Figure 1. Microgrid- A Schematic Diagram
The increasing electrification of daily life and the growing number of sensitive or critical loads have led to a rising demand for high-quality electricity and overall energy consumption. Customer demands for increased generating capacity and efficient energy production, distribution, and utilization are driven by the global increase in energy consumption and the depletion of fossil resources. The concept of the microgrid holds promise for addressing significant issues arising from the widespread use of distributed generation in distribution networks. To ensure successful microgrid operation, an appropriate control strategy is essential. MATLAB and other software can be used for simulating and evaluating various load models. This article provides an overview of the previous research on microgrids.
The term "Microgrid" (MG) refers to a system that is on a smaller size and is situated closer to the customer. The phrase "microgrid" refers to the coupling of low-voltage distribution networks with smaller power production facilities. Both a link to the primary power network and independence from that network are viable options for operating microgrids. The various energy resources in MG for electrification of rural areas, where there is no possible access to grid electricity due to poor access of remote areas to technical skills include small capacity hydroelectric units, ocean energy and biogas plants, wind, diesel-generation, Photovoltaics (PV), and energy storage, amongst other options. The microgrid should be designed in a way that simplifies the installation, commissioning, operation, and maintenance processes. This design is required before the microgrid can be implemented. The microgrid contributes to a reduction in expenditures by easing network congestion, cutting down on line losses and expenses, and ultimately leading to greater energy efficiency (Lee et al., 2008; Panigrahi et al., 2006; Yuan & Zhang, 2006).
The primary obstacle facing society today is the incorporation of renewable energy sources into the existing electricity grids. MG is able to function in both the grid-connected mode of operation as well as the islanded mode of operation, and its components may either be physically close to one other or scattered geographically (Nagliero et al., 2010; Syed et al., 2013). This provides it with greater flexibility and dependability compared to other systems.
New methods of power generation, such as renewable energy, clean and efficient fossil fuels, and distributed generation, have been developed in order to meet the ever-increasing demand for electricity, as well as to improve the efficiency of energy utilization and the reliability of its use (Qiang et al., 2012). These methods include the notion of a microgrid is predicated on the premise that a large number of small generators are connected to a network in order to reduce the requirement for a high-voltage transmission and distribution infrastructure (Mashhour & Moghaddas- Tafreshi, 2009). Yet, the microgrid has the potential to be integrated with the distribution system; however, this integration carries with it the risk of jeopardizing the secure and dependable functioning of the grid as a result of a net loss in line flow, voltage, and power quality (Qiang et al., 2012; Wang et al., 2012). This research discusses the regulation of voltage and power as well as the management of energy in microgrids. The simulation efforts that were done for the various load models of microgrids and its findings are discussed in detail.
The operation and control system in a microgrid involves the management of various components and processes to ensure the reliable and efficient operation of the microgrid. There is now an alternative to the conventional method of energy generation and delivery, and it is known as the microgrid. In addition, integrated control of decentralized power generation is possible with the use of technologies that are associated with smart grids. Figure 1 shows an MG operating properly and linked to the grid through the substation transformer and the Point of Common Connection (PCC). The PCC is the location in an electrical circuit at which a microgrid connects to a main grid.
Figure 1. Microgrid- A Schematic Diagram
The converters play an essential part in the process by initially connecting Distributed Generation (DG) systems in parallel with the grid or other sources, and then continuing to work in stand-alone mode in the event that critical loads are not supplied by any other sources (Venkateswarlu & Kishore, 2012). The connection to the utility can be severed by the system in the event of faults and voltage collapses, as well as when the power quality coming from the grid falls below certain thresholds. Within the microgrid, a centralized model controller has been installed to optimize the control logic of the main power supply for both unexpected and scheduled mode conversions. The control of the microgrid is a "master and slavery" control because when the microgrid is operating in the grid-connected mode, the main power is operating in the PQ mode, and when the microgrid is operating in the islanding mode, the main power is operating in the V-F mode.
Information about the microgrid, like as its current and voltage levels, may be used to determine the work mode of the microgrid (Zhang et al., 2012). The ability of the consumer to make their own selection is the primary driver of an emerging market for Distributed Generation (DG). It is up to them to decide whether they will meet their power requirements by using DG sources or through the purchase of electricity from the current utilities in their area. If all clients can come together, there is a possibility of developing a new model for power generation and distribution. Among different operational modes, the nonautonomous microgrid, also known as the paralleled microgrid, offers the greatest number of benefits to both the utility and the consumer (Smallwood, 2002). A system that utilizes variable speeds has been presented in order to ensure that a collection of small water turbines that are incorporated into an AC grid of medium voltage operate as efficiently as possible. The operation at variable speed is designed to allow connection to the 50 Hz power grid through an AC/DC and DC/AC interface because the efficiency of hydro machines increase as there is a large variation in the amount of water flow. The utilization of a power electronic-based interface accomplishes the goals of reactive power and harmonic voltage adjustment, as well as the transmission of energy from generator to grid (Magureanu et al., 2008).
As a result of deregulation and the restructuring of the traditional centralized power system, competition among the various utility service providers has begun in various sectors of the electric power system, such as Generation, Transmission, and Distribution. It is from this that the concept of Multi Generation (MG) originates. Some advantages of using a microgrid are transmission line congestion, simplified installation and control of small distributed energy resources, the operation of combined heat and power generators, and a decrease in emissions of nitrous oxide and sulphur dioxide. The MG has been employed in the capacity of slack bus, which has been investigated using the Fast Decoupled Load Flow (FDLF) mechanism in Compaq Visual Fortran (Basu et al., 2008).
If the Microgrid with Multi-Energy Generators (MGMEG's) power electronics are properly integrated and intelligently controlled by power electronic Voltage Source Inverter (VSI) for its operation with high power quality, the MGMEG will be able to detach and isolate itself from the utility system so that the utility grid becomes unstable. A Multi agent approach and power vs. frequency droop characteristic control strategy of VSIs have been developed as a means of facilitating the efficient installation of distributed energy resource units and loads in a variety of MGMEGs depicted in Figure 2 (Meiqin et al., 2008).
Figure 2. Power vs. Frequency Droop Control Strategy
Inverters serve as a universal interface that may inject the electricity that is generated by distributed power generation into stand-alone loads, microgrids, or the primary electrical grid.
In order to regulate the active and reactive power flows in the event of grid-connection as well as islanding operating mode, the droop control and inverse droop control have been proposed (Nagliero et al., 2010). In order to keep the output of a single microgrid stable, a variety of control techniques are utilized. These strategies include PQ control when the microgrid is linked to the grid, droop control in conjunction with Voltage/Frequency (V/F) control when the microgrid is isolated, and so on. It is possible to achieve steady functioning of the microgrid in either mode by combining a number of different control schemes and seamlessly switching between the two modes (Xue-song et al., 2011).
Monitoring and management of the microgrid system are essential for reducing the impact of power quality issues during steady state, islanding operation, and reconnection with conventional power systems. In order to do this, a V/I measuring equipment of MG system that was equipped with a real-time measurement function and the ability to communicate with a PC through a USB connection was employed. Additionally, this system is utilized for a variety of functions, including the examination of transitory states, the monitoring of realtime operations, and the evaluation of the quality of the power system (Lee et al., 2008).
The capacity of Photovoltaic (PV) inverters to be scaled and their modular design are the primary factors driving down costs. In order to make the electrical grid more durable, it is necessary to optimize the efficiency of the system as a whole, including the efficiency of the inverter, in addition to tracking the maximum power that can be produced by PV modules (Yuan & Zhang, 2006).
The microsource of three phase output voltage asymmetry caused by a micro-source three-phase load imbalance has the potential to result in functioning problems and potentially damage electronic devices.
For the purpose of trading electrical energy or providing system support services, a Virtual Power Plant (VPP) is used to aggregate a number of Distributed Energy Resources (DER) of various technologies with various operating patterns and availability that are connected to various points in distribution network. This is done in order to facilitate the trading of electrical energy. Distributed Energy Resources (DER), often known as DGs, have the potential to be incorporated into microgrids and virtual power plants (Mashhour & Moghaddas-Tafreshi, 2009), together with controlled loads and energy storages.
An approach to control known as plug-and-play has been presented. This approach can be implemented in electronic power processors that interface distributed energy resources with residential microgrids, which are environments in which the number of active energy sources and the amount of power generated vary throughout the day. The goal of this approach is to maximize the use of available energy sources while simultaneously minimizing distribution losses. Therefore, home microgrids may automatically switch from gridconnected to islanded operation in response to fluctuations in supply and demand (Tenti et al., 2010). This allows more efficient operation of the supply and load.
For the purpose of energy and comfort management in integrated smart building and microgrid systems, a multiagent based control framework using Particle Swarm Optimization (PSO) has been presented (Wang et al., 2011). This framework consists of a central coordinator agent and many local controller-agents.
Distinctions have been demonstrated between the conventional power grid and the smart grid in terms of risk assessment. The current self-healing idea in smart grid, which is of utmost significance, was utilized in order to have a detailed information about the smart grid risk assessment system as well as risk control measurement (Hou et al., 2011). A unique Electric Information Transmission Algorithm (EITA), based on distributed agent technologies and traffic engineering, has been presented with the intention of forming an effective communication network among equipment, distribution centers, generating units, and dispatching centers (Yang et al., 2011).
Meters that are either pre-paid or smart can be used to monitor an individual's power use in order to keep an eye on their utility and electricity bills. Pricing, renewable energy output, load demand, storage, and forecasting decisions are made and communicated by a central intelligent unit, which also provides a supporting power supply in the event of power cuts, blackouts, grid failure, and peak demand, as well as results in minimum purchase from the utility, which in turn results in low electricity bill for the user, and ensures continuity of power (Rathore, 2012).
As a result of the fact that the synchronization of microgrids that run with multiple DGs and loads cannot be controlled by a conventional synchronizer, an active synchronizing control scheme has been proposed. This scheme takes advantage of network-based coordinated control of multiple DGs in order to provide a reliable connection to the grid (Cho et al., 2011).
The Object Linking and Embedding for Process Control (OPC) protocol was developed as a supervisory control system for a controllable Distributed Energy Resource (DER) that is fueled by producer gas and shares a common load with a non-controllable DER. There has been the development of a user interface for the same, which allows for the current automation gear in a plant to be used for the purpose of operating DERs (Philip et al., 2011).
The primary purpose of the overall architecture as well as primary technologies included in the MG platform, such as the power technology, the plug and play technology, and the optimization technology, have been investigated (Feng et al., 2011).
Integration of renewable energy supplies, real-time demand response, and management of intermittent energy resources are some of the primary issues that must be overcome before a smart grid can be successfully implemented. It has been hypothesized that the recent developments in Information and Communication Technologies (ICTs) could make the efficient development of a future microgrid system more likely by enhancing the system performance, modelling, monitoring, and controlling the microgrids (Shamshiri et al., 2012). This hypothesis has been supported by a number of studies and reports.
A control method has been developed in order to facilitate an improvement in the parallel operation of two Micro Hydro Power Plants (MHPPs) on an islanded microgrid (MG). Both the MHPPs have fixed-speed turbines that are connected to Induction Generators (IG) for power generation.
The suggested control system is depicted in Figure 3 as a combination of stepped capacitors, a Voltage Source Inverter (VSI), and a Dump Load (DL) connected to the DC side of the VSI. The VSI is responsible for stabilizing the MG frequency due to its consistence operation at a specific frequency (Ion & Marinescu, 2012).
Figure 3. Voltage Source Inverter (VSI), and a Dump Load (DL) Control Strategy
The coordinated control of micro-power and energy storage devices can maintain the isolated network operation of MG (Gu et al., 2012), which is necessary for ensuring system security, reliability, and economical running under a variety of control strategies for distributed power. This is necessary in order to ensure that the system is operating economically. The performance profiles of various microgrid topologies have been demonstrated to change depending on the operational environment. Distributed Energy Resources (DER) have the ability to send any excess electricity to the utility grid while simultaneously providing reliable and efficient power delivery to the local community at the installation site (Mohanty et al., 2012). The nature of the power generated from renewable power sources is such that it is prone to unpredictability and fluctuation. As a result, the optimal operation planning method should take into consideration the uncertainties of renewable power generation and load demand (Sobu & Wu, 2012). This method has been proposed and is currently under research.
A vector control algorithm-based strategy was developed for a two-level IGBT full power converter to efficiently operate wind generation in a hybrid DC-AC link topology. This strategy is allowed for operation in both Maximum Power Point Tracking (MPPT) mode and non- MPPT mode with enhanced tracking performance. Additionally, the dynamic features of micro sources and the microgrid were analyzed under normal and fault conditions. The control strategy was designed based on microgrid energy balance and frequency stability to ensure effective control and dynamic analysis of the microgrid (Qiang et al., 2012). HOMER® and EUROSTAG® software programs were employed to analyze the electrical sources and evaluate the dynamic operation capacity of a microgrid. A sensitivity analysis was conducted, exploring various combinations of hybrid renewable energy and renewable energy sources to determine the optimal configuration. The EUROSTAG® software was used to analyze the performance of the newly implemented microgrid architecture (Kreckelbergh & Vechiu, 2012).
The term "Nearly Zero-Energy Buildings" (NZEB) refers to a type of structure that is characterized by excellent energy performance and a significantly low energy demand. Furthermore, a case study of a microgrid established for a mixed-use commercial and residential complex, along with a load management technique, has been published (Martirano et al., 2013). Stability analysis and the stabilization of MV droop-controlled microgrids with IM loads are presented in reference (Kahrobaeian & Yasser, 2013). If all clients can come together, there is a possibility of developing a new model for power generation and distribution. Among different operational modes, the nonautonomous microgrid, also known as the paralleled microgrid, offers the greatest number of benefits to both the utility and the consumer (Divshali et al., 2012). This renders the standard load frequency control techniques useless.
It is possible to make advantage of the waste heat produced by MG by positioning the sources in close proximity to the heat load. It is possible to separate the generating and the loads that correspond to it from the distribution system without compromising the integrity of the transmission grid (Lasseter & Paigi, 2004). This will allow the load on the microgrid to be shielded from the disruption. The active power of the PV inverter is a function of the system frequency, and it is managed as a current source so that it can follow a reference active and reactive power. By utilizing frequency as the control signal, wireless communication among different renewable energy sources was achieved, enabling continuous monitoring. A sinusoidal Pulse Width Modulation (PWM) controller with variable frequency and variable amplitude was employed for the battery converter (Bakirtzis & Demoulias, 2012).
An energy management programme for grid-connected microgrids with renewable energy generation and electric vehicles has been proposed. The program's objective is to minimize energy costs based on forecasting of loads, prices, and renewable energy generation. It was solved with genetic algorithm and pattern search methods. The Monte Carlo approaches were successful in finding solutions to the problems involving uncertainty (Liu et al., 2012).
An efficient method for regaining control of Flywheel Energy Storage System (FESS) in Distribution Power Automation Environment has been proposed (Xuemei, 2011). This system includes the distributed control mechanism design for the physical components of FESS, as well as intelligent decision and planning strategies for the FESS charging and discharging procedure.
Difficulties that have been identified in microgrid development include the costs associated with purchasing electricity from the main grid, operating Distributed Generators (DGs), starting up and shutting down operations, and dealing with disruptions to loads. To address these challenges, component models of microgrids, including wind turbines, micro turbines, photovoltaic arrays, and fuel cells, were analyzed using real data. The objective was to minimize the overall cost of the microgrid (Nasrolahpour et al., 2012). Through this analysis, optimal generation strategies for each DG and the management of controllable loads throughout the day were determined.
A microgrid powered by Photovoltaic (PV) cells and has integrated energy storage through batteries and super capacitors with high energy and power density has been suggested shown in Figure 4, and its control method has been tested under various environmental and load conditions.
Figure 4. PV Based Microgrid with Battery and Super Capacitor Combined Storage
Molitor et al. (2012) proposed a concept, that can be developed to construct accurate load models of individual dwellings at a high resolution.
A unique method to double-layer coordinated control, consisting two levels-the schedule layer and the dispatch layer-has been proposed for microgrid energy management. This technique is comprised of both layers. The schedule layer is responsible for obtaining an economic operating scheme based on forecasting data, while the dispatch layer determines the power output of controllable units using real-time data. Through coordination control applied to both levels, errors between real-time and forecasting data have been mitigated (Jiang et al., 2013). An optimized scheduling of a microgrid battery storage system has been introduced. This optimized scheduling takes into account the next-day forecasted load and generation profiles as well as spot electricity prices. The goal of this optimal scheduling is to reduce operating costs by optimally scheduling the generation and/or storage systems (Mahat et al., 2013).
Figure 5 illustrates the utilization of Distribution Static Compensators (D-STATCOM) in smart microgrids (MG).
Figure 5. D-STATCOM with Battery Storage
An overview of D-STATCOMs has been provided, outlining their configuration, system components, and various functions, with or without an energy storage system. The issue of management of these devices for application in smart MG has finally been addressed, with the primary attention being placed on the selection of the communication technologies that will be used for data interchange with an Energy Management System (EMS) (Falvo et al., 2013).
In the Republic of Maldives, on three outlying islands, a cutting-edge wind/PV/diesel hybrid system, coupled with cutting - edge power electronics and control technologies, has been installed. The design approach and first results of this system have been published (Tang & Suponthana, 2008).
To address the expensive nature of constructing ultra-high voltage (UHV) and extra-high voltage (EHV) transmission lines, it is essential to develop a comprehensive plan for Distributed Generation (DG) that considers the potential integration of small, medium-sized, and large regional projects in the future. Following an analysis of the concept of autonomous or non-autonomous modified microgrids, a bottom-up approach has been proposed (Blyden & Lee, 2006). This approach enables the provision of electricity to local residents while simultaneously establishing the foundational elements for future system expansion.
The Nepal Electricity Authority (NEA) and the Alternative Energy Promotion Centre (AEPC) are two key institutions responsible for implementing various on-grid and off-grid rural electrification policies in Nepal. Recently, these policies have been subject to review. Additionally, there have been discussions and concerns regarding the connection of micro hydropower systems and the development of small grids in the context of rural electrification (Baral et al., 2012).
Earlier protection systems linked with medium and low voltage networks were established on the basis of unidirectional power flows. For protection against network failures, time-coordinated over current relays were utilized. The fact is that, many of these sources can be connected to form independent microgrids, in addition to the changes that these systems have undergone over the past few decades, have posed a challenge to this protection perspective (Buigues et al., 2013). Distributed generation refers to the process in which power is generated by multiple generators located in separate locations. It has been said that a successful approach of the protection of microgrid may be achieved via the implementation of an adaptive protection system that makes use of digital relaying and enhanced communication (Kumar et al., 2013).
A protection strategy for a DC microgrid is one of the ideas that has been proposed. A 400-volt Direct Current (DC) microgrid takes into consideration about the abnormal operating conditions brought on by a variety of faults (Lee & Kang, 2011). The microgrid consists of a wind power system with a Permanent Magnet Synchronous Generator (PMSG), a photovoltaic system, a fuel cell system, and energy storage components. Various technological issues related to microgrids have been discussed and examined (Sailalitha & Kiranbabu, 2013). These challenges include voltage and frequency management, islanding, and protection of microgrids. In order to ensure that one can have faith in the protection system, a fault mitigation strategy and an operational safety design concept have been proposed. The multifunctional intelligent digital relay has been utilized for the microgrid protection and safety concept with the central control and monitoring unit for the adaptive relay settings approach for the microgrid protection (Islam & Gabbar, 2012).
The implementation of a controller based on state space design for a Shunt Active Filter with Energy Storage (SAFES) within a local power supply network has been reported, aiming to ensure voltage regulation and harmonic cancellation (Carastro et al., 2006). This controller was designed to manage the load site in the presence of scattered generation. Generators can produce active and reactive power in a coordinated manner to effectively meet the load demand while maintaining voltage and frequency stability. This coordination is achieved by adjusting the voltage amplitude and phase of a PWM converter. PWM converters have the capability to bring the power factor of the generators to unity and reduce harmonic distortion, resulting in improved power quality (Wei et al., 2008).
An accurate reactive power sharing method that acts by calculating the impedance voltage drops has been presented as a means of enhancing the precision of reactive power regulation and sharing. This will allow for improved performance in both areas. A power control strategy that takes into consideration both the effect of impedance voltage drops and the effect of DG local load has been proposed (Li & Kao, 2009). This power control strategy includes a virtual inductor at the output of the interfacing inverter as well as an accurate power control and sharing algorithm.
The ability of the microgrid system to ride at low voltage has been made possible because of a multiple converter scheme that has been suggested. This makes the system more dependable and stable. There has been discussion over the control strategy for an auxiliary power converter that is linked in parallel with the primary converter in order to support additional reactive power to endure the extreme voltage dip (Ambia et al., 2012).
The utilization of a Static Synchronous Compensator (STATCOM) and a Battery Energy Storage System (BESS) has been investigated for the purpose of stabilizing the voltage of the microgrid during short circuit faults in islanded mode of operation in order to continue power supply to the customers and, as a result, increasing the reliability of the power system (Ardeshna & Chowdhury, 2008).
Static Var Compensators (SVC), combining Thyristor Switched Capacitors (TSC) and Thyristor Controlled Reactors (TCR), or SVC paired with Active Power Filters (APF), have been proposed as solutions to address power quality issues (Bogonez-Franco et al., 2011). Additionally, a management model for optimal consumption reduction has been developed (Aghaebrahimi et al., 2011) to minimize losses, generation costs, and transmission line overloads during peak periods.
It has been suggested that the microgrid uses a brandnew power line conditioner known as the Universal Power Line Manager (UPLM) in order to resolve a variety of power quality concerns, including voltage sag, voltage swell, power frequency fluctuation, and harmonics. The UPQC, UPFC, and frequency changer (matrix converter) are the three components that come together to form the UPLM (Paul et al., 2011).
Considering the power sharing stability of a gridconnected Micro grid (MG) system with three Distributed Generation (DG) units, a PSO-based Power System Stabilizer (PSS) has been built for low and medium of the MG. This was done in order to implement a Power System Stabilizer (PSS). PSO has been used in order to optimize the controller settings, and in order to produce the best transient response possible under a variety of DG penetration levels, a number of alternative PSS structures have been utilized and compared.
The idea of Power Electric Building Block (PEBB) has been incorporated into the microgrid in order to accomplish plug- and play and to allow flexible application of DFACTS to the microgrid. The primary roles that a selection of representative DFACTS play in the microgrid have been analysed in Wang et al. (2012). The technique is used to minimise the disturbance caused by various loads, one of which was built on a two-level voltage structure while the other was developed on a three-level voltage NPC structure (Neutral Point Clamped) (Wasynczuk et al., 2012).
Two power conditioners were connected to separate four-wire hydro-generators. It is crucial to regulate the voltage amplitude and frequency across the microgrid (MG) system (Wasynczuk et al., 2012). The presence of harmonic currents from power electronic devices and loads with high reactive power demands is a significant factor affecting the power quality of the microgrid. Figure 6 depicts a combined system consisting of an Active Power Filter (APF) and a Static Var Compensator (SVC), both of which have been implemented to enhance the power quality of a microgrid. In order to reduce the amount of harmonic current, an APF has been put at the outlet of the micro source inverter (Dong et al., 2012).
Figure 6. General Structure of SVC
For the purpose of making a microgrid's dynamic voltage stability more consistent, a controller that makes use of a Microgrid Voltage Stabilizer (MGVS) has been suggested as a potential solution. This control signal is then further divided among the reactive power sources in the microgrid in proportion to their available capacities; as a result, each source will be required to generate a certain amount of reactive power. The MGVS is a secondary level voltage controller that generates the control signal. To enhance the power quality of microgrids that are powered by renewable energy sources, an Active Power Conditioner (APC) that operates in three phases has been developed. APC serves as an interface between renewable energy sources and the AC bus of a microgrid. It employs an enhanced control technique, which enables it to inject energy into the microgrid, compensate the current harmonics, and correct the power factor (Naresh et al., 2013). APC also works to correct the power factor.
A new application of the Unified Power Flow Controller (UPFC) has been developed to address voltage stability issues in low and medium voltage microgrid systems. This modified UPFC can enhance the voltage profile of the system, regardless of whether the microgrid is connected to the grid or not (Joglekar & Nerkar, 2010).
To improve the power supply quality in an autonomous microgrid, an optimal power control strategy has been proposed. This strategy utilizes a real-time self-tuning method and requires the presence of Distributed Generation (DG) units. The Particle Swarm Optimization (PSO) algorithm, in conjunction with the PI regulator, is suggested for achieving real-time system self-tuning (Al- Saedi et al., 2011).
Based on the provided review, it can be concluded that the increasing focus on renewable energy, the need for reliable power quality, rural electrification, and improved efficiency have led to the growing importance of microgrid infrastructure. Microgrids offer the advantage of local dependability and the ability to integrate generation and loads. However, the evolving nature of distributed generation and the integration of independent microgrids pose challenges to traditional protection approaches. The implementation of Flexible AC Transmission System (FACTS) devices in microgrids can enhance power quality and improve power flow. MATLAB is used to analyze and study these factors. The future research should involve more case studies of actual microgrid sites and emphasize issues such as protection, power system stability, and the implementation of FACTS devices.