energy development.\n

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-10-25
DOI
https://doi.org/10.1051/e3sconf/202458305012/pdf
Primary Topic
Integrated Energy Systems Optimization
Type
article
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article

The impact of power system characteristics on the energy consumption of a steel plant

Springer Link (Chiba Institute of Technology)
Integrated Energy Systems Optimization
article

The impact of power system characteristics on the energy consumption of a steel plant

article en

Abstract

\nThis paper presents a comprehensive analysis of the relationships between energy consumption and various factors affecting the operation of the power system of a steel plant. Given the growing demand for electricity and the necessity to transition to sustainable energy sources, studying these relationships is becoming increasingly relevant. The main methods used in the research include correlation and factor analysis, which help identify key dependencies and patterns in the behavior of power systems. The study covers parameters such as reactive power, load type, and temporal factors, including the day of the week and the day's status. The results of the correlation analysis reveal a strong relationship between energy consumption and lagging reactive power, as well as significant connections with other variables, such as load type and temporal characteristics. These dependencies highlight the importance of considering various factors in energy resource management. Factor analysis identifies several key factors influencing energy consumption, opening new opportunities for process optimization in power systems. The findings emphasize the need for a comprehensive data analysis approach to effectively manage energy consumption and enhance the resilience of power supply systems. This work is of practical significance for energy companies and specialists in energy management, as the results can be used to develop strategies for optimizing energy consumption, improving planning, and ensuring supply reliability. Overall, this study contributes to the understanding of power system dynamics and lays the foundation for future research in the field of sustainable energy development.\n

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 71%
Integrated Energy Systems Optimization
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