基于绿色低碳理念的智能建筑设计

Q2 Energy
Qian Lv
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引用次数: 0

摘要

智能建筑将现代技术与建筑设计相结合,带来了功能和用户体验的进步。这些发展也有助于通过实施先进的技术系统来追求环境的可持续性、节约能源和减少排放。智能建筑设计以绿色低碳理念为指导,强调充分利用可再生能源,同时利用先进的算法优化智能建筑的能源调度,实现绿色、低碳、节能、减排的目标。因此,本研究基于绿色低碳理念,对智能建筑的可再生能源系统、照明控制系统、电梯控制系统、空调控制系统进行优化。以上海某示范性智能办公大楼为例,实验结果表明,该建筑的太阳风互补发电系统年发电量可达609,380千瓦时。这个数量满足了60%的建筑电力需求,从而标志着传统建筑能源供应方法的重大突破。照明系统采用智能定时照明双模控制,能耗降低10.1%。优化后的电梯群控算法可实现月均节电6100千瓦时。通过负荷预测模型,空调系统每月减少能耗7238千瓦时。结果表明,本研究建立的智能建筑能源优化系统,通过多系统算法联动,整体能源效率较传统解决方案提高23%。该方法为智慧城市减排提供了可重复使用的技术范式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

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来源期刊
Energy Informatics
Energy Informatics Computer Science-Computer Networks and Communications
CiteScore
5.50
自引率
0.00%
发文量
34
审稿时长
5 weeks
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