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Analysis of Building Model Forecasts using Autonomous HVAC Optimization System for Residential Neighborhood

Publication Type
Conference Paper
Book Title
2023 IEEE Energy Conversion Congress and Exposition (ECCE)
Publication Date
Page Numbers
1218 to 1224
Publisher Location
New Jersey, United States of America
Conference Name
IEEE Energy Conversion Congress and Exposition (ECCE)
Conference Location
Knoxville, Tennessee, United States of America
Conference Sponsor
Conference Date

Heating, ventilation, and air conditioning (HVAC) systems account for the highest share of home energy consumption in the United States. Optimized HVAC control can provide thermal improved comfort to the occupants, improve energy efficiency, reduce energy cost, and support grid services. In this paper, we discuss a multi-agent and cloud-based software framework that has been deployed in occupied residential neighborhood. This system enables automatic data collection, learning, optimization, and dispatches signals to neighborhood devices. HVAC optimization is based on model predictive control (MPC). Since the operational performance of MPC depends on model forecasting accuracy, it is crucial to evaluate the model continuously and modify or retrain it as necessary. In this research, we developed an automated workflow to evaluate the performance of temperature and power forecasts based on measured data in the real world. This will provide researchers with a deeper understanding of the model and how it can be improved.