The rapid tidal current near a lake inlet is transformed into electrical energy with Darius-type hydraulic turbine generators. When the tidal power generation is insufficient, the stored excess electric power generated from midnight to early morning of a representative day is used. The balance of energy supply and demand for all sampling events in a representative day must be predicted very accurately in a system with energy storage. In this study, electric power and heat demand are forecasted on the basis of weather data obtained from the Internet, and the corresponding values are used to plan the storage of electricity and heat from midnight to early morning. The results of the case analysis show the influence of the economic efficiency of the heating system, the capacity of the tidal power generator, the prediction error of the tidal power generator, and the insulation efficiency (Q-value) on the energy cost. Optimization of the introduced simulation model was considered. The objective functions of optimization were minimization of operation cost and facilities cost of the simulation model.