Data Quality Guarantee In Monitoring And Transmission Process Of Internet Of Building Energy Systems

Building energy conservation is one of the most important topics to alleviate energy supply shortage and reduce pollutant emission, realize the sustainable development of building energy and environment, with the objective of which is to increase the energy utilization efficiency and decrease energy consumption. Building energy consumption monitoring platform (BECMP) and Internet of Building Energy Systems (iBES) provide a powerful theoretical and technical support to promote building energy efficiency evaluation and energy-saving renovation in our country, which has important practical and long-term significance. Energy consumption data of iBES plays an important role during the process of energy saving, which could not only be guidance for operation management, but also the basis of energy-saving diagnosis and evaluation of energy efficiency. However, how to ensure the data quality is a key issue for building energy conservation, especially for the public buildings. Based on the investigation of data analysis for iBES application and experiments of network transmission quality, it is found that there are two vital factors affect the data quality. One is the abnormal data caused by interference in perception layer channel, and the other is data transmission obstacles when encounters network congestion. In order to solve these problems, the researches of this dissertation are as follows:Firstly, the approach to ensure data quality in monitoring of BECMP was studied in order to solve the poor communication reliability problem, which was caused by severe working condition and serious electromagnetic interference. Three parameters of RS485fieldbus, namely, biasing resistor, terminal resistor and bus load were taken as research objects in order to solve the problem. Equivalent circuit model of RS485fieldbus was proposed and then the range of biasing resistor value was obtained by Kirchhoff’s Current Law (KCL) and current limiting method. Furthermore, the effect of biasing resistor on terminal resistor and bus load is also presented. Results showed that the rational value range of biasing resistor was556Q-716&, and665Ω was the best value for biasing resistor in engineering, which could not only ensure the stability communication, but also gain the maximum bus load. The findings could provide technology guidance for future engineering application.Secondly, in view of the complex network structure and diversification of the transport layer of iBES, network delay, which could evaluate the performance network communication, was selected as the breakthrough point in order to grasp the communication quality of network. S-Ping tool was developed to measure the distribution characteristic of the network delay from several different aspects, and then proposed a network delay prediction method based on Wavelet-Autoregressive Integrated Moving Average model (W-ARIMA) to judge the network transmission quality. The result shows that, the W-ARIMA algorithm has a high prediction precision and is able to forecast the congestion level of network, which establishes a good foundation for optimizing energy consumption data transmission.Thirdly, a fuzzy control transmission method was presented in order to solve the problem caused by network congestion based on the results of network delay prediction, which could adjust the data packet interval or data packet size. The results from Matlab simulation experiments indicated that, the packet loss ratio decreased23%and71%by adjusting packet interval (VPI-FATC) and packet size (VPS-FATC), respectively, compared to the default transmission method, furthermore, the value is79%if two methods (VPIS-FATC) used in combination.Finally, this paper developed a smart data collector for iBES based on the above-mentioned theoretical research results. The specific functions of this data collector are:(1) It could do a self-configuration from SD card avoiding to loss data when network breaks down.(2) It could realize optimization of data acquisition by frequency changing sampling method and Lebesgue sampling method, which could save a large amount of storage in database.(3) It could adjust the data transmission strategy according to the network congestion level by changing packet interval and packet size to adapt the changes of network load, and improve the quality and efficiency of data transmission.