Distributed energy resources (DERs) such as residential fuel cell combined heat and power systems, air conditioners, or energy storage systems are expected to contribute to energy savings and power system operations. Additional energy savings could be achieved by using high-efficiency equipment with optimized control by energy management systems (EMSs). Both electricity and hot water demand data are needed to optimize the DER operation. An EMS realizes optimal operation by prediction, planning, and real-time operation. Accumulating basic data on electricity and hot water demand is essential for the development of prediction methods needed for EMS. Energy demand is related to the activity patterns of residents, which vary according to factors such as the number of people at home and what they do there. The purpose of this study was to accumulate electricity and hot water demand data from residential dwellings, and then analyze the data to obtain useful knowledge for demand prediction to apply to an EMS. For 4 years, detailed measurements of electricity and hot water demand were made at an apartment building. Differences between weekdays, weekends, and holidays; differences among households; frequency of bathtub use; and variations of activity patterns by year were analyzed.