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This study proposes a method of specifying where there is leeway for improvement of thermal performance of an office building by identifying the thermal performance parameters, which refers to such as the insulation and fraction of solar shading, based on operating data. This can contribute to the planning of energy reduction retrofit. The proposed method combines two methods: identifying parameters using a thermal load calculation program and conducting an inspection following a prepared diagnosis flow. Various parameters within the input data in the thermal load calculation program are classified into a small number of group, and the representative parameters of each group are identified based on measured thermal load and room temperature. The identified and standard parameters are compared and, judging from the differences between them, it is determined whether or not each of the specified parameters is in an abnormal state. Afterwards, a diagnosis flow is proposed to specify which individual unknown parameters cause the abnormality. Introduction When the quantity of energy used in a completed building is larger than predicted during the design period, it must be determined whether there are areas where energy could be reduced, for instance, in the building envelope, in room usage, and in equipment and machinery. Many research studies in Tobias Maile, Vladimir Bazjanac, and Martin Fischer (2012) and E.H.Borgstein, R.Lamberts, and J.L.M.Hensen (2016), whose titles include the word “commissioning”, have been conducted to improve operation of equipment and machinery. However, there have been few research studies have considered the building envelope or the room usage. In the field of research for residential buildings, many studies in Okuyama Hiroyasu and Onishi Yoshinori (2012) and M.J.Jiménez, H.Madsen, and K.K.Andersen (2008) have conducted to identify the insulation performance. However, their studies conducted case studies in small-size buildings where nobody was living. The objective of this study is to propose a method for estimating the thermal performance such as insulation and infiltration of occupied office buildings using actual operating data. This method is expected to be contributed to do energy-saving action for practical situations. Figure 1 shows the proposed methodology. To establish the methodology, energy simulation is firstly conducted to identify unknown building parameters such as thermal insulation thickness and ceiling height using a thermal load calculation program. The unknown parameters are classified into two groups which are representatives of the considerable parameters. The proposed method identifies two parameters of the groups to briefly approximate thermal performance. Secondary, a diagnosis flow is proposed to specify which individual unknown parameters cause the abnormality in a representative. In this study, we use virtual measurement data generated by the thermal load calculation program. The virtual measurement data was generated under the condition that some specific parameters— amount of outside air, infiltration rate, and fraction of solar shading— had abnormal values comparing to standard values. The identification result shows the possibility of detecting abnormalities in parameters. Figure 1: Proposed methodology for thermal performance diagnosis Outline of parameter identification and diagnosis flow Figure 2 shows an overview of proposed parameter identification. There are the two groups which are mentioned in Introduction section: 1) the overall conductance group (Group 1) which represents some related parameters such as the amount of outside air and infiltration rate, 2) the steady thermal load group (Group 2) which represents some parameters such as a fraction of solar shading. What is called at the beginning "representative parameter" is instead a calibration dimensionless index, which is used in equation 1) to vary all the physical properties of a group with the same Measurement data Drawing information※1 Parameter identification※2 Detection of abnormal representative parameter※3

Diagnoses Of Building Thermal Characteristics By Parameter Identification And Manual Inspection.