Design optimization of office building envelope based on quantum genetic algorithm for energy conservation

Designing envelope configurations of building with the low construction cost and low energy consumption is of important significance to green building. At present, there are some mature professional software for building optimization design, however, these programs run for a long time and require detailed input of building parameters, which makes the design very inconvenient. It is relatively convenient to use some optimization algorithms to optimize the design of buildings. Genetic algorithm is a common algorithm for building design optimization. However, genetic algorithm has the disadvantage of being easy to be trapped into local optimization. Based on this, in this paper, we propose a design optimal method of office building envelope based on quantum genetic algorithm. We optimize the office building envelope structure, such as walls, windows, glass curtain wall, numbers of windows, etc. to minimize the construction cost at the required energy conservation. Compared with the traditional genetic algorithm, in this paper, when using the quantum genetic algorithm makes the design optimization of office building envelope configuration at the required ENVLOAD (energy load of building envelope) value, the total window area are increased by 13.8%, which means that the natural ventilation is better; glass curtain wall ratio is increased by 14%, which means that indoor lighting is better; the cost fall by 0.7%, which means the cost is lower; the generation number to achieve convergence is reduced by 50%, which means the convergence is faster. And compared with original design, the total cost reduces by 35.3%. Compared with other literatures, the construction cost per unit area of envelope in this paper is lower and the building energy load per unit area of envelope is smaller.

Automated summary

The study proposes a design optimal method for office building envelopes based on quantum genetic algorithms to optimize the structure and reduce construction costs while improving energy efficiency. Using the quantum genetic algorithm resulted in an increase in window area, glass curtain wall ratio, while lowering costs and improving convergence speed. Compared to traditional genetic algorithms, total costs reduced by 35.3%, demonstrating better energy efficiency at lower construction costs.