Abstract
Residential buildings, accounting for 37% of the total electricity consumption in the United States, are suitable for demand response (DR) programs to support effective and economical operation of the power system. A home energy management system (HEMS) enables residential buildings to participate in such programs, but it is also important for HEMS to account for occupant preferences to ensure occupant satisfaction. For example, people who prefer a higher thermal comfort level are likely to consume more energy. In this study, we used foresee™, a HEMS developed by the National Renewable Energy Lab (NREL), to perform a sensitivity analysis of occupant preferences with the following objectives: minimize utility cost, minimize carbon footprint, and maximize thermal comfort. To incorporate the preferences into the HEMS, the SMARTER method was used to derive a set of weighting factors for each objective. We performed week-long building energy simulations using a model of a home in Fort Collins, Colorado, where there is mandatory time-of-use electricity rate structure. The foresee™ HEMS was used to control the home with six different sets of occupant preferences. The study shows that occupant preferences can have a significant impact on energy consumption and is important to consider when modeling residential buildings. Results show that the HEMS could achieve energy reduction ranging from 3% to 21%, cost savings ranging from 5% to 24%, and carbon emission reduction ranging from 3% to 21%, while also maintaining a low thermal discomfort level ranging from 0.78 K-hour to 6.47 K-hour in a one-week period during winter. These outcomes quantify the impact of varying occupant preferences and will be useful in controlling the electrical grid and developing HEMS solutions.
Sensitivity analysis of the effect of airflow velocity on the thermal comfort in underground mines