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

• URL: http://arxiv.org/abs/2201.08909v1
• Date: Fri, 21 Jan 2022 22:30:13 GMT
• Title: Uncertainty-Cognizant Model Predictive Control for Energy Management of Residential Buildings with PVT and Thermal Energy Storage
• Authors: Hossein Kalantar-Neyestanaki, Madjid Soltani
• Abstract summary: Building sector accounts for almost 40 percent of the global energy consumption. This paper offers a building energy system embracing a heat pump, a thermal energy storage system along with grid-connected thermal photovoltaic (PVT) collectors.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The building sector accounts for almost 40 percent of the global energy consumption. This reveals a great opportunity to exploit renewable energy resources in buildings to achieve the climate target. In this context, this paper offers a building energy system embracing a heat pump, a thermal energy storage system along with grid-connected photovoltaic thermal (PVT) collectors to supply both electric and thermal energy demands of the building with minimum operating cost. To this end, the paper develops a stochastic model predictive control (MPC) strategy to optimally determine the set-point of the whole building energy system while accounting for the uncertainties associated with the PVT energy generation. This system enables the building to 1-shift its electric demand from high-peak to off-peak hours and 2- sell electricity to the grid to make energy arbitrage.

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