Smart Control Strategy for PV and Heat Pump System Utilizing Thermal and Electrical Storage and Forecast Services
Abstract
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 proposed control strategy is applied to the base case to optimize the available PV electricity production using short-term weather and electricity price forecasts. The three smart and predictive control algorithms were developed with the scope to minimize final energy by the use of the thermal storage of the building, the hot water tank and electrical storage. Results show reduction of the final energy by 26.4%, increase of the self-consumption of 49.5% and decrease of the annual cost of 15% when using the forecast services in combination with thermal and electrical storage, in comparison to the base case.