Predictive energy management of residential buildings while self-reporting flexibility envelope

In recent years, renewable energy resources have been increasingly embedded in the distribution grids, raising new issues such as reverse power flows, and challenging the traditional distribution system operation. In order to mitigate these issues, it has been proposed to operate the distribution system more flexibly. For instance, residential buildings are ideal candidates to offer energy flexibility locally and defer avoidable and expensive system expansions. Due to advances in smart meter technologies and trends towards digitalization, it becomes more and more common that electrical appliances in residential buildings are equipped with remote communication and control capabilities. This paper aims at quantifying a flexibility envelope of actively controlled flexible buildings and at analyzing the sensitivity of flexibility levels with respect to system configuration, control strategy and objective function settings. We consider rooftop photovoltaic units, air sourced heat pumps for space heating and domestic hot water, thermal energy storage and electric vehicles. The results show that an optimal control aiming at minimizing energy costs while limiting peak power can lead to savings of up to 25% compared to the existing rule-based control. When carbon emissions are considered in the cost function, the optimized controller leads to an emission reduction of up to 21%. The time-dependent quantification of the flexibility envelope further reveals that high and low power levels can only be sustained for a limited period, whereas medium power levels can be sustained the longest.