Study on Energy Saving Optimization of Residential Building Envelope Structure in Qinghai City Based on Genetic Algorithm

The northwest region of China is categorized as a severely cold and cold area in the thermal zoning for buildings, characterized by harsh climate conditions, long and cold winters, and high heating energy consumption, leading to significant energy consumption and economic burden. To address this issue, efforts must begin at the planning and design stages, aiming to reduce building energy consumption while minimizing costs. This paper focuses on Qinghai Province in China, applying multi-objective optimization theory and selecting the genetic algorithm as the solution method for multi-objective optimization problems. Based on genetic algorithm theory and current building energy efficiency standards, the study conducts multi-objective optimization for the energy efficiency of urban residential buildings in Qinghai, analyzing the primary factors affecting building energy consumption and economic costs. The study selects building energy consumption and the cost of insulation materials for the envelope as two optimization goals, constructs a genetic algorithm mathematical model for building energy efficiency, establishes a functional relationship between building energy consumption, the heat transfer coefficient of the envelope, and the economic aspects of insulation materials, and uses the MATLAB platform to debug and run the algorithm, as well as the Design Builder energy consumption simulation software to achieve a closed-loop system for simulation verification. This provides data support for the optimization of building energy efficiency in the northwest region of China.