A Research of Building Energy Diagnosis via Multiple Parameters Statistical Analysis Using the Concept of System Efficiency

• Main Authors: Ch''ng Yoong Pin, Ch''ng Yoong Pin
• Other Authors: 蔡尤溪
• Format: Others
• Language: en_US
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/71853172984525452442

碩士 === 國立臺北科技大學 === 能源與冷凍空調工程系碩士班 === 100 === In the era of global energy crisis many researchers focused on increasing the efficiency of the HVAC equipment. However the results of the relevant research have reached the limits and hence many start to explore the methods of energy management to improve the efficiency of the whole HVAC system. This research applied the idea of Building Energy Managing System (BEMS) using an innovative method to diagnose building HVAC systems and suggest control method to the important parameters. This method should be simple, precise, and user-friendly, taking the idea of Bin method and statistical analysis. This research collected and analyzed the output data from a complex simulation. The data library about the particular building HVAC system can be constructed and controlled through diagnosing the system by analyzing the corresponding data from the library. Through all these diagnosing and controlling method, system optimization can be achieved thus much unnecessary energy consumption can be avoided. This research used DOE – eQUEST as a tool to simulate a building model in order to obtain output data as prerequisite to diagnose a building. By inserting appropriate inputs, the simulations may provide correct data to be diagnosed. After the processing and analysis of the simulated results, a library was created by taking outdoor dry-bulb, wet-bulb temperatures and enthalpy differences as base parameters. The simulated results provide outputs which are System Performance Factor (SPF) of the whole HVAC system the HVAC Energy Consumption. The raw data is complex and abundant, hence the concept of Bin method was use to create Bin parameters such as Bin temperatures and Bin enthalpy diffenrences. Using t-distribution as base statistical method, the confidence intervals of desired output data are created, to be used for diagnosing purpose. The data collected was a scattering data with some unwanted desired information. Therefore, the data were statistically filtered and collected since not all data is appropriate. However, the results show that the method is fit for predicting or estimating the desired result data such as energy consumption and system performance, although only a small portion of the simulated data could be collected from simulation data. This database provided standards or bases to be compared or verified on real-time measurement. In short, this research showed a potential of diagnosing buildings almost accurate as the simulations while only few steps have to be followed with the researched method, considering the building is similar as the modeled building. Control system may be attached onto the diagnosing tool in order to provide complete system of BEMS.