Jens Engel, Thomas Schmitt, Tobias Rodemann, Jürgen Adamy, "Hierarchical Economic Model Predictive Control Approach for a Building Energy Management System With Scenario-Driven EV Charging", IEEE Transactions on Smart Grid, vol. 13, no. 4, pp. 3082 - 3093, 2022.

To deal with the increasing number of EVs and their effect on the infrastructure, intelligent and coordinated charge management is necessary. In this paper, this problem is considered in the context of a commercial building energy management system (BEMS) with V2G-capable employee EV charging stations (EVCS). We propose a hierarchical economic model predictive control (EMPC) scheme for the operation of the BEMS and the integration of EV charge management. An aggregator plans the operation of the BEMS under consideration of its components and an aggregated perspective of the EVCS. A distributor then allots the aggregated charge power to the individual EVCS. Both layers employ EMPC to jointly consider the objectives of monetary costs, building temperature deviation, and EV charge satisfaction as well as battery degradation. For the predictions of the EV behaviour, scenario generation based on usage data and user input is employed. The main contributions of this paper are the symmetric consideration of EV charging objectives using EMPC in both levels of the hierarchy, as well as the use of user inputs to improve behaviour predictions.