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The building sector accounts for almost 40 percent of the global energyconsumption. This reveals a great opportunity to exploit renewable energyresources in buildings to achieve the climate target. In this context, thispaper offers a building energy system embracing a heat pump, a thermal energystorage system along with grid-connected photovoltaic thermal (PVT) collectorsto supply both electric and thermal energy demands of the building with minimumoperating cost. To this end, the paper develops a stochastic model predictivecontrol (MPC) strategy to optimally determine the set-point of the wholebuilding energy system while accounting for the uncertainties associated withthe PVT energy generation. This system enables the building to 1-shift itselectric demand from high-peak to off-peak hours and 2- sell electricity to thegrid to make energy arbitrage.

Uncertainty-Cognizant Model Predictive Control for Energy Management of Residential Buildings with PVT and Thermal Energy Storage