{"title":"基于绿色节能的高校建筑照明设计","authors":"Wei Dong, Shanchuan Pan, Dao Zhou","doi":"10.1680/jensu.23.00022","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":49671,"journal":{"name":"Proceedings of the Institution of Civil Engineers-Engineering Sustainability","volume":"118 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Lighting design of university buildings based on green energy-saving\",\"authors\":\"Wei Dong, Shanchuan Pan, Dao Zhou\",\"doi\":\"10.1680/jensu.23.00022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":49671,\"journal\":{\"name\":\"Proceedings of the Institution of Civil Engineers-Engineering Sustainability\",\"volume\":\"118 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Institution of Civil Engineers-Engineering Sustainability\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1680/jensu.23.00022\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Civil Engineers-Engineering Sustainability","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1680/jensu.23.00022","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
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.
期刊介绍:
Engineering Sustainability provides a forum for sharing the latest thinking from research and practice, and increasingly is presenting the ''how to'' of engineering a resilient future. The journal features refereed papers and shorter articles relating to the pursuit and implementation of sustainability principles through engineering planning, design and application. The tensions between and integration of social, economic and environmental considerations within such schemes are of particular relevance. Methodologies for assessing sustainability, policy issues, education and corporate responsibility will also be included. The aims will be met primarily by providing papers and briefing notes (including case histories and best practice guidance) of use to decision-makers, practitioners, researchers and students.