Model predictive control applied to a heating system with PV panels and thermal energy storage

Abstract

Nowadays, a considerable amount of energy is consumed by the building sector, especially due to space heating purposes. The overall cost of this energy demand can be reduced with the use of renewable energy sources. However, the main challenge to overcome is the mismatch between the power generation from renewable s and the users demand. To tackle this issue, the main objective of the present study is to optimize the performance of a single-family house heating system based on an air-to-water heat pump, with thermal energy storage (TES) and PV panels, controlled through a model predictive control (MPC) strategy to minimize the final energy cost. Results obtained from several simulated cases point out that using this system, cost savings about 50% might be achieved. The analysis the impact of the TES system and PV panels in the heating operation together with a study of different working horizons and MPC settings are the novelties of this study.