The purpose of this study is to reduce the energy cost of the low-income households in the hot and humid climates of the U.S. and thereby to help them afford comfortable homes. In this perspective, a new HVAC energy saving strategy, i.e. “partial conditioning” was modeled and its potential to reduce the HVAC energy consumption of the low income homes in Texas was quantified. The “partial conditioning” strategy combined three primary ideas: 1) using historic courtyard building schemes to provide a buffer zone between conditioned spaces, 2) zoning and applying occupancy based heating/cooling in each zone, and 3) reusing the conditioned air returning from the occupied zones in the unoccupied zones before it is returned to the system. The study was conducted in four steps: 1) data collection, 2) baseline design and modeling, 3) partial conditioning design and modeling, and 4) analyses and recommendations. First, a site visit was held to the Habitat for Humanity office in Bryan, Texas to collect data on the characteristics of the Habitat for Humanity houses built in Bryan. Second, a base-line Habitat for Humanity house was designed and modeled based on this information along with multiple other resources including International Energy Conservation Code 2012 and Building America benchmark definitions. A detailed comparison was made between the commonly used energy modeling tools (DOE-2.1e, EnergyPlus and TRNSYS) and a modeling method was developed for the estimation of the baseline energy consumption. Third, the “partial conditioning” strategy was introduced into the baseline energy model to simulate a partially conditioned atrium house. As the occupied zone and the direction of the airflow changed throughout the year in the partially conditioned house, this step required an innovative air loop model with interzonal air ducts that allowed for sched- uled bi-directional airflow. This air loop was modeled with the AirflowNetwork model of EnergyPlus. Fourth, the modeling results were analyzed and discussed to determine the performance of the partial conditioning strategy in a hot and humid climate. It was found that partial conditioning strategy can provide substantial (37%-46%) reduction in the overall HVAC energy consumption of small residences (∼1,000 ft2) in hot and humid climates while performing better in meeting the temperature set points in each room. It was also found that the quantity of the energy savings that can be obtained with the partial conditioning strategy depends significantly on the ground coupling condition of the house for low rise residential buildings.

Energy efficiency of buildings is an important measure to obtain a reduction of emissions of greenhouse gases since the building sector currently emits 40% of the total emissions in the world. A modification of control systems within commercial buildings is shown in earlier research to have a possible energy saving. The conventional control is usually controlled by fixed schedules and might presumably result in unnecessary energy use, since it operates at full capacity during the set period. Thus, modification of such control systems in commercial buildings might have a significant energy efficiency potential. The aim was to investigate the overlooked effect of human behavior on buildings’ energy usage. The hypothesis was a significant energy saving could be achieved if control systems use occupancy-based (OB) control instead of a conventional control based on fixed schedules. Firstly, occupancy data acquired from motion sensors in offices in the natural science building at Umeå University was used to create average occupancy patterns. The occupancy patterns were used to create various schedules with different objectives while representing the average floor occupancy. Secondly, the created schedules were used in the building simulation program IDA ICE. The simulation program was used to investigate how the energy consumption changed if the control system was changed to operate as OB control. Lastly, the potential energy savings were calculated with values from the simulations. The results showed that an average energy saving of 14% was achievable if OB control was used instead of fixed-schedule control. It was also found that a potential energy saving largely depends on the behavior of the occupants. Depending on the occupancy pattern and intensity, a potential energy saving of 10% to 17% was obtained. The results also signify the importance of well-functioning sensors and accurate detection. Additionally, it was found that the summer months had less potential energy savings compared to the other months. The results show that human behavior can have a large effect on the energy consumption within a building. Thus, implementing occupancy information in control systems might yield a potential energy saving. The intensity of occupants’ affects the potential energy saving. It was found that a higher intensity yields a lower potential while a lower intensity yields a larger potential energy saving. An interesting theory regarding the sensors was found after studying the results. It was found that it might be possible to let six arbitrarily offices represent 40 offices in an office environment. An important measure when collecting personal occupancy information is to inform the occupants of the experiment, as to not have problems with perceived privacy. Including the occupants in the data-collecting project might yield a better understanding and thus better collaboration with the experiment.