A Building Energy-Saving Method of Small High-Rise Office Building Based on BIM Model

Junqing Li,Xuan Zhang,Yongbing Li,Sikandar Ali

doi:10.1155/2022/9628115

Abstract

Building green energy-saving is an important area of current architectural application research. Artificial intelligence algorithm can effectively improve the design of building energy-saving digital, intelligent level. Therefore, this paper proposes the use of BIM model based on genetic algorithms to optimize the application of building energy conservation research. In this paper, the basic structure of genetic algorithm and advantages and disadvantages of the algorithm are described. According to the need of optimal design of building energy-saving integration, multiobjective optimization function is introduced and a multiobjective optimization genetic algorithm is established to improve the prediction effect of building energy efficiency model. Finally, results of analysis of some of the influencing factors and the simulation test of building energy-saving integrated optimization algorithm in small high-rise office building show that the improved genetic algorithm can effectively improve the effect of energy-saving integrated optimization and has good application prospects.

Highlights

China is the second largest economy in the world today and the largest developing country in the world
In order to solve the problem of multiobjective solution in building optimization, aiming at the design requirements in the field of building energy conservation, this paper aims at solving the conflicting and incomparable subfunctions that may appear in the optimization objective function, finding the global optimal solution in the range of feasible solutions
Genetic algorithm can simulate biological evolution and has genetic advantages so that certain goals need to be solved to get the best solution and is one of the human intelligent algorithm models. erefore, this paper proposes the application of building energy conservation based on genetic algorithms. is article elaborates the operation and advantage of genetic algorithm and optimizes and improves the genetic algorithm

Summary

Introduction

China is the second largest economy in the world today and the largest developing country in the world. In the background of the national gross floor area and the continuous development of the construction industry, the energy consumption proportion in building energy is facing a new test for the energy situation [2, 4]. Due to the vast territory of our country, large changes in environmental climate, thermal performance of buildings, equipment efficiency, and other factors, it is still very difficult to build an organic symbiotic architecture with advanced design concepts [2, 5]. One of the main shortcomings is that the concept of overall optimization has not been established in the design of building energy efficiency, and all aspects of building functional design are in their own independent state.

Objectives

Methods

Findings

Conclusion