PI: Anjan Bose
Co-PI(s):
Sponsor: Avista Corporation
Award Amount: $200,000
Project Period: 02/2019 – 12/2021
Summary: Data Sensing: High resolution input data is required to obtain a detailed prediction of the building performance. High resolution information about hourly weather information, building geometric and HVAC description (such as multi-zone airflow and extensive HVAC specification capabilities) are required to assist calibration. This task mainly concentrates on the application of specialized software and hardware tools (e.g. Power Quality meters for high resolution end use power data) to gather and analyze data over short period in order to calibrate building models along with existing long term data. Model Calibration: In order to use the building models with any degree of confidence, it is necessary to calibrate the Building Energy Performance Simulation Model (BEPS) with the measured building performance data. This task involves using suitable calibration algorithm to get reasonable agreement between the measured and simulated data. It also involves incorporating model parameter uncertainty in the building models in order to predict the ‘equifinality’ of the simulation models.