## 1 Introduction
[PERSON] [15] developed an optimization formulation for MG operations to minimize the power mismatch that can occur during the multiple duration of the event and extended the model that considers forecasting errors of the load and renewable energy generation in [16]. The authors of [17] studied an approach to managing energy storage systems and distributed generators to guarantee sufficient power resources when an event occurs. Further, [PERSON] et al. [17] employed a two-stage robust optimization to confirm that the availability of power resources takes precedence over MG operating costs. A more balanced MG operation between ensuring load survivability and reducing MG operating costs was pursued through a two-stage adaptive robust optimization model in [18]. The authors of [19] suggested a novel optimization formulation for a proactive MG operation that includes resilience cuts for the state of charge of energy storage systems. Further, they considered the dynamic cost of load shedding to reduce the likelihood of critical load curtailment. In [20], the authors demonstrated that a two-stage stochastic programming approach could significantly mitigate the effect of natural disasters by reflecting a wide range of uncertainties attributed to various factors in optimal MG operation. The authors of [21; 22] suggested an MG operation to maintain supply capability above a certain level during the on-event phase. They defined supply capability as the probability that the net demand falls within the spinning reserve range provided by the MG. The problem was formulated as a MILP with chance constraints in [21], and they assumed the forecast error of the net load to be a Gaussian distribution. In [22], the authors extended the problem of considering the reconfigurable capability of the MG during the on-event phase. [PERSON] et al. [23] synthesized resilience indexes and developed a multi-objective economic-resilience scheduling model for the microgrid. For the resilience enhancement, the authors of [23] suggest the first objective function as the cost of the MG operation and the second objective function as a combination of indices that include fragility, recovery efficiency, voltage, and lost load. However, conservatively operating MGs to be ready for all unforeseen events can be inefficient because this can lead to MGs having excess reserves, which is not economical in most situations. Furthermore, huge events, such as hurricanes, tropical storms, and blizzards, can typically be predicted at least 24-72 h in advance [6], and approximately 43.6 percent of events causing power outages and microgrid disconnections are predictable [24]. Therefore, in order to achieve resilient and cost-effective MG operations, it is crucial to establish a specified operating scheme for different operating conditions of MGs: the pre-event, after-warning, and on-event phases. In [24], the authors suggested an energy management method to procure adequate energy reserve for uninterruptible power supply to the critical load based on the predicted natural disaster. However, this study assumes that the levels of renewable generation and loads are given as determinative parameters without taking into account their uncertainty. We present a resilience-oriented MG operation strategy that proactively manages its energy resources to enhance the survival of important loads in anticipation of extended external grid outages. The goal is to reduce the impact on critical loads after the event occurs and to achieve cost-effectiveness in the MG operation by deliberately managing MG resources when a credible forecast of the event occurrence times is provided. The main contributions of this work are summarized as follows:  
* Proposing a new formulation for proactive microgrid management strategy: We propose an optimal resource scheduling method of the MG for resiliency enhancement to protect loads according to their importance from predicted extreme events.