The transition from fossil fuels to renewable energy in multi-family houses is crucial for achieving climate-neutral residential buildings. A key technology in this transition is the heat pump, which operates most efficiently at low supply temperatures of the heating system. However, high temperatures are often required to meet hygienic standards in central water heating systems, as domestic hot water must circulate between the basement and the apartments at temperatures of up to 60 ℃ to disinfect against Legionella bacteria. Heat interface units (decentralized instantaneous water heaters) can hydraulically decouple domestic hot water from heat storage by using decentralized heat exchangers in each apartment, thereby lowering temperature levels in heating centers. Piping losses remain significant for maintaining user comfort but can be reduced through smart operating strategies. This paper examines predictive operating strategies for heating systems with heat interface units and a heat pump. A predictive, demand-based keep-warm function for heat interface units, predictive variable network flow temperatures, and predictive tank charging were tested. These strategies were analyzed using dynamic thermal simulation in TRNSYS for reduction of pipe losses and increasing of the efficiency of the heat pump. The study shows that a smart keep-warm function and predictive variable network temperature can reduce the pipe losses up to 19% and therefore the electricity consumption of the heat pump up to 6%. In contrast, predictive charging of the tank resulted in only marginal savings in the final energy consumption.