The effect of changing heat use patterns on residential energy efficiency in a Japanese smart community

In light of the prospective development of smart communities and the significant effect of residential energy consumption on global CO₂ emissions, addressing sustainable household energy efficiency solutions is extremely critical. Given the lack of properly designated energy models for residential energy reduction, the primary objective of this study is to implement integrated energy prediction models and occupant-related parameters in proposing human-centered energy-saving and low-carbon building solutions. Specifically, on-site electricity monitoring and behavioral questionnaires were conducted before inputting the real-time data into physics-based modeling for building energy forecasts. Calculated energy-saving ratios are used to assess the influence levels of heating usage patterns and discuss the potential of energy efficiency scenarios. The findings highlight that household attributes and energy management systems substantially enhance the dwelling's energy efficiency. Prominent impact factors are family income, property ownership, and energy consumption patterns, which may also pertain to occupant habits. Consequently, a rigorous focus must be placed on these elements, including controlling setpoints and schedules for primary residential end-use systems such as Heating Setpoints and Schedule Modes, which significantly reduces up to 38% of energy consumption in heating systems and 14% in total household energy end-uses. The paper uncovers the significance of integrating multi-directional approaches, including physical and social elements in modeling, predicting, and implementing a holistic human-centered smart system. This system correlates occupant activities with household energy consumption patterns to optimize energy savings while maintaining occupant comfort and fostering a sustainable indoor environment in smart communities.