An algorithm for the optimal management of air-source heat pumps and PV systems

The progressive decentralization and decarbonisation of the energy system calls for an increased flexibility of the demand side. Model predictive control techniques can help users consume more efficiently by shifting their energy demand toward most convenient time windows. The present work proposes an algorithm to optimally shift the heating demand of a residential building equipped with an air-source heat pump and PV panels by exploiting the inertia provided by its thermal mass. Results show that the proposed look-ahead control strategy is able to achieve significant cost savings for the users without affecting the thermal comfort in the indoor environment.