{"title":"基于绿色低碳理念的智能建筑设计","authors":"Qian Lv","doi":"10.1186/s42162-025-00513-9","DOIUrl":null,"url":null,"abstract":"<div><p>The integration of modern technology and architectural design in intelligent buildings has led to advancements in functionality and user experience. These developments have also contributed to the pursuit of environmental sustainability, energy conservation, and emission reduction through the implementation of advanced technological systems. Guided by the concept of green and low-carbon, intelligent building design emphasizes the full utilization of renewable energy while utilizing advanced algorithms to optimize energy scheduling in intelligent buildings, achieving green, low-carbon, energy-saving, and emission-reduction goals. Therefore, based on the concept of green and low-carbon, this study optimizes the renewable energy system, lighting control system, elevator control system, and air conditioning control system of intelligent buildings. The experimental findings, utilizing a paradigmatic intelligent office building in Shanghai as a case study, demonstrated that the solar wind complementary power generation system of the building attained an annual power generation of 609,380 kWh. This amount satisfied 60% of the building's electricity requirement, thereby signifying a substantial breakthrough in conventional building energy supply methodologies. The lighting system adopted intelligent time lighting dual-mode control, reducing energy consumption by 10.1%. The optimization of the elevator group control algorithm could achieve an average monthly power saving of 6100 kWh. The air conditioning system reduced energy consumption by 7238 kWh/month through a load forecasting model. The results showed that the intelligent building energy optimization system established in the study, through multi-system algorithm linkage, improved overall energy efficiency by 23% compared to traditional solutions. This method provides a reusable technical paradigm for smart city emission reduction.</p></div>","PeriodicalId":538,"journal":{"name":"Energy Informatics","volume":"8 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://energyinformatics.springeropen.com/counter/pdf/10.1186/s42162-025-00513-9","citationCount":"0","resultStr":"{\"title\":\"Intelligent building design based on green and low-carbon concept\",\"authors\":\"Qian Lv\",\"doi\":\"10.1186/s42162-025-00513-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The integration of modern technology and architectural design in intelligent buildings has led to advancements in functionality and user experience. These developments have also contributed to the pursuit of environmental sustainability, energy conservation, and emission reduction through the implementation of advanced technological systems. Guided by the concept of green and low-carbon, intelligent building design emphasizes the full utilization of renewable energy while utilizing advanced algorithms to optimize energy scheduling in intelligent buildings, achieving green, low-carbon, energy-saving, and emission-reduction goals. Therefore, based on the concept of green and low-carbon, this study optimizes the renewable energy system, lighting control system, elevator control system, and air conditioning control system of intelligent buildings. The experimental findings, utilizing a paradigmatic intelligent office building in Shanghai as a case study, demonstrated that the solar wind complementary power generation system of the building attained an annual power generation of 609,380 kWh. This amount satisfied 60% of the building's electricity requirement, thereby signifying a substantial breakthrough in conventional building energy supply methodologies. The lighting system adopted intelligent time lighting dual-mode control, reducing energy consumption by 10.1%. The optimization of the elevator group control algorithm could achieve an average monthly power saving of 6100 kWh. The air conditioning system reduced energy consumption by 7238 kWh/month through a load forecasting model. The results showed that the intelligent building energy optimization system established in the study, through multi-system algorithm linkage, improved overall energy efficiency by 23% compared to traditional solutions. This method provides a reusable technical paradigm for smart city emission reduction.</p></div>\",\"PeriodicalId\":538,\"journal\":{\"name\":\"Energy Informatics\",\"volume\":\"8 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://energyinformatics.springeropen.com/counter/pdf/10.1186/s42162-025-00513-9\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1186/s42162-025-00513-9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Energy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Informatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1186/s42162-025-00513-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Energy","Score":null,"Total":0}
Intelligent building design based on green and low-carbon concept
The integration of modern technology and architectural design in intelligent buildings has led to advancements in functionality and user experience. These developments have also contributed to the pursuit of environmental sustainability, energy conservation, and emission reduction through the implementation of advanced technological systems. Guided by the concept of green and low-carbon, intelligent building design emphasizes the full utilization of renewable energy while utilizing advanced algorithms to optimize energy scheduling in intelligent buildings, achieving green, low-carbon, energy-saving, and emission-reduction goals. Therefore, based on the concept of green and low-carbon, this study optimizes the renewable energy system, lighting control system, elevator control system, and air conditioning control system of intelligent buildings. The experimental findings, utilizing a paradigmatic intelligent office building in Shanghai as a case study, demonstrated that the solar wind complementary power generation system of the building attained an annual power generation of 609,380 kWh. This amount satisfied 60% of the building's electricity requirement, thereby signifying a substantial breakthrough in conventional building energy supply methodologies. The lighting system adopted intelligent time lighting dual-mode control, reducing energy consumption by 10.1%. The optimization of the elevator group control algorithm could achieve an average monthly power saving of 6100 kWh. The air conditioning system reduced energy consumption by 7238 kWh/month through a load forecasting model. The results showed that the intelligent building energy optimization system established in the study, through multi-system algorithm linkage, improved overall energy efficiency by 23% compared to traditional solutions. This method provides a reusable technical paradigm for smart city emission reduction.