Research on energy consumption control method for the lifecyle of public green buildings based on multi objective optimization

In the operation process of public green buildings, traditional optimization algorithms require a lot of time and computational resources to solve complex models, and may even get stuck in local optimal solutions, unable to find the global optimal solution, resulting in high energy consumption costs. Therefore, a multi-objective optimization based energy consumption control method for the lifecyle of public green buildings is proposed. Firstly, an optimization model for energy consumption control throughout the entire lifecyle of public green buildings is developed with the goal of maximizing energy efficiency and minimizing incremental costs. During the operation of public green buildings, it helps to reduce energy consumption and minimize the impact on the environment. Next, constraints such as building envelope structure, heating, ventilation, and air conditioning (HVAC) systems, roof structure, and maximum incremental cost are defined. Finally, the improved genetic algorithm is used to solve the constructed model and output the lifecyle energy consumption control optimization results for public green buildings. The experimental results show that through the verification of the energy consumption control scheme with 10 sets of differentiated building envelope parameter combinations, the lifecyle cost of this method is reduced by 29.5%, carbon emissions are reduced by 29.0%, and the response time is controlled within 6 s. This study innovatively adopts a multi-objective optimization framework and an improved genetic algorithm to construct a lifecyle energy consumption control model for public green buildings. By synchronously optimizing key parameters such as building envelope and HVAC system, the dual improvement of energy efficiency and environmental benefits can be achieved under the constraint of incremental cost, opening up a new path for intelligent operation and management of green buildings, which has significant comprehensive economic and environmental value.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-12-23
DOI
https://doi.org/10.1051/ro/2025137/pdf
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
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article

Research on energy consumption control method for the lifecyle of public green buildings based on multi objective optimization

Springer Link (Chiba Institute of Technology)
Building Energy and Comfort Optimization
article

Research on energy consumption control method for the lifecyle of public green buildings based on multi objective optimization

article en

Abstract

In the operation process of public green buildings, traditional optimization algorithms require a lot of time and computational resources to solve complex models, and may even get stuck in local optimal solutions, unable to find the global optimal solution, resulting in high energy consumption costs. Therefore, a multi-objective optimization based energy consumption control method for the lifecyle of public green buildings is proposed. Firstly, an optimization model for energy consumption control throughout the entire lifecyle of public green buildings is developed with the goal of maximizing energy efficiency and minimizing incremental costs. During the operation of public green buildings, it helps to reduce energy consumption and minimize the impact on the environment. Next, constraints such as building envelope structure, heating, ventilation, and air conditioning (HVAC) systems, roof structure, and maximum incremental cost are defined. Finally, the improved genetic algorithm is used to solve the constructed model and output the lifecyle energy consumption control optimization results for public green buildings. The experimental results show that through the verification of the energy consumption control scheme with 10 sets of differentiated building envelope parameter combinations, the lifecyle cost of this method is reduced by 29.5%, carbon emissions are reduced by 29.0%, and the response time is controlled within 6 s. This study innovatively adopts a multi-objective optimization framework and an improved genetic algorithm to construct a lifecyle energy consumption control model for public green buildings. By synchronously optimizing key parameters such as building envelope and HVAC system, the dual improvement of energy efficiency and environmental benefits can be achieved under the constraint of incremental cost, opening up a new path for intelligent operation and management of green buildings, which has significant comprehensive economic and environmental value.

Springer Link (Chiba Institute of Technology)
Affordable and clean energy
Openalex Percentile: Top 44%
Building Energy and Comfort Optimization
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