Resilience-Oriented Behind-the-Meter Energy Storage System Evaluation for Mission-Critical Facilities

Immunization of mission-critical facilities such as hospitals and first responders against power outages is crucial for the operators due to their significant value of the lost load, affecting citizens' lives. This paper proposes a novel evaluating framework which enables facility operators to efficiently size and optimally dispatch their behind-the-meter energy storage systems (BTM-ESS) for resiliency purposes during grid emergencies. The proposed framework, formulated as a mixed integer linear programming model, aids facility operators to quantify the impacts of various BTM-ESSs on resilience enhancement where the Avoided Loss of Load (ALOL) is incorporated as the resilience indicator. BTM-ESS is assumed to be operated in both standalone and coupled with solar photovoltaic (PV) as an onside backup generation which is a viable energy solution for more prolonged power outages. The proposed model is developed on a probabilistic energy procurement model, aiming to minimize the facility's total operation cost. The uncertainty of power outages is characterized by a set of a large number of scenarios generated by the brute-force enumeration method. Additionally, to analyze the impacts of facilities' behaviors on the BTM-ESS evaluation procedure, a set of 24 facilities from different end use sectors with various functionalities are simulated by employing our in-house-developed building simulator, which is a physics-based simulation tool. Finally, the practicality of the proposed evaluating framework is investigated through two case studies where both short and long-duration grid outages are examined based on the historical outage data adopted from New Jersey, USA. The simulation results reveal that a BTM-ESS with 4 hours discharge duration that is sized at rated power equal to 50% or more of the facility's peak load generates sufficient resilience benefits for most of the 24 representative facilities in case of short-duration power outages.