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In this study, a detailed model of a single-family house with exhaust air heat pump, PV system and energy hub developed in the simulation software TRNSYS 17 is used to evaluate energy management algorithms that utilize weather and electricity price forecasts. A system with independent PV and heat pump is used as a base case. The three smart and predictive control algorithms were developed with the scope to minimize annual cost of bought electricity by the use of the thermal storage of the building, the hot water tank and electrical storage. The results show reduction of the final energy of 26.4%, increase of the self-consumption to 60% and decrease of the net annual cost for electricity of 15% when using the forecast services in combination with thermal and electrical storage compared to the base case.