Considering PV, double-fed induction generator (DFIG)-based wind, diesel generator, and critical and non-critical loads, an efficient under frequency control and the energy management of an RESs-based MG were presented [5]. Additionally, an efficient power management control for MGs with energy storage was presented [6]. The proposed control scheme increases the reliability and resiliency of the MG. Both the MG and its controller were developed in a Real-Time Digital Simulator (RTDS). Due to the uncertainties of both loads and RESs, an optimal operation of RESs was probabilistically investigated [7]. An optimal PQ control scheme was proposed to control and share predefined injected real and reactive powers of the MG [8]. An optimal design of MGs in autonomous and grid-connected modes was introduced [3]. For both modes, the controller parameters of the MG are optimally designed to make the MG more stable after getting disturbed. The dynamic operation and control strategies for a hybrid MG involving wind, PV, fuel cell, and static VAR compensator (SVC) were examined. This stand-alone MG could effectively extract the maximum power from the wind and PV energy sources [9]. A static synchronous compensator (STATCOM) was controlled using a novel intelligent controller to reduce the power fluctuations, voltage support, and damping in an MG system [10]. To improve the MG protection system and reduce the maximum transient overvoltage of a wind turbine, a grounding scheme was modified [11]. An advanced demand-side management (DSM) and control strategy were introduced for an efficient energy management system (EMS) in smart microgrid (SMG) [12]. An optimal cost-effective EMS operation was firstly proposed based on a two-level genetic algorithm (GA) optimization problem and augmented with the time-of-use pricing (ToU) principle. Secondly, the SMG voltage and frequency were optimally regulated using an improved proportional integral derivative (PID)-based mixed sensitivity H-infinity (PID-MSH\(\infty\)) control scheme while operating in islanded mode. The proposed DSM and control strategy harness the immense internet of things (IoT)titudes to ensure an economic and secure operation of the SMG. Depending on the MG operation modes, disturbances, and time frame, MG stability was classified in [13]. Additionally, a comprehensive review presented and addressed the challenges and effects of the instability MG problems. Load perturbations, changing operating conditions, and interactions between the load dynamics and generation dynamics significantly disturbed the MG stability [14]. Intensely, the MG stability depends on several parameters such as controller parameters, load dynamics, LC filters, and controller dynamics [3]. It was reported that the low-frequency modes are dominantly affected with both load demand and outer controller parameters. Meanwhile, the medium and high-frequency damped modes are mainly influenced with the load dynamics, filter components, and inner controller parameters [14]. Electrical loads are classified as passive and active loads. Resistive space heaters and incandescent lighting are common passive load examples. They are usually modeled as a resistor or an inductor-resistor combination. Meanwhile, electronics loads such as switching power supplies, motor drive systems, and electrical vehicles are considered as active loads. Recently, power electronics applications have been utilized in different applications such as RESs, electrical vehicles, MGs, and smart grids. Nevertheless, such active loads tend to behave like constant power loads (CPLs) [15]. CPLs have been tremendously used in distributed power systems. They are extensively involved in MGs with a main concern in stability studies [14; 15; 16; 17; 18; 19; 20]. It is worth mentioned that CPLs significantly reduce the MG damping [14]. A comprehensive review on CPLs compensation techniques in the DC microgrid (DCMG) and AC microgrid (ACMG) was presented and classified in [16]. The CPLs stability problem in MG was defined and analyzed [17].