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This paper defines a smart home use case to automatically adjust home temperature and/or hot water. The main objective is to reduce the energy consumption of cooling, heating and hot water systems in smart homes. To this end, the residents set a temperature (i.e., X degree Celsius) for home and/or hot water. When the residents leave homes (e.g., for work), they turn off the cooling or heating devices. A few minutes before arriving at their residences, the cooling or heating devices start working automatically to adjust the home or water temperature according to the residents' preference (i.e., X degree Celsius). This can help reduce the energy consumption of these devices. To estimate the arrival time of the residents (i.e., drivers), this paper uses a machine learning-based street traffic prediction system. Unlike many related works that use machine learning for tracking and predicting residents' behaviors inside their homes, this paper focuses on predicting resident behavior outside their home (i.e., arrival time as a context) to reduce the energy consumption of smart homes. One main objective of this paper is to find the most appropriate machine learning and neural network-based (MLNN) algorithm that can be integrated into the street traffic prediction system. To evaluate the performance of several MLNN algorithms, we utilize an Uber's dataset for the city of San Francisco and complete the missing values by applying an imputation algorithm. The prediction system can also be used as a route recommender to offer the quickest route for drivers. [ABSTRACT FROM AUTHOR]

This paper evaluates through experimental testing a prototype of switchable insulated shading (SIS) systems suitable for windows to optimize solar heat gains in order to maintain indoor thermal comfort. Specifically, the paper describes a laboratory testing procedure and measurement results for SHGC values specific to various SIS designs and operation settings using a box calorimeter set-up. The SIS prototype can modulate continuously its optical and thermal properties including U-value and SHGC using rotating insulation layers controlled through an actuator to a specific slate angle setting. The results of the experimental testing confirm that SHGC value for the SIS prototype is correlated to the slate angle of the insulated layers. This correlation remains applicable for any SIS insulation thickness. The measured data are used to assess the potential energy efficiency benefits from SIS when applied to windows for US homes. In particular, a prototypical housing unit located in three US cities is considered to evaluate the energy efficiency potential for switchable opaque insulated shading systems. The results indicate that SIS systems can achieve up to 8.3%, 11.3%, and 11.4% in annual HVAC energy consumption compared to no-shading cases for dwellings located in Golden, CO (representing a cold climate), Phoenix, AZ (representing a hot climate), and San Francisco, CA (representing a mild climate), respectively. [ABSTRACT FROM AUTHOR]

• A novel sliding/rotating overhangs is presented and evaluated for US residential buildings. • Both energy efficiency and environmental impacts of the dynamic overhangs are evaluated. • PV-integrated control strategies are considered to operate the dynamic overhangs. • The PV-integrated dynamic overhangs can result in net-zero building designs. The paper evaluates the benefits of integrating PV arrays with sliding and rotating overhangs to both generate electricity and reduce heating and cooling thermal loads for housing units in US apartment buildings. Optimal controls to operate the sliding-rotating overhangs are considered to minimize annual net energy demands with and without the integrated PV arrays. A series of sensitivity analyses is performed to assess the impact of design and operating conditions on the energy performance as well as the environmental impacts of the sliding-rotating overhangs. The analysis results clearly indicate that when integrated with PV modules, sliding overhangs can significantly reduce the energy demand for US housing units especially when they are set at the optimal angles specific to the building location to maximize their electricity generation and solar shading effects. Specifically, it is found that sliding overhangs can not only reduce energy demand but also can achieve net-zero energy conditions for US apartment units with large windows and located in mild climates even when monthly adjustments are applied to operate the shading systems. For instance, 9.2% of the total energy use of an apartment housing unit located in Boulder, CO, can be reduced using the sliding-rotating overhang with no-PV. In San Francisco, CA, more than 100% of the apartment housing unit energy demand can be avoided using PV-integrated sliding-rotating overhangs. To minimize design and operation complexities, it is recommended to consider sliding-only overhangs set at the latitude of the location to reduce both heating and cooling demand as well as increase PV array output. For instance, it is found that sliding overhang set at the latitude angle can be sufficient to achieve net-zero status and even a carbon-neutral operation for an apartment housing unit located in San Francisco, CA, even when adjusted on a monthly basis. [ABSTRACT FROM AUTHOR]

A novel dynamic overhang system is evaluated in this paper when applied to control solar heat gains through windows of US residential buildings. In particular, the energy performance of the dynamic overhangs is compared to static systems using various operation scenarios. The main objective for the control strategies evaluated in the analysis is to minimize annual heating and cooling energy consumption when dynamic instead of static overhangs are applied to US residential buildings. The operation of the dynamic overhangs is adjusted to account for the range of positions allowed as well as the setting frequencies. In particular, the dynamic overhangs can be set on hourly, daily, and monthly basis depending on the window orientation and the time of the year. The analysis has indicated that the performance of the dynamic overhangs depend on their design specifications as well as on the window glazing type. However, the energy saving potential for the dynamic overhangs compared to static devices depend largely on the window size and the climate with significant reduction in cooling energy use achieved in hot and mild US climatic zones. Indeed, the dynamic overhangs can save over 45% of the air conditioning needs for US homes with window-to-wall ratio of 30% located in Phoenix, AZ, and San Francisco, CA, when automatically operated on hourly basis. [ABSTRACT FROM AUTHOR]