<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper takes the air conditioning energy consumption in railroad building design as the main object of analysis and uses an orthogonal experimental design method to study the influencing factors and effects of energy consumption in the Middle East railroad construction design. Stochastic working condition simulation is carried out for the typical models of passenger stations in five climate zones to obtain the data set of the passenger station energy consumption model, and the multiple linear regression prediction models of air conditioning energy consumption in different regions are established. Combined with the hour-by-hour average outdoor temperature, hour-by-hour passenger flow and lighting and related equipment data in the waiting hall of a city in July, the air-conditioning cold load of railroad passenger stations is simulated and analyzed. Explore the implementation effect of energy-saving strategies for railroad passenger station air-conditioning system, and for the traditional PID control strategy, put forward the control strategy based on model prediction, analyze the change of centralized air-conditioning system cold load and the change of the actual performance coefficient of the chiller unit under different control strategies. The data show that compared with the traditional PID control, the model prediction control reduces the total energy consumption by 0.2063, which realizes the energy-saving optimization of the air conditioning system for railroad building design.</p>
</abstract>

This paper takes the air conditioning energy consumption in railroad building design as the main object of analysis and uses an orthogonal experimental design method to study the influencing factors and effects of energy consumption in the Middle East railroad construction design. Stochastic working condition simulation is carried out for the typical models of passenger stations in five climate zones to obtain the data set of the passenger station energy consumption model, and the multiple linear regression prediction models of air conditioning energy consumption in different regions are established. Combined with the hour-by-hour average outdoor temperature, hour-by-hour passenger flow and lighting and related equipment data in the waiting hall of a city in July, the air-conditioning cold load of railroad passenger stations is simulated and analyzed. Explore the implementation effect of energy-saving strategies for railroad passenger station air-conditioning system, and for the traditional PID control strategy, put forward the control strategy based on model prediction, analyze the change of centralized air-conditioning system cold load and the change of the actual performance coefficient of the chiller unit under different control strategies. The data show that compared with the traditional PID control, the model prediction control reduces the total energy consumption by 0.2063, which realizes the energy-saving optimization of the air conditioning system for railroad building design.

Research on energy-saving strategies in the architectural design of the Eastern Railway in the era of artificial intelligence

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper takes the air conditioning energy consumption in railroad building design as the main object of analysis and uses an orthogonal experimental design...

Research on energy-saving strategies in the architectural design of the Eastern Railway in the era of artificial intelligence

Publié en ligne: 31 janv. 2024

Pages: -

Reçu: 11 déc. 2023

Accepté: 18 déc. 2023

DOI: https://doi.org/10.2478/amns-2024-0022

Mots clés
Orthogonal experimental design, Conventional PID control, Multiple linear regression, Energy modeling, Railroad buildings

© 2024 Jianjun Xu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on energy-saving strategies in the architectural design of the Eastern Railway in the era of artificial intelligence

Publié en ligne: 31 janv. 2024

Pages: -

Reçu: 11 déc. 2023

Accepté: 18 déc. 2023

DOI: https://doi.org/10.2478/amns-2024-0022

Mots clésOrthogonal experimental design, Conventional PID control, Multiple linear regression, Energy modeling, Railroad buildings

© 2024 Jianjun Xu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Orthogonal experimental design, Conventional PID control, Multiple linear regression, Energy modeling, Railroad buildings