(186m) Physically Based Dynamic Modeling for Predictive Simulation of a Net-Zero Home

Building design has grown increasingly sophisticated throughout the decades. In recent years, assessment of building performance and sustainability has grown in popularity as the U.S. Green Building Council published LEED certifications for new and existing buildings. The LEED rating system uses standards developed by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) to assess thermal comfort, air quality, energy building performance, and heat, ventilation, and air conditioning (HVAC) operation. Submittal of energy performance building reports for construction design and green building rating systems is becoming more common as building performance assessment software becomes more widely available.

The University of Maryland currently is a participant in the Solar Decathlon intercollegiate competition sponsored by the Department of Energy. The University of Maryland's reACT team is working to construct a net-zero solar powered house for judging in Denver, CO in October 2017. Concurrently with the housing design, a substantial effort was put into assessing the projected building performance to aid in the design process and to set the stage for model-based home automation. While software such as OpenStudio and BEOPT are available and were used for year-averaged performance reports, a physically based model of the house was built from scratch to serve as a real-time simulation of virtual versions of reACT located in College Park, MD and Denver, CO.

In its current configuration, the reACT house simulation system runs automatically once a day in the early morning hours after hourly outdoor air temperature and cloud cover forecasts are downloaded from weather prediction websites corresponding to the location of each house. With the day's weather information in hand, the simulator predicts each house's expected performance over the day using the following simulation element modules:

1) A model predicting the sun's normal irradiance as a function of house location and time of year is combined with the cloud-cover forecasts to determine the incident global irradiance on each external surface of the house, including all windows and PV modules.

2) A single-diode equivalent-circuit PV cell model is identified using the PV manufacturer's performance data to determine the current versus voltage characteristics of the PV arrays over the course of the day using the predicted irradiance levels.

3) Nominal scheduled electrical loads have been identified and are stored in an XML file; the loads are read by the simulator and used to compute energy consumption associated with regularly scheduled events.

4) Incident radiation and indoor/outdoor air temperature variations are used to determine heat transfer rates through the house external walls.

5) External wall and window heat transfer, direct radiation through the house windows, and waste heat produced within the house determine HVAC loads, indoor air temperature, and overall net power production.

This paper will present the architecture, validation (using a previous Maryland entry to the Solar Decathlon), and ultimate performance of the virtual home simulator as part of a supervisory home automation system. Current performance of the virtual homes can be found at http://reactvirtual.eng.umd.edu/index.html