Energy Management System Based on Predictive Control for a Commercial Smart Building with PV, BESS and EV Charging Providing Tertiary Frequency Regulation

This manuscript presents an energy management strategy (EMS) for a commercial smart building participating in a tertiary frequency regulation market. The building integrates non-controllable components, such as loads and photovoltaic generation, and controllable resources such as a battery storage system and a set of electric vehicle (EV) chargers that are available for customers of the smart building. The EMS is based on model predictive control due to its innate ability to deal with operational constraints and different optimization criteria, which are critical for the operation of the EMS, and consists of two stages. The first iteratively optimizes energy costs and revenues from tertiary regulation reserves and activations in order to determine the optimal operation of the smart building and the regulation offers in nominal conditions. Then, a second problem determines the operation whenever an activation request is made. Simulation-based analyses are performed to study the performance of the EMS and its financial viability in diverse scenarios relevant to the smart commercial building. The results show that profits are greater if both upward and downward regulation can be provided, for a larger number of EVs and chargers and for longer connection times. Most notably, incomes from regulation almost match operation costs for a large number of chargers and EVs (240), obtaining a deficit of only EUR 39.12 for a day of operations.