Abstract

Energy management in buildings equipped with renewable energy is vital for reducing electricity costs and maximizing occupant comfort. Despite several studies on the scheduling of appliances, a battery, and heating, ventilating, and air-conditioning (HVAC), there is a lack of a comprehensive and time-scalable approach that integrates predictive information such as renewable generation and thermal comfort. In this paper, we propose an online energy management framework to incorporate the optimal energy scheduling and prediction model of PV generation and thermal comfort by the model predictive control (MPC) approach. The energy management problem is formulated as coordinated three optimization problems covering a fast and slow time-scale.This reduces the time complexity without a significant negative impact on the global nature and quality of the result. Experimental results show that the proposed framework achieves optimal energy management that takes into account the trade-off between the electricity bill and thermal comfort.

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