Lighting design of university buildings based on green energy-saving

The traditional way of designing parameters of university buildings is to give designs based on the experience of designers after surveying the local environment, but this approach is time-consuming and laborious. The research problem of this paper is to quickly optimize the parameters of university buildings with the goal of energy saving. This paper first constructed a model of energy consumption and lighting of university buildings, then used a particle swarm optimization (PSO) algorithm modified by the genetic algorithm to optimize the building parameters, and compared it with the traditional PSO algorithm in a case study. The results were that the PSO algorithm improved by the genetic algorithm converged the building parameter scheme to stability faster, and the scheme fitness value at stability was lower than that of the traditional PSO algorithm, and the improved PSO algorithm required less computation time in optimizing the building parameter scheme.