Optimizing the Operation of Energy Storage Embedded Energy Hub Concerning the Resilience Index of Critical Load

Dealing with high-impact events in energy hubs requires increasing resistance and restoration capability in multi-carrier energy systems. Assessing resilience as an essential and high priority measure must be done to ensure the optimal and economical operation of the energy hub. Thus, this paper introduces a cost-based optimization model of the energy hub that contains storage and considers resilience constraints and other general constraints. In this methodology, loads are categorized as critical and non-critical. The approach defines the highest priority for supplying the critical loads, whereas interruptions in non-critical loads must be minimized. That in this context, storages play a vital role. Four scenarios are investigated as normal situations and contingency cases. The contingency scenarios examine energy carrier interruptions such as electricity, gas, and heat input in an energy hub system. The mathematical model of this problem is founded based on a Mixed Integer Nonlinear Programming (MINLP), which DICOPT solver implements in GAMS. Mentioned model is evaluated by simulation of different case studies for the given energy hub test system. The trade-off between increasing critical load resiliency and reducing total costs is investigated. The results show that as critical load flexibility increases, total costs increase. In the worst-case scenario, only up to 13% of the total load can also be considered as critical load. Moreover, in different scenarios, the results demonstrate that using storage devices helps to increase resiliency Furthermore, in severe events, using storage devices has an increasing trend.