建筑能源系统物联网数据监测与传输质量保障方法

发布时间：2018-03-06 21:36

本文选题：建筑能耗监测　切入点：建筑能源系统物联网　出处：《大连理工大学》2014年博士论文　论文类型：学位论文

【摘要】：建筑节能,以提高建筑能源利用效率、降低能源消耗为目标,已成为我国缓解能源供给不足、降低污染物排放,实现建筑能源环境可持续发展的重要课题之一。建筑能耗监测及建筑能源系统物联网(Internet of Building Energy Systems, iBES)为量化考评我国建筑节能工作、促进建筑能效评价与节能改造工作的深入开展,提供了理论基础和技术支持,具有重要的现实和长远意义。能耗数据作为指导建筑系统运行管理、节能诊断和能效评价的基础数据,其正确性和可靠性至关重要。但通过对建筑能耗监测系统的建设和实际运行调研发现,现有建筑能耗监测系统在底层能耗数据监测和网络层数据传输过程中,仍然存在较大的数据质量问题,特别是因感知层信道干扰造成的异常能耗数据、传输层因网络拥塞造成的数据传输障碍等问题亟需进一步解决。为此,本文将以建筑能源系统物联网为平台,通过理论和试验研究、技术开发等手段,以提高建筑能耗监测系统数据监测和数据传输质量为目标,开展以下研究工作。首先,针对建筑能耗监测系统中普遍采用的RS485总线因工作环境恶劣、强电磁干扰等因素引起的通信可靠性较差问题,研究iBES感知层数据监测质量保障方法。以总线的偏置电阻、终端电阻、总线节点数量三个关键参数为研究对象,建立了RS485总线的等效电路模型,通过基尔霍夫电流定律及限流法确定了偏置电阻的合理取值范围,进一步分析了偏置电阻对终端电阻以及总线节点数量的影响。结果表明,偏置电阻的理论最小值为556Ω,最大值为716Ω,当偏置电阻取值为665Ω时,可以确保RS485总线稳定通信的前提下得到总线的最大节点数量,为RS485总线在iBES工程应用提供了技术指导。其次,针对iBES传输层网络结构复杂、网络类型多样化、跨网远距离传输的特点,以能够评价能耗监测网络通信性能的关键参数——网络时延的特性研究为切入点,研究分析iBES网络时延组成,通过S-Ping测量方法从不同角度探究网络时延的分布特性,在此基础上,提出了基于小波滤波-差分自回归滑动平均模型(W-ARIMA)的能耗监测网络时延预测方法。结果表明,W-ARIMA算法具有较高的预测精度,可以实现对网络通信拥塞程度的预判,为优化能耗数据传输奠定基础。第三,针对iBES传输层网络拥塞造成的传输障碍、数据丢失等问题,基于网络时延特性的预测结果,研究改变能耗数据包发包间隔(VPI)和发包大小(VPS)的模糊自适应传输方法。Matlab仿真结果表明,与采用“定时、定量、定间隔”传输方法相比,采用VPI-FATC方法传输时,能耗数据包丢包率下降了23%,采用VPS-FATC方法传输时,丢包率下降了71%；采用VPIS-FATC方法传输时,丢包率下降了79%。最后,在上述理论研究结果的基础上开发了iBES智能数据采集器,其具体智能功能体现在：(1)自配置功能,当遇到网络中断时,可自主读取SD卡中存储的配置信息,避免丢失能耗数据；(2)智能采样功能,可通过变频采样、勒贝格采样方式对能耗数据进行优化采样,在保证能耗数据变化趋势要求的基础上,节约大量的数据存储空间；(3)智能传输控制方法,根据网络拥塞程度动态调整下一时刻能耗数据包的发送时间间隔、数据包大小,适应网络负载变化带来的影响,提高能耗数据传输质量和效率。
[Abstract]:In order to improve building energy efficiency, building energy efficiency, reduce the energy consumption, has become China's energy supply, reduce pollutant emissions, one of the important task for the implementation of building energy and environment sustainable development. The building energy consumption monitoring and building energy system networking (Internet of Building Energy Systems, iBES) for the quantitative evaluation of our country the construction of energy-saving work, to promote building energy efficiency evaluation and energy-saving work in depth, to provide theoretical basis and technical support, has important practical and long-term significance. The energy consumption data refers to the operation and management system construction as the guide, the basic data for diagnosis and evaluation of energy saving efficiency, its correctness and reliability is essential. But through the actual operation and construction the building energy consumption monitoring system's research found that the existing building energy consumption monitoring system in the lower energy consumption data monitoring and network layer data transmission In the process, there are still large data quality problems, especially due to abnormal energy consumption data channel interference caused by the perception layer, transport layer problems due to network congestion caused by data transmission obstacles need further solution. Therefore, this paper will take the Internet of building energy system as a platform, through theoretical and experimental research, technology development and other means in order to improve the building energy monitoring system, data monitoring and data transmission quality as the goal, to carry out the following research work.
First of all, according to the commonly used building energy consumption monitoring system of RS485 bus communication due to poor working conditions, poor reliability problems caused by strong electromagnetic interference and other factors, the research of iBES sensing layer data monitoring quality assurance method. To bias resistors, bus terminal resistor, three key parameters of the bus node number as the research object, established the equivalent circuit the model of RS485 bus, to determine the reasonable range of the bias resistors by Kirchhoff's current law and current limiting method, further analysis of the bias resistors on the bus terminal resistance and the number of nodes of the influence. The results show that the theoretical minimum bias resistance is 556 ohms, the maximum value is 716 ohms, when the bias resistor value is 665. When the RS485 bus communication can ensure the premise of stability under the maximum number of nodes of the RS485 bus in the bus, for the engineering application of iBES provides technical guidance.
Secondly, according to the iBES transmission layer structure of complex networks, the network of diverse types, characteristics of inter network transmission, in order to study the characteristics of key network delay parameter can be used to evaluate the communication performance of the energy consumption monitoring network as the breakthrough point, analysis of the composition of iBES network delay distribution research, to explore the characteristics of network delay from different angles through the S-Ping measuring method. On this basis, put forward the wavelet filter difference autoregressive moving average model (W-ARIMA) based on the prediction method of energy consumption monitoring network delay. The results show that the W-ARIMA algorithm has higher prediction accuracy, can predict the degree of congestion of network communication, to lay the foundation for optimizing the energy consumption of data transmission.
Third, according to the iBES transport layer transmission obstacles caused by network congestion, data loss, network delay prediction results based on the change of energy consumption data packet interval (VPI) and the size (VPS) fuzzy adaptive transmission method.Matlab simulation results show that compared with the "timing, quantitative, compared to a given interval transmission method, using the method of VPI-FATC transmission, the packet loss rate of energy consumption decreased by 23%, using the method of VPS-FATC transmission, the packet loss rate decreased by 71%; by the method of VPIS-FATC transmission, packet loss rate decreased by 79%.
Finally, the iBES intelligent data acquisition system based on the above research results, the intelligent function is reflected in: (1) self configuration function, when the network is interrupted, the configuration information can be independently read SD card storage, avoid loss of energy consumption data; (2) intelligent sampling function, through frequency sampling Lebesgue, sampling to optimize sampling of energy consumption data, while ensuring the requirements of changing trend of energy consumption data, saving data of a large amount of storage space; (3) intelligent transmission control method, according to the energy consumption of the packet transmission time interval network congestion dynamic adjustment of next time, packet size, network load to adapt to the impact of changes the data transmission quality and improve energy efficiency.

【学位授予单位】：大连理工大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TP391.44;TN929.5;TU111.195

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