Optimal Design and Control of Behind-the-Meter Resources for Retail Buildings with EV Fast Charging

Abstract

The growing electrification of buildings and vehicles, while a natural step towards achieving global decarbonization, poses some challenges for the electric grid in terms of power consumption. One way of addressing them is by deploying onsite, behind-the-meter resources (BTMR), such as battery energy storage and solar PV generation. The optimal design of these systems, however, is a demanding task that depends on the integration of multiple complex subsystems. In this work, the optimal integrated design and dispatch of BTMR systems for retail buildings with electric vehicle fast charging stations is addressed. A framework is proposed, combining high-fidelity simulation (of buildings, electric vehicle fast charging stations, and BTMR), predictive control strategies with closed-loop implementation, and a derivative-free design method that explores parallelization and high-performance computing. Focus is given to the design layer, highlighting the effect of parallelization on the choice of the method, computational effort, and types of results. A case study of a big-box grocery store with an EV fast charging station is presented, and its optimal BTMR system is identified in terms of equipment sizes, costs (capital, utility, lifecycle, and levelized) and resiliency against outages, demonstrating great potential for real-world applications.