基于多源数据集成的建筑能源管理与控制平台

Y. Qi, Kun Wang, Sen Wang, Zhiyong Gan, Jiang Bian, Guochao Yang, Zhaowen Yang, Delu Li
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摘要

大力发展节能减排,发展低碳经济,保持国民经济的可持续发展,是必由之路。本文提出了一种基于多源数据的建筑智能节能平台。基于建筑能源供需侧数据驱动CPS(Cyber Physical Systems)架构,构建了包含智能感知层、智能分析层、智能网络层、智能认知层和决策执行层的系统级5C CPS。提出了基于建筑体免疫遗传算法的节能降耗全局控制技术。将遗传算法与遗传算子的协同机制相结合,提取了多设备终端的全局最优解。基于神经网络的建筑能源系统与电网协同运行算法,能够实时了解电网与建筑协同运行环境,提供各种预警和后分析功能,并完成实时信息交互、网络连接交互和多重能源协同的要求。
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Building Energy Management and Control Platform Based on Multi-source Data Integration
The only way which must be passed is to develop energy saving and emission reduction, and to develop low-carbon economy and maintain sustainable development of national economy. In this paper, a building intelligent energy saving platform based on multi-source data is proposed. Based on data driven CPS(Cyber Physical Systems) architecture of building energy supply and demand side, a system level 5C CPS including intelligent perception layer, intelligent analysis layer, intelligent network layer, intelligent cognition layer and decision and execution layer is built. Based on the building body immune genetic algorithm, the global control technology of energy saving and consumption reduction is proposed. Combining genetic algorithm with the cooperative mechanism of genetic operators, we extract the global optimal solution of multi device terminals. The collaborative operation algorithm of building energy system and power grid based on neural network can real-time understand the collaborative operation environment of power grid and buildings, provide the functions of various early warning and post analysis, and also complete the requirements of real-time information interaction, network connection interaction and multiple energy synergy.
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