Abstract
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.
Highlights
To quantify the resilience impacts of various behind-the-meter energy storage systems (BTM-energy storage system (ESS)), we introduce the Avoided Loss of Load (ALOL), which measures the expected energy not served under all possible grid outage scenarios over the planning horizon as a proxy indicating the value of resilience
THE PROPOSED PROBABILISTIC ENERGY PROCUREMENT-BASED BTM-ESS EVALUATION MODEL we present the mathematical formulation of our proposed facility-level BTM-ESS evaluation framework, where the impacts of ESS on the resilience of various facilities are quantified by employing an appropriate resilience index
A probabilistic energy procurement-based model was developed where the brute-force enumeration method was employed to generate a set of a large number of outage scenarios to characterize the grid outage uncertainty for both short and long-duration outages
Summary
The technical literature, lacks a comprehensive evaluation framework that aids mission-critical facility operators to optimize both size and dispatch of their BTM-ESSs to achieve their resiliency goals under uncertain grid outages, including short- and long-duration events. From the facility operator’s perspective, the proposed evaluating framework anticipates the expected utility grid outages of both shortand long-duration events during the planning horizon, thence co-optimizes the BTM solar-plus-storage system dispatches based on the candidate ESS sizes to achieve the desired resiliency goals. The remainder of this paper is organized as follows: The proposed probabilistic energy procurement-based BTM-ESS evaluation model is presented, where the uncertainty of the utility grid outage events is first characterized using a scenario-based approach. The mathematical formulation of the proposed model is elaborated in the following
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