The role of energy storage systems in resilience enhancement of health care centers with critical loads

Due to the spread of pandemic coronavims disease (COVID-19), health care centers have been encountered an increasing number of infected patients. Therefore, the resilience of hospitals during unpredicted power outages would be a concerning issue that need to be addressed appropriately. Electricity outage can endanger patients' lives, especially those who have needed immediate special care. In this study, a hybrid micmgrid (MG) including renewable energy sources (RESs), energy storage systems (ESSs), and diesel generators (DGs) is proposed to enhance the hospital's resilience during unpredicted power outages. To evaluate the resilience performance of the proposed MG, random outages are generated in different days of the year. Furthermore, a resilience index is introduced to measure the amount of unmet electrical load demand. Based on the optimization results, the resilient configuration consists of the wind turbine (WT) system, DG, ESS, and bi-directional converter. However, the optimum economic configuration is based on WT, DG, and bi-directional converter. In the resilient configuration, the WT system supplies most of the load demand over the optimization year. The surplus generated electricity by the WT system is directly sold-back to the main grid based on the predefined feed-in-tariff (FiT) rate. Simulation results show that the optimal operation of the ESS has improved the resilience of MG during unpredicted grid outages. The reliability of the hospital is also increased by considering ESS and DG in the architecture of the MG. The net present cost (NPC) and the cost of energy (COE) of the proposed system are 103,507 US$ and 272x10(-6) US$/kW, respectively. Optimization results based on the grid-load system as the base case and those of hybrid energy systems indicates that the utilization of the ESS has led to an increase in NPC and COE of the resilient MG. Moreover, the proposed resilient MG produces fewer greenhouse emissions in comparison with optimum economic configuration regarding the ESS utilization. The results of sensitivity analysis on the number and duration of outages indicate the significant effect of grid outages on the configuration and economic of the system.