# State-of-the-art of hierarchical microgrid technological framework: operational strategies with manifold barriers and future trajectories

Abdul Latif, Abdelhakim Saim, Azeddine Houari, Ali Djerioui

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Abdul Latif, Abdelhakim Saim, Azeddine Houari, Ali Djerioui. State-of-the-art of hierarchical mi- crogrid technological framework: operational strategies with manifold barriers and future trajectories. Renewable Energy Focus, 2025, 55, pp.100743. 10.1016/j.ref.2025.100743. hal-05502721

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Research Review

# State-of-the-art of hierarchical microgrid technological framework: operational strategies with manifold barriers and future trajectories

Abdul Latif<sup>a,*</sup>, Abdelhakim Saim<sup>a</sup>, Azeddine Houari<sup>a</sup>, Ali Djerioui<sup>b</sup>

ARTICLE INFO

Keywords:

Microgrid

Technological framework

Operational management

Stability

Barriers

ABSTRACT

Microgrids represent a critical and integral element in the advancement of smart grid technologies. These are diminutive-scale power systems, encompassing distributed energy resources. For the realization of the potential inherent in distributed generation, it is imperative to adopt a framework wherein the corresponding loads and generation are conceptualized as a sub-system, or more precisely, a microgrid. This article presents a comprehensive review of the scholarly literature pertaining to microgrid concept, technological applications. Research in this field is bifurcated into three primary domains: feasibility, control with management and stability strategies. Initially, the article delineates the various applications and categorizations of microgrids. Subsequently, it elucidates the objectives underlying microgrid control. Additionally, the article delves into the issue of small signal stability and hierarchal stability framework and clustering within microgrids, exploring various methodologies to enhance this aspect. Later, the paper scrutinizes the aspect of load frequency control within the microgrid paradigm. Additionally, numerous potential issues and barriers associated with microgrid implementation are identified and discussed. The paper concludes by delineating key areas for future microgrid research. This work aims to provide scientists, academician, and policymakers with comprehensive and structured knowledge about microgrids.

Introduction

The modern electrical system, an extensive and intricate network, is governed by the integrated power networks community [1,2]. This network is distinguished by the shared utilization of diverse renewable energy sources [3]. The global trend in electricity generation is moving towards an increased reliance on renewable sources, driven by industrial advancements and environmental considerations [4]. This shift is leading to a greater integration of sustainable renewable resources into the distribution frame. Microgrids, which are localized power networks of various sizes embedded within distribution systems, are gaining popularity [5,6]. Their rise can be attributed to several factors: (a) their potential to lessen environmental impacts and reduce the need for extensive allocation in power plant infrastructure and costs, (b) their contribution to enhanced and stable energy efficacy, (c) the ability of energy storage units to maintain operation during disruptions, and (d) their ability to mitigate the effects of sudden grid outages [7,8].

Renewable resources such as wind [9,10] solar, and hydroelectric power [10,11] are increasingly recognized as cost-effective means to

fulfill a significant portion of energy requirements. Regarding power provision, microgrid technology offers significant advantages, especially for remote communities, by improving local energy security [12]. This technology significantly contributes to energy security by decreasing reliance on imported energy [13]. When a renewable resources-powered microgrid is connected to the utility grid, it obviates the need for additional frequency regulation efforts [14]. However, the integration of microgrids presents several challenges, including maintaining stability [15,16] managing bidirectional power flows [17,18], developing accurate modeling and economic, market, regulatory aspects with other operation issues. Additional concerns include low system inertia [19,20] the impact of load perturbations, and inherent uncertainties [21]. The deployment of distributed generators (DGs) within microgrids can sometimes introduce more challenges than solutions [22]. Microgrids represent small-scale energy networks where the integration of sustainable power generation as well as storage technologies is critical to meet regional energy demands effectively [23]. Microgrids can be configured using either direct current (dc) or alternating current (ac) [24] systems. These configurations, particularly when combined with multi-converter devices, demonstrate significant potential for future

<footnote><sup>a</sup> Nantes Université, Institut de Recherche en Énergie Electrique de Nantes Atlantique, IREENA, 44600 Saint-Nazaire, France</footnote>

<footnote><sup>b</sup> LGE, Laboratoire de Génie Electrique, Department of Electrical Engineering, Faculty of Technology, University of M'sila, BP 166 Ichbilia, Msila, Algeria</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: abdul.latif@univ-nantes.fr (A. Latif).</footnote>
Nomenclature

<table><tr><td>MG</td><td>Microgrid</td></tr><tr><td>DGs</td><td>Distributed generators</td></tr><tr><td>ESU</td><td>Energy storage units</td></tr><tr><td>FACTS</td><td>Flexible AC Transmission System</td></tr><tr><td>MPC</td><td>Model Predictive Control</td></tr><tr><td>PCC</td><td>Point of common connection</td></tr><tr><td>MGCC</td><td>Microgrid Central Controller</td></tr><tr><td>DRM</td><td>Demand response management</td></tr><tr><td>VSC</td><td>Voltage source converter</td></tr><tr><td>MC</td><td>Micro controller</td></tr><tr><td>DDGs</td><td>Diesel driven generators</td></tr><tr><td>RRs</td><td>Renewable resources</td></tr><tr><td>AC</td><td>Alternating current</td></tr><tr><td>PMMS</td><td>Power management microgrid system</td></tr><tr><td>CC</td><td>Central controller</td></tr><tr><td>LC</td><td>Local controller</td></tr><tr><td>DERs</td><td>Distributed energy resources</td></tr><tr><td>f, v</td><td>Frequency, voltage</td></tr><tr><td>PLL</td><td>Phase lock loop</td></tr><tr><td>VSG</td><td>Virtual synchronous generator</td></tr></table>

energy systems by enhancing reliability, efficiency, and the quality of power supply [25]. There is a considerable body of research focused on various aspects of microgrid technology. These include classification systems [26], control strategies [27], protection devices [28], optimization methods [27,29], combustion control [30], stability [31], power sharing [32], and techniques for reactive power compensation. A comprehensive summary of existing review studies on microgrids is presented in Table 1 where a statistical survey presented in Fig. 1 indicates that microgrids (MGs) are expected to experience substantial growth over this decade. Projections suggest that both the annual capacity installations and associated expenditures will increase by five times from 2018 to 2027.

This paper conducts a comprehensive review of the operation, application, and control systems of microgrids. To summarize, the significance and novelty of this study are outlined as follows:

* The in-depth exploration of conceptualization of MGs and their applications is delved (Section 2).

* An overview of the different classifications of MGs' technological framework is presented (Section 3).

* The MG's control architecture, operational management with hierarchical stability analysis are depicted in (Section 4). The analysis of small signal stability is covered (Section 4).

* Improvements in microgrid stability are detailed (Section 4). The cluster of MGs with adaptive load frequency stabilization is the subject of Section 4.

* The manifold barriers associated with the integration of microgrids are discussed (Section 5).

* Some future research direction with potential opportunities are also delineated (Section 6).

Methodological review approach and analysis

This review article endeavors to offer an exhaustive summary of Microgrids (MGs), focusing particularly on unresolved challenges and prospective trajectories. To achieve this objective, a methodical examination of academic papers and reports was undertaken. Fig. 2 illustrates the sequential progression of the review process. This approach facilitated the identification and scrutiny of pivotal discoveries, as outlined in

<table><caption>**Table 1**
An analysis covering various dimensions of microgrids</caption><thead><tr><th>Reference</th><th>Focus area</th><th>Methodology and contributions</th></tr></thead><tbody><tr><td>Carpintero-Rentería et al., [33]</td><td>Layered Structure</td><td>Conducted an analytical review of both academic and industrial documents, applying a layered approach integrated with environmental considerations to assess their impact on microgrid functional architecture.</td></tr><tr><td>A.Latif et al. [27]</td><td>Frequency Regulation and control strategies</td><td>Categorized various frequency control methods and strategies within microgrids, underscoring the diversity of approaches for maintaining frequency stability.</td></tr><tr><td>Bouzid et al., [34]</td><td>Distributed Generation</td><td>Focused on integrating renewable energy resources within distribution networks as microgrids, emphasizing a hierarchical control structure and strategies for managing power generation and distribution system units.</td></tr><tr><td>Abdellatif et al., [35]</td><td>Distributed Generation</td><td>Examined contemporary local power distribution systems, emphasizing the integration of renewable energy resources and various energy storage techniques. It also explored configurations of microgrids, addressing their operation in both islanded and grid-connected modes through the application of diverse controllers and algorithms.</td></tr><tr><td>Gayatri et al., [36]</td><td>Reactive Power Compensation</td><td>Modeled microgrids using real environmental data to identify challenges and power quality issues, proposing compensation methods via diverse control techniques, algorithms, and devices.</td></tr><tr><td>Hajiaghasi et al., [37]</td><td>Hybrid Energy Storage Unit (ESU)</td><td>Proposed innovative hybrid energy storage units (ESU) for MG applications, including an economic assessment and design procedure from the perspective of investors and system engineers.</td></tr><tr><td>Arfeen et al., [38]</td><td>Hybrid ESU</td><td>Explored current local power distribution networks, with a specific focus on sustainable resources and ESU methods. It also assessed the advantages and drawbacks of prevailing controllers used within these systems.</td></tr><tr><td>Jing et al., [39]</td><td>Hybrid ESU</td><td>Investigated advancements in battery ESU and supercapacitor ESU based hybrid energy storage units (HESU) for isolated microgrids, comparing their topology, energy management, and control strategies.</td></tr><tr><td>Urquiza et al., [40]</td><td>Power Quality Improvement</td><td>Proposed techniques for enhancing power quality in microgrids, emphasizing the role of distribution Flexible AC Transmission System (FACTS) devices in augmenting the stability and control of AC transmission networks.</td></tr><tr><td>Llaria et al., [41]</td><td>Inverter Control</td><td>Surveyed microgrid configurations, particularly focusing on unplanned islanding scenarios and inverter control strategies therein.</td></tr></tbody></table>

(continued on next page)
<table><caption>**Table 1 (continued)**</caption><thead><tr><td>Reference</td><td>Focus area</td><td>Methodology and contributions</td></tr></thead><tbody><tr><td>Wei et al., [42]</td><td>Microgrid Technologies</td><td>Offered a comprehensive review of essential MG technologies, outlining their typical architecture, planning, design, operational control, protection technology, and considerations for power quality.</td></tr><tr><td>Gutierrez-Rojas et al., [43]</td><td>Microgrid Protection</td><td>Reviewed the vital role of communication technologies in distributed energy systems for device coordination, offering a comprehensive analysis of associated communication technologies with optimization approaches.</td></tr><tr><td>Zhang et al., [44]</td><td>Microgrid Protection</td><td>Delivered analysis, identification, and management strategies for faults within DC microgrids, including coordinated control and protection strategies.</td></tr><tr><td>Chandra et al., [45]</td><td>Microgrid Protection</td><td>Discussed how architectural changes in DC microgrids impact existing protection schemes, highlighting the challenges posed by rapid increases in fault current and reviewing protection challenges associated with DC microgrids.</td></tr><tr><td>Hu et al., [46] and A. Latif [47]</td><td>Model Predictive Control (MPC) and diverse structure of MPC</td><td>Reviewed predictive control models applicable to both single and interconnected microgrids, including surface control and converter strategies within the hierarchical control architecture. To this end, diverse structure MPC used in MGs active power management and control.</td></tr><tr><td>Yamashita et al., [48]</td><td>Building Microgrids</td><td>Examined primary control algorithms for building microgrids, detailing their strengths, weaknesses, and the roles of primary, secondary, and tertiary control levels in adapting microgrids to grid structures.</td></tr><tr><td>A. Latif et al. [49] and A. Daraz [50]</td><td>Marine Microgrids</td><td>Illustrated secondary control of marine vessel MGs considering fractional order and cascaded based approaches.</td></tr></tbody></table>

the following strategy:

a) **Goal and Extent:** The main goal of this review cycle is to assess the existing body of knowledge on Microgrids (MGs), identify the operational strategies, pinpoint unresolved matters, and explore probable future developments. This literature review encompasses a range of sources, including research papers, conference proceedings, and technical reports. The review's scope extends from the early phases of MG research to present-day advancements.

b) **Search Methodology for Literature:** An exhaustive and systematic search was executed across multiple academic databases to locate pertinent literature. These databases included Google Scholar platform, IEEE digital library, ScienceDirect, ResearchGate forum, Scopus, Web of Science (WoS), and the ACM digital platforms. Key search terms employed were 'microgrid operation', 'microgrids control', and 'nano-grid'. The scope of this search was confined to publications written in English.

c) **Criteria for Selection:** The selection of articles was guided by specific inclusion and exclusion parameters. Preliminary screening involved an assessment of article titles and abstracts to ascertain their relevance. For detailed analysis, only peer-reviewed articles, conference articles, as well as authoritative reports that specifically focused on Microgrids (MGs) and related subjects were taken into consideration.

d) **Synthesis and Analysis of Data:** Pertinent information was culled from the chosen articles, encompassing details such as the author(s), year of publication, research methodologies utilized, key findings, identified challenges, and projected future directions. This data was methodically organized to enable efficient analysis and synthesis.

**Microgrid conceptual viewpoints: Overview and Applications**

The fundamental aspects of microgrid structure include assessing the functionality of MG components, the benefits of MGs on key distribution system such as stability profiles, economic profiles, and reliability and renewable integration. This section explores the definitions and key components with application aspects related to MG structure.

**Definition and basic research**

The literature features various definitions of microgrids [52] and their functional classification systems [53]. One widely referenced definition, formulated by the Microgrid Exchange Group – an ad hoc assembly of research and deployment specialists – for the U.S.

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** The projected microgrid capacity and expenditure, under the foundational scenario, for the period spanning 2018 to 2027 [51].</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>Fig. 2. The strategic flow diagram for the review mechanism: microgrid structure viewpoints, types/groups, control, architecture and operational management of MGs.</figcaption></figure>

Department of Energy, is as follows:

"{A microgrid is defined as a collective of interconnected loads and distributed energy resources, confined within specific electrical boundaries, functioning as a unified, controllable unit in relation to the grid. It possesses the capability to connect to and disconnect from the grid, allowing it to function in either grid-connected or islanded mode [54]."

This definition encompasses three key criteria: a) the ability to delineate the segment of the distribution system that constitutes a microgrid, distinguishing it from the broader system; b) the necessity for resources linked to a microgrid to be managed in unison, as opposed to coordinating with remote resources; and c) the capability of the microgrid to operate independently, irrespective of its connection to the larger grid.

The basic research and development initiatives in the realm of microgrids began with Consortium for Electric Reliability Technology Solutions (CERTS) in the United States (US) and the MICROGRIDS project in Europe, both initiated in the late 1990s, have played pivotal roles in advancing systematic research and development in their respective regions [54,55]. Established in 1999, CERTS is acknowledged

as a trailblazer in the development of contemporary grid-connected Microgrid (MG) concepts [56]. The CERTS MG model emerged as a potential resolution to the complexities of integrating Distributed Energy Resources (DERs) into the grid [57]. Initial efforts centered around automated, seamless transitions between islanding and grid reconnection, coupled with passive control strategies [58]. This concept has since been evaluated in both experimental test beds and practical MG implementations [59]. CERTS initially focused on enhancing grid reliability through renewable sources, with less emphasis on reducing greenhouse gas emissions. Concurrently, the MICROGRIDS project of the European Union delved into similar technical challenges, like, energy regulation, safe islanding, reconnection practices, protection systems, control approaches for both islanded and grid-connected states, and communication protocols [60]. In this regards, 'Concept Grid' and 'Nice Grid' pilot MICROGRIDS projects has been developed in France with the integration of solar PV panels, Wind farms and different storages systems [61]. Following to this, in Africa there are different isolated MG projects successfully completed such as, 'Mafate Microgrid', 'Longmeadow', 'Robben Island' with the integration of solar PV, hydrogen fuel cell, diesel, and battery storages to provide local building demanded
power during uncertain weather condition [61]. Out of the 900 million individuals globally who lack access to electricity and basic clean cooking facilities, 640 million reside in Africa, resulting in an access rate of only 40 percent in Sub-Saharan Africa in the viewpoint of non-accessibility of electricity in Africa continent [62]. These foundational issues, first explored in the early phases of microgrid research, continue to garner significant interest and investigation [54].

## Fundamental microgrid elements

The architecture of a microgrid is composed of five primary elements: (a) micro sources or distributed generators, (b) adaptable loads, (c) distributed energy storage systems, (d) control strategies, and (e) components at the point of common coupling. These elements are integrated into a low-voltage distribution network and are designed to operate in a controlled and coordinated fashion, whether they are connected to the utility grid or functioning in an islanded state [63]. The constituents of the microgrid are depicted in Fig. 3.

a) *Micro-sources or distributed generators:* The generation system within a microgrid may comprise a variety of both dispatchable and non-dispatchable units. Dispatchable units include options like natural gas driven turbine generators, biogas powered generators, and combined heat and power (CHP) generation systems. Conversely, non-dispatchable units encompass sustainable energies i.e., solar PV, wind, hydro, and biofuel [3,5,64].

b) *Distributed energy storage units:* In Microgrids (MGs), the energy storage units (ESU) fulfills several roles, including maintaining power quality, facilitating peak load managing, regulating frequency, stabilizing the output from sustainable energy sources (SESs), and offering backup power support. Additionally, the ESU is pivotal in optimizing the cost-efficiency of MGs [64].

c) *Control strategies:* The control strategy is instrumental in the intelligent management of the Microgrid (MG), utilizing energy meters and communication tools for this purpose. It governs the dispatching of MG generation and load, guided by considerations of economic efficiency and reliability. Where the controller of MGs is responsible for overseeing the system's immediate operational activities [5,64].

d) *Adaptable loads:* Microgrids primarily accommodate two categories of loads: (i) vital loads, which require uninterrupted service under all circumstances, and (ii) deferrable loads, which can be modulated to facilitate load balancing within the MGs, thereby ensuring the utmost economical power generation [3,5].

e) *Components at the point of common connection:* The point of common connection (PCC) is a critical element, serving in terms of physical

juncture where the microgrid connects with the utility grid network. It acts as the interface for the exchange of electrical energy among the microgrid and the broader power system. The PCC encompasses a variety of apparatus and devices that support connection, power transfer, contain, and safety between the MG and the utility grid, including circuit breakers (CB), protective relays, and synchronization apparatus. Notably, an islanded MG operates without a PCC [5,64].

f) *Hardware elements:* In a hierarchical microgrid control system, primary, secondary, and tertiary control layers perform distinct functions supported by different hardware. Primary control focuses on real-time local regulation using fast-response devices such as inverters (with VSG technology), distributed generation units, energy storage systems, and protection equipment to maintain system stability. Secondary control coordinates multiple primary controllers to optimize resource use and power quality; centralized systems rely on a Microgrid Central Controller (MGCC), while distributed systems use local controllers, intelligent inverters, sensors, and communication modules. Tertiary control handles global optimization and long-term planning using centralized dispatch systems, SCADA for real-time monitoring, and EMS to integrate data and develop scheduling strategies based on market and forecast inputs [65].

## Advantages of microgrids implementation

a) Investing in the grid infrastructure can mitigate risk, serving as a safeguard against unforeseen and potentially high costs associated with emergency or contingency energy requirements. Additionally, it provides a buffer against the variability of electricity bills.

b) Subject to local market regulations and initiatives, MGs have the capacity to reduce peak load pricing, participate in dynamic demand response management (DRM) markets, and contribute frequency adjustment facilities to the broader grid. Moreover, they hold potential for revenue generation through the reduction of peak load costs, active engagement in DRM deregulation, and provision of frequency contain facilities to the larger grid network.

c) In several developed countries, the electrical system is generally stable, yet outages can be both expensive and hazardous. Presently, the electricity infrastructure faces escalating threats from extreme weather events, aging systems, physical assaults, and cyberattacks [66,67]. Operating in island mode, where the system isolates itself from the main grid and relies on local generation, can guarantee a consistent electricity supply.

d) Integration of RESs play a critical role in meeting global energy demands. The current worldwide energy crisis has catalyzed a

<figure><img src="image_5.png" /><figcaption>Fig. 3. Diagram illustrating a MG with diversified system components.</figcaption></figure>
significant momentum for the development of RESs. Forecasts from the International Energy Agency (IEA) suggest that the growth of sustainable energy capacity in the upcoming five years is set to exceed prior projections. Between 2022 and 2027, sustainable energy capacity is expected to increase by about 2400 GW, marking an 85% acceleration related to the observed growth in the preceding five years. This anticipated expansion is nearly 30% greater than predictions made in the previous year's technical report, representing the largest rising modification to date [68]. Consequently, MGs are gaining increased significance in harnessing the advantages of RESs.

e) The capability of MGs to operate in island mode enables them to maintain power supply to their consumers during power outages. Additionally, this islanding feature is crucial for isolating faults by segregating distribution feeds.

f) There are instances where systems require a level of electricity that surpasses the capacity of the electric grid. The adoption of a Microgrid (MG) facilitates enhanced containment over power constraints, which is vital for the operation of sensitive subsystems in sectors such as healthcare, advanced manufacturing, laboratories, and various other organizations.

g) Microgrids can be conceptualized as fundamental components in the development of smart grids. Alternatively, envisioning future utility grids as an interconnected network of MGs, these systems could effectively manage demanded energy and generation both at micro and macro stages.

h) MGs alleviate grid bottleneck and diminish high load demands. Additionally, they provide a variety of grid services, encompassing energy, level of capacity, and ancillary services.

## Key employment and advanced utilizations frameworks

Based on current experience and literature, numerous principal utilizations of microgrids have been identified.

a) **Educational location:** Microgrids in educational environments typically encompass a specific number of buildings within a confined geographical space. The requisite standards for power supply quality can vary based on the institution type [69]. For instance, government and institutes facilities often have adequate functionality with moderate reliability in power supply, whereas research institutions might require a higher quality of power. In these microgrid configurations, all buildings and stakeholders are usually part of a single organization, with centralized decision-making authority. This arrangement facilitates expedited decision-making processes, and the property owner is positioned to implement measures when clear advantages are identified [70].

b) **Commercial/industrial location:** Commercial/industrial microgrids share similarities with the previously mentioned single-owner type. However, when an microgrid is established in a commercial/industrial zone with multiple stakeholders, the situation becomes more intricate. In cases where a 'commercial-industrial park' is a new development ('greenfield project') offering both premium and standard power supply options, the developer may choose an MG configuration to accommodate the diverse needs of all clients. Facilities linked to public grids can reduce energy expenses and enhance self-reliance by diversifying their energy sources, leveraging time-of-day electricity pricing, and ensuring access to backup power as needed.

c) **Community location:** "Community" microgrids predominantly serve private end-customers in residential areas, although they occasionally cater to business and industrial clients as well. These MGs can encompass urban neighborhoods, community areas, and rural feeders. Being connected to the larger utility grid, they have the capability to supply power to both urban and rural regions. This type of MG can incorporate a diverse array of energy sources, either

renewable or fossil-fuel-based. The commercial viability of these MGs is significantly influenced by national and international standards and regulations. Decision-making processes in such MG structures tend to be more protracted due to the involvement of numerous participants.

d) **Isolated/off-grid frameworks:** Community microgrids are often quite similar to isolated MGs, with the primary difference being the usual lack of connection to the main grid network. In some instances, if the geographical distance permits, isolated MGs might have a cable connection to the utility grid on the mainland. However, decision-making processes on isolates may be expedited based on the existing power supply infrastructure. Off-grid structure MGs are particularly significant for geographically isolated communities, including those in developing countries, emphasizing distributed and diverse power sources. Many remote MGs are currently being developed with the potential to eventually integrate into larger grid systems as the electrical infrastructure in these regions advances. Alternatively, some isolated MGs are designed for self-sufficiency to ensure energy security. Additionally, hybrid microgrids [71], which integrate renewable energy sources typically as supplements to diesel generator-based systems, exhibit significant potential for diversifying generation and reducing operating costs. This is particularly relevant in island communities dependent on costly imported oil for electricity generation, and in remote areas distant from existing electricity infrastructure [72,73]. Research studies featuring isolated microgrids have highlighted examples such as Huatacondo Island in Chile [74], Xingxingxia in Xinjiang, China [75], and Lencois island in Brazil [76].

e) **Advanced utilizations frameworks:** In addition to their standard applications, microgrids can also be employed for the following purposes: (i) shipboard power systems, which are installed on ships, ferries, large vessels, and other marine equipment, typically function in an isolated mode while at sea and switch to grid-tied mode when docked at ports. Consequently, shipboard MGs represent genuine mobile microgrids with both affordability and a promising market potential. The significance of shipboard MGs is on the rise as ships increasingly adopt electrical systems [77]. (ii) The concept of aircraft MGs has become increasingly pertinent in recent times. Within the aerospace sector, there is a growing trend of replacing mechanical, hydraulic, or pneumatic power sources with electrical ones. This shift is evident in various applications, including airport microgrids and electric or more electric aircraft [78]. (iii) The dependability of the power networks components in spacecraft or satellites is vital for the successful execution of highly expensive space missions. Consequently, Space microgrids have been developed as a sustainable approach to fulfill the energy needs of space applications [79], (iv) Artificial ecosystems, functioning as life support networks (LSNs), are increasingly utilized for sustaining prolonged human space missions. In space, there are no inherent means for food production or waste disposal. Consequently, open LSNs necessitate external support for food and waste management from earth. Closed ecological networks (CENs), which do not engage in material exchange with their external environment, are essential for long-term manned space missions to reduce dependency on earth. These systems comprise multiple distinct segments that emulate the critical functions of an ecological system, operating continuously in controlled conditions [80]. On the other hand, with the escalating dependence on electricity, prolonged power outages can significantly impact communities. Such outages can disrupt water treatment facilities, leading to shortages of clean water essential for post-disaster recovery. A viable strategy to address these challenges involves temporarily reconfiguring electricity and water infrastructures into localized networks. These include electric microgrids and water microgrids, which utilize local resources to satisfy local demands, independent of the primary power grid and water networks [81].
# Addressing types/groups in microgrid technological framework

An extensive literature review was undertaken to explore the fundamental topologies and structural frameworks of contemporary microgrids. This analysis aims to assist designers in selecting intrinsically safe and resilient strategy alternatives. MGs can be classified into various clusters based on their applications, architecture, and the specific necessities of their end-users, as depicted in Fig. 4.

## Addressing size/scale based MGs

Based on their size, MGs can be segmented into three categories: small-scale, medium-scale, and large-scale MGs [63].

In the world of sustainable energy, there existed three kinds of microgrids, each unique in its capacity and utility, serving different realms of society. In the quaint villages and remote islands, the small-scale MGs reigned. These MGs were modest yet mighty in their own way, harnessing the power of renewable resources (RRs) to generate electricity. With a capacity of up to 10 MW, they often integrated diesel driven generators (DDGs) alongside or in place of RRs, lighting up residential buildings, powering small regional grids, and bringing energy to remote areas that had never known stable power [82].

Then the medium-scale MGs, the guardians of industrial zones. These MGs were more powerful, with a generation capacity ranging from just over 10 MW to 100 MW. They drew their strength from a mix of renewable resources, oil, and coal, seamlessly blending the old and new energy sources. Their energy lit up the bustling industrial zones, driving the wheels of progress and innovation [82]. Finally, the large-scale MGs towered over the industrial landscapes with their formidable presence. They were the titans of electricity generation, primarily utilizing oil and coal to produce power well over 100 MW. These MGs were the backbone of industrial site applications, supporting large factories and industrial complexes with their immense power, ensuring that the heart of industry never missed a beat [82]. Together, these three types of MGs formed an intricate tapestry of energy solutions, each serving its purpose, each essential to the grand design of a sustainable, energy-efficient world.

## Addressing distribution supply system based MGs

Regarding the nature of the power supply connection, microgrids could be segmented into three distinct types: AC MGs, DC MGs, and Hybrid MGs [83,84].

### a) MGs with AC supply:

An AC microgrid is typically characterized by an alternating current (AC) power supply, servicing loads that operate on AC power. Such MGs can function autonomously or be interconnected with the utility grid at the PCC. In these systems, an AC bus links power generation sources, ESUs, and additional apparatuses to meet AC load requirements. Integration of these MGs into existing power systems is relatively straightforward, and they do not necessitate additional control mechanisms. AC MGs can be further divided into three types: 1-phase, grounded 3-phase, and ungrounded 3-phase configurations [85]. Additionally, they can be categorized on the basis of frequency into high-frequency [86,87], low-frequency [88] and nominal-frequency AC MGs. Additionally, AC microgrid represent the predominant and most extensively applied design in practical implementations. Nevertheless, difficulties emerge in achieving synchronization with the host grid, especially in regulating voltage magnitude, phase angle, and frequency. The efficacy and reliability of AC MGs are comparatively lower, and they require complex architectural and control solutions.

### b) MGs with DC supply

DC Microgrids are designed to generate and accumulate electricity in direct current (DC) form. In these systems, both the power supply and the connected loads operate on DC power. DC MGs offer advantages over AC MGs, notably in that they do not require synchronization and typically exhibit fewer power quality issues. Furthermore, they are not burdened with power factor (pf) enhancement concerns. To integrate with current distribution systems, DC MGs employ a range of converters and power electronic apparatuses. Compared to AC MGs, they are more efficient and involve fewer conversion processes for powering DC loads. DC MGs find application in areas such as telecommunications, electric vehicles aggregators, mobile power networks, and other commercial settings. These MGs can be categorized into mono-polar, bi-polar, and homo-polar types [89,90].

A key benefit of DC MGs is their ability to directly connect DC loads to the DC bus, minimizing the need for power converters. However, DC MGs lack a identical voltage level, necessitating an extra step to produce AC voltage. Additionally, they cannot be readily reconfigured from the existing grid, and their protection mechanisms are typically complex.

### c) MGs with hybrid AC/DC supply

Hybrid AC/DC microgrids are characterized by the utilization of both AC and DC power sources to drive the connected loads. These MGs incorporate both AC and DC distribution systems, with the primary objective being to diminish the conversion phases' number and interface components, thereby reducing energy costs [91]. This approach enhances the overall system efficiency and reliability. Hybrid MGs can support a mix of AC and DC loads, offering consumers the flexibility to

<figure><img src="image_6.png" /><figcaption>Fig. 4. Categorization of MG.</figcaption></figure>
tailor their power consumption to specific requirements. Power elec-
tronic converters within these MGs segregate the AC and DC elements
[92,93]. In AC-DC hybrid MGs, distributed generation units can be
connected directly to either the DC or AC networks, eliminating the need
for synchronization [94]. However, this configuration does not auto-
matically translate into reduced energy losses. The system may still
experience losses due to factors such as converter inefficiencies, trans-
mission losses, and limitations in system control. Hybrid MGs require
advanced control and management systems, especially when operating
in islanded mode. Compared to AC MGs, they exhibit lower reliability,
mainly due to the inclusion of interface power converters in the distri-
bution network for DC-link generation [84]. Nonetheless, a decrease in
the number of converter stages can enhance the reliability of inter-
connected devices.

Addressing energy sources based MGs

Renewable energy resources based microgrids are powered pre-
dominantly by distributed renewable energy sources, typically consist-
ing of RRs and batteries. They offer low-carbon electricity to end-users
and are increasingly popular worldwide due to their reduced environ-
mental impact. However, the variable and intermittent nature of RESs
adds complexity to the MG’s operation, particularly in meeting fluctu-
ating demands. ESUs play a vital role in maximizing the utilization of
renewables and balancing demand and supply in MGs. Coordinating
storage systems with distributed RESs and variable power demand re-
mains a significant challenge, necessitating an effective power man-
agement microgrid system (PMMS) for renewable MGs. Renewable MGs
can be categorized based on their primary renewable sources into solar,
wind, biomass, micro-hydro, and hybrid MGs:

**Solar:** These are scalable and widely considered viable for rural electrification. Their effectiveness is contingent on sunlight availability and often includes storage to counteract periods of low sunlight.

**Wind:** These consist of interconnected loads and wind turbines, typically incorporating ESS to stabilize supply and store excess energy.

**Biomass:** These MGs utilize biomass gasifier systems to produce syngas, which is then used to generate electricity. While less common than solar and wind MGs, they are becoming more popular due to lower capital requirements.

**Micro-hydro:** These are usually run-of-the-river projects, ideal for areas with sufficient water flow, offering low energy generation costs.

**Hybrid:** Combining various renewable sources like PV, wind, biomass, and micro-hydro, these MGs can provide power in remote locations.

In contrast, fossil fuels MGs, typically powered by diesel or natural gas generators, are capable of operating in both islanded and grid-connected modes. They have been a standard for local power generation in microgrids but carry negative environmental and economic impacts. The high costs and carbon footprint of transporting fossil fuels are significant drawbacks. Consequently, many MGs are exploring cleaner alternatives to mitigate these impacts.

Addressing deployment based MGs

Microgrids can be classified into various categories based on their
specific applications. Some of the key types include:

**Defense:** These are small-scale electrical infrastructures designed to function almost independently at military base camps.

**Institute:** Found in corporate, university, and college campuses, these MGs often incorporate CHP systems.

**Community:** These local grid networks, typically in developed countries, are supported by high penetrations of local RRs and other DERs. They are commonly used to help communities achieve renewable energy targets.

**Isolated:** Small-scale and completely isolated from the main grid, these MGs generate their own electricity, often in remote island settings.

**District energy:** Providing both electricity and thermal energy, these MGs cater to heating (and sometimes cooling) requirements of various facilities.

Multiple control architectures and operational management in MGs

Microgrids are characterized by their distributed resources. The variability and intermittency of RRs add to the operational complexity of MGs, making a robust control strategy essential for ensuring stable and consistent power flow. The central controller (CC) of MGs plays a crucial role in controlling and managing the MG. It could be located at a local MG's CC or a distribution substation. CC oversees local distributed generation units and disseminated ESUs devices, coordinating with lower-level controllers. Additionally, MGs can employ distributed management methods such as droop contain and agent systems. In the context of MG control, several key requirements must be met:

**Power management:** This involves coordinating DG power supply and effective load sharing.

**Transition Management:** Ensuring seamless transitions between islanded and grid-tied methods of operation.

**Safety scheme:** This entails overseeing energy flow and essential equipment, in addition to handling grid faults.

**Power Conveyance:** Facilitating the transfer of power among the utility grid and the MGs.

**Optimization/technique:** Developing optimal MG dispatch plans for economic benefits and enhanced energy efficiency, tailored to the MG's conditions.

**Synchronization:** Aligning the MG with the power network for optimal power transmission.

**System stability:** Regulating voltage and frequency across various operating modes and maintaining a robust power network on both AC and DC sides of the MG. Fig. 5 provides an extensive classification of the control methods commonly employed in the operation of MGs. Also, a brief definition or short characteristic of each strategies is given in the Table 2, and their characteristics are explained more in detail in the following subsections.

Centralized control strategies

In the realm of MG management, there's a tale of centralized control, a method revered for its simplicity and efficiency. Picture a vast network of distributed generation units, each like a star in a galaxy, all orchestrated by a single, powerful central controller (CC) - the sun around which these stars revolve. In this system, the CC reigns supreme. It's the mastermind, overseeing every aspect of the MG's operations. Each distributed generation unit, equipped with its own local controller (LC), acts as an envoy, communicating directly with the CC. The CC, with the aid of cutting-edge computational technologies, monitors and analyzes data relayed from these LCs in real time, ensuring the smooth functioning of the MG universe [113]. The beauty of this centralized control system lies in its simplicity. Its implementation is straightforward, a testament to human ingenuity and technological advancement. It has shown remarkable efficiency in managing the MG cosmos, responding swiftly and effectively to the myriad demands of this complex network. However, this universe is not without its challenges. Large-scale hybrid systems, with their intricate web of components, often stretch the limits of centralized control [114]. The CC, for all its power, is also a single point of failure. Should it falter, the entire system risks descending into chaos. Moreover, this control technique, despite its strengths, struggles with flexibility and expandability, somewhat limiting the MG universe's potential to grow and evolve [63,115]. Thus, the story of centralized control in MGs is one of a mighty ruler, effective yet vulnerable, facing the future with the challenge of adapting and expanding its realm in an ever-changing landscape of energy needs and technological possibilities.
<figure><img src="image_7.png" /><figcaption>Fig. 5. Control architecture of MG (a) centralized, (b) decentralized, (c) distributed.</figcaption></figure>

<table><caption>**Table 2**

Brief characteristics of different control mechanisms of MGs.</caption><thead><tr><td>Control mechanism</td><td>Service type</td><td>Short characteristic</td><td>References</td><td>Control architecture</td></tr></thead><tbody><tr><td>Centralized</td><td>Central Processing</td><td>Central processing unit collects all measurements and chooses the next act for interacted operation inside the microgrid.</td><td>[95,96]</td><td>Post Communication</td></tr><tr><td>Decentralized</td><td>Local Measurement</td><td>Local measurements are utilized, and decisions are rendered at the component level, guided by predefined techniques embedded within every node.</td><td>[97,98]</td><td>Pre Communication</td></tr><tr><td>Distributed Multi-Agent</td><td>Decentralized</td><td>This approach employs a decentralized technique in which each local controller engages in communication with its neighboring controllers.</td><td>[99,100]</td><td>Post Communication</td></tr><tr><td>Post/post Communication</td><td>Dynamic Load Sharing</td><td>This method is founded on a master/slave, central, or concentrated control system, incorporating the principle of instantaneous current sharing.</td><td>[101,102]</td><td>Communication System</td></tr><tr><td>Master-Slave Mode</td><td>Master-Slave</td><td>Mostly leveraged for MG in standalone mode.</td><td>[103,104]</td><td>Control Mode</td></tr><tr><td>Peer-to-Peer Mode</td><td>Peer-to-Peer</td><td>Peer-to-peer control framework is essential for enabling plug-and-play functionality within MGs.</td><td>[105,106]</td><td>Control Mode</td></tr><tr><td>Combined Mode</td><td>Combined</td><td>This approach integrates the benefits of both master-slave and peer-to-peer control to ensure stable operation of the MG.</td><td>[107]</td><td>Control Mode</td></tr><tr><td>Primary</td><td>Reliable Operation</td><td>Provides reliable procedure and responds to communication catastrophes.</td><td>[108]</td><td>Control Level</td></tr><tr><td>Secondary</td><td>Frequency-Voltage Regulation</td><td>System adjusts the voltage and frequency in response to variations in load and supply.</td><td>[109,110]</td><td>Control Level</td></tr><tr><td>Tertiary</td><td>Power Flow Control</td><td>Regulates the transfer of power from the microgrid to the main grid.</td><td>[111,112]</td><td>Control Level</td></tr></tbody></table>

### Decentralized control strategies

In recent times, decentralized control has been significantly advanced to enhance the autonomy of micro sources and loads within Microgrids (MGs). This control approach focuses on maintaining stability, cost-effectiveness, and reliability in MG operations [116]. Decentralized control bases its decisions on local measurements and necessitates minimal local connections. Notably, it does not require high-performance computing units or extensive connectivity [113]. However, this method does not assure global optimum solutions for the entire MG system.

### Distributed control strategies

The exchange of information amid controllers in a system is facilitated to ensure that each controller has a degree of insight into the others' behaviors, thereby enhancing overall performance [117]. Table 3 concisely presents various control methods along with their respective advantages and disadvantages.

### Hierarchical control strategies

In microgrid control strategies, it is crucial to consider all time scales
<table><caption>**Table 3**
A comprehensive overview of control strategies for microgrids, along with their respective benefits and limitations [118].</caption><thead><tr><td>Control strategies</td><td>Benefits</td><td>Limitations</td></tr></thead><tbody><tr><td>Centralized</td><td>- Global optimum solutions</td><td>- Need communication architecture- Abridged scalability- Communication channels impacts stability</td></tr><tr><td>Decentralized</td><td>- No need of communication architecture- Reduced computation burden- Improved scalability- Higher reliability</td><td>- Lacks a universally optimal solution.</td></tr><tr><td>Distributed</td><td>- Lesser computation burden- Improved scalability- Better reliability</td><td>- Less optimal solutions- Necessitate communication infrastructure-The communication network influences stability.</td></tr></tbody></table>

of the system. These strategies are categorized into three hierarchical levels: (a) primary, (b) secondary, and (c) tertiary. The primary and secondary levels are concerned with the independent operation of the microgrid, whereas the tertiary level focuses on coordinating operations between the microgrid and the host network. Traditionally, hierarchical control is employed in existing power grids to regulate voltage and frequency and to maintain power balance [119,120]. The hierarchical control of microgrids is organized into three levels, as detailed in Fig. 6. This structure includes a multimode operation strategy comprising autonomous, cooperative, and scheduling controllers, as proposed in [52]. The primary level predominantly employs droop control [121], a standard approach for distributing power among microgrid generators [122]. Innovations in this area include a voltage-power droop and frequency reactive power boost control scheme for effective power sharing within converter-fed microgrids, as introduced in [123]. Additionally, a combined angle-frequency droop controller with a nonlinear control law has been developed for enhanced power sharing and control flexibility, as outlined in [124]. A droop-based strategy for hybrid microgrids focusing on common bus voltage regulation is discussed in [125]. For standalone microgrids, a virtual output-impedance loop is suggested in [126] to manage frequency and amplitude adjustments, especially in islanded setups with multiple generation units. An advanced droop control integrating a virtual power source and composite virtual impedance is also proposed for low-voltage microgrids [127]. Table 4 enumerates the contributions of control strategies centered around supervisory control applications within microgrid systems.

<figure><img src="image_8.png" /><figcaption>**Fig. 6.** Hierarchical control architecture of MG.</figcaption></figure>

<table><caption>**Table 4**
Applications for supervisory control strategy.</caption><thead><tr><td>Refs.</td><td>Control mechanism</td><td>Nature of MG</td><td>Key features</td></tr></thead><tbody><tr><td>[128]</td><td>Centralized</td><td>Alternating current</td><td>Implementation of distributed battery energy storage units (ESUs) for optimal control, focusing on the power equilibrium of every battery based on available discharge energy.</td></tr><tr><td>[129]</td><td>Centralized</td><td>Direct current</td><td>Development of a double-stage hierarchical control framework aimed at addressing the challenges of coordinating multiple batteries within a standalone MG.</td></tr><tr><td>[130]</td><td>Decentralized</td><td>Alternating current</td><td>Proposal of a interactive control architecture for isolated AC MGs featuring smooth transition droop mechanism. This allows for adaptable power adjustment of sustainable energy sources and the storage capacities of ESUs through seamless mode transitions.</td></tr><tr><td>[131]</td><td>Decentralized</td><td>Direct current</td><td>Introduction of a coordination strategy for standalone low-voltage DC microgrids, including a control architecture that facilitates the technique and specifies the optimum operating range for power-line channeling frequencies.</td></tr><tr><td>[132]</td><td>Hierarchical Multi-Agent</td><td>Alternating current</td><td>A distributed interactive control approach for ESU coordination to uphold supply-demand equilibrium and diminish net power loss due to charging/discharging inefficiencies.</td></tr><tr><td>[133]</td><td>Distributed Multi-Agent</td><td>Direct current</td><td>Establishment of a unified distributed control framework for DC microgrid operating modes, integrating distributed controllers for enhanced energy balancing.</td></tr></tbody></table>

Progress in microgrid operational management

Recent progress in control and management systems for off-grid and grid-connected MGs has been propelled by the growing integration of RRs, the necessity for greater grid adaptability, and the increasing intricacy of MG functionalities. The principal objective of these technological developments is to enhance the performance, dependability, and efficiency of these MGs. This includes ensuring smooth incorporation of distributed energy resources and proficiently overseeing grid operations. Key advancements in MG control and supervision systems encompass:

* **Proficient energy management:** Contemporary energy management in microgrids are increasingly harnessing artificial neural network, machine learning strategy, and optimization techniques for effective management of energy generation, storage, and consumption [134]. These advanced systems consistently observe, predict demanded energy and production. They dynamically enhance energy distribution and enable real-recorded decision-making to achieve optimal operational efficiency.

* **Effective optimal power flow (OPF):** The efficient power exchange between the microgrid and the main grid can be optimally facilitated in grid-connected mode. In tertiary layer uses OPF problem under double-levels control based on consensus algorithm to determine efficient power exchange between the microgrid and source grid [135]. Decisions are based on electricity prices, forecasts, and DER availability to minimize operational cost.

* **Robust ESUs management:** Advanced power management have been formulated to maximize the usage and effectiveness of ESUs in microgrids. These approaches incorporate smart scheduling and contain of ESU, taking into account real-time capacity demands,
availability of renewable energy, and current grid conditions [136,137]. Such approaches enable efficient energy balancing, peak load drop, load shedding, and provision for grid stability.

* **Management of grid-forming inverter:** Grid-forming inverter technology has gained prominence for its capability to autonomously manage the voltage (v) and frequency (f) in MGs, thereby reducing reliance on the utility grid [138]. This is increasingly important as RRs become further widespread. Enhanced control techniques related to grid-forming inverters are instrumental in improving grid stability, bolstering the resilience of MGs, and facilitating smooth transitions between grid-connected and islanded operational modes [139].

* **Amalgamation of demand-side management (DSM):** Advancement in control operation schemes within microgrids are now integrating DSM mechanisms, empowering consumers to engage actively in demanded load management. Through the application of sophisticated DSM techniques and different communication protocols, a real-time interface is established among the microgrid operator and end-users. This interaction enables load shedding/load shifting during maximum demand times, thereby optimizing overall energy usage [140].

* **Cyber resilience approach:** As microgrid operational arrangement become increasingly interconnected and reliant on digital communication and contain mechanism, ensuring their cyber-physical security is paramount [141]. To mitigate cyber threats, strategy and controlling systems are incorporating sophisticated security measures. These include encryption, validation protocols, anomaly detection, with invasion anticipation systems [142,143].

## Stability assessment

System stability has emerged as a critical concern in the operation of microgrids [144]. Consequently, several review papers have been worked, focusing on the organization and investigation of MG stability. A summary of these review articles concerning microgrid stability, alongside diverse approaches for analyzing small-signal stability within MGs is provided in Table 5.

To evaluate dynamic stability and transient analysis, small signal

<caption>**Table 5**</caption>

Comprehensive examination of research on microgrid stability, alongside diverse approaches for analyzing small-signal stability within MGs.

<table><thead><tr><td>Ref.</td><td>Focus</td><td>Analysis scheme</td><td>Goal/Goals</td></tr></thead><tbody><tr><td>[154]</td><td>Microgrid Stability</td><td>Classification Method</td><td>Proposes a stability classification method based on microgrid characteristics assessments, focusing on operation approach, disturbance nature, and time scale.</td></tr><tr><td>[155]</td><td>Microgrid Stability</td><td>Lyapunov-based Large-signal Stability Study</td><td>Conducts a comprehensive survey on stability studies concerning microgrid load types and settings.</td></tr><tr><td>[156]</td><td>Droop Mechanism</td><td>Eigenvalue assessment using state-space domain</td><td>Proposes an enhanced droop control method that incorporates voltage amplitude feedback PI control, aimed at achieving reliable output voltage amplitude and equitable load sharing among distributed generators (DGs).</td></tr><tr><td>[157]</td><td>Complex Load</td><td>Load Dynamics Assessment</td><td>Studies the impact of static load, damping, and inertia factors on the stability of microgrids.</td></tr><tr><td>[158]</td><td>X/R Ratio</td><td>Time Domain Simulation</td><td>Outlines the control system for an islanded microgrid utilizing distributed control framework and discusses the approach to small-signal modeling.</td></tr></tbody></table>

analysis is utilized, enabling designers to fine-tune control parameters [145,146]. The microgrid concept plays a pivotal role in integrating distributed sustainable energies with the main grid. Given the regular fluctuations in power output from distributed generators, accurately determining microgrid parameters poses a challenge, highlighting the significance of assessing microgrid's small signal stability [147,148].

The persistent issues contributing to small signal stability problems in microgrids are associated with the feedforward controller, minor load changes, system's damping, constant load switching, and the power limits of micro sources. Fig. 7 illustrates the study focus on the small signal stabilization of microgrids.

The analysis of small-signal stabilization, focusing on the collective droop and mean power technique for dynamic load sharing strategy among numerous dispersed generation systems in an isolated AC source mode, is explored. In [149], a small-signal MG model is developed, with its precision confirmed via simulations based on the novel nonlinear model. Authors [150] employs a strategy that integrates online grid parameter estimation with small signal stabilization analysis to detect islanding events and modify the droop mechanism parameters of inverters. Furthermore, [151] introduces a methodology for small signal study of droop-integrated generation control across numerous distributed inverters arranged in parallel, including active power-frequency (dp-df) and reactive power-voltage (dq-dv) controllers. The stability of various converter-integrated islanded microgrids is assessed using eigenvalue study [152], wherein the voltage source based converter for each disseminated generation, along with its state feedforward and droop controllers, is exhibited within the state space province. Lastly, [153] examines the impact of active loads on system small-signal stability, observing that active loads with elevated DC voltage controller gain may precipitate instability.

## Hierarchical microgrid stability

The unique characteristics of microgrids, introduce a distinct stability challenges not typically encountered in conventional power systems. In traditional setups, issues related to transient disturbances and voltage stability are more prevalent than those concerning frequency stability. In contrast, isolated or off-grid microgrids face heightened difficulties in maintaining frequency stability due to their low inertia MG network as well as high integration of RRs. As RRs become increasingly a part of MGs, its system becomes prone to disturbances and instability due to low damping coefficients and inertia. Therefore, the simultaneous frequency and voltage control problem of MGs comprised of renewable wind and storage units based virtual synchronous generator (VSG) support could be possible solution for that [159]. Furthermore, specific stability issues common in large inter-tied grids, like., inter-zonal oscillations and voltage downfall, are conspicuously absent in microgrid settings. Therefore, there is a necessity to reassess and refine existing power networks stability arrangements to accurately address pertinent stability concerns specific to MGs. Stability in MGs can be classified based on the underlying cause of instability, the magnitude of the disturbance, the physical apparatus enabled, the duration over which instability occurs, and the methodologies used for analysis, as proposed in [160]. Voltage and frequency in microgrids exhibit strong interdependencies, leading to instability that manifests through fluctuations across all system variables. This interconnected nature complicates traditional classifications like “voltage instability” or “frequency instability,” which generally rely exclusively on the measurement of respective variables. To address this challenge, an additional practical organization method is proposed here, emphasizing the role of equipment and controllers involved in instability triggered by system disturbances. As outlined in the preceding discussion, Fig. 8 illustrates the hierarchical stability framework in microgrids. Accordingly, microgrid stability is categorized into two primary domains: phenomena associated with equipment contain systems, and phenomena related to the management of active as well as reactive power distribution and
<figure><img src="image_9.png" /><figcaption>Fig. 7. Research focus on small-signal stability of MG.</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>Fig. 8. Hierarchical stability outlook of MG.</figcaption></figure>

equilibrium. It's important to note that instability in microgrids can occur over varying time scales—short-term issues span up to a few seconds, while longer-term stability concerns extend beyond this time-frame, reflecting the overall stability of the system.

### a) Power share and equilibrium stability

Power share and equilibrium stability concerns the system's capability to maintain equilibrium in power distribution among DERs, ensuring it meets operational demands. Challenges in this area arise from various factors including generator failures, exceeding DER limits, inefficient power allocation among multiple DERs, incorrect prioritization of primary resources, and involuntary load tripping without fault. Additionally, specific loads like constant power devices or induction motors can induce instability like, voltage fluctuations with harmonic issues. This type of stability is further categorized into frequency $\Rightarrow$'f' and voltage $\Rightarrow$'v' Stability, which will be detailed subsequently.

#### 1) Stability of frequency

Frequency fluctuation poses a significant challenge in isolated or off-

grid microgrids due to specific system characteristics, notably lesser system's inertia with high proportion of irregular RRs. The limited amount of generation components in MGs makes the system vulnerable to major disturbances during generator outages, causing rapid and significant frequency deviations that threaten system stability [161]. Conventional frequency control methods often struggle to react swiftly enough to these rapid frequency changes, even with sufficient generation reserves [162]. The pronounced interdependency among voltage/ frequency in MGs complicates frequency regulation efforts. Initially, the elevated R/X ratios in MG feeders challenge the traditional approach of separating active power flow from voltage levels. [163]. Secondly, the comparatively small size of MGs means that voltage fluctuations at the terminals of DERs promptly affect load conditions, thereby modifying system demand in accordance with the sensitivity of load voltage indices [164]. Consequently, this coupling of 'v' and 'f' must be considered in the analyses of frequency stability and in the development of control strategies within microgrids. Frequency instability in MGs can arise from
various causes. For instance, a sudden increase in load coupled with inadequate system response can swiftly reduce frequency due to low system inertia, potentially triggering system blackouts through protective measures [161]. Inadequate coordination among multiple frequency controllers and ineffective power sharing between DERs can lead to problems with small-perturbation stability, manifesting as undamped frequency oscillations that may last from seconds to minutes, a phenomenon rarely seen in larger grids. Depending on the speed of frequency protection schemes in tripping the system, this instability can persist over the long term. Inadequate generation reserve can similarly cause steady-state frequency to deviate beyond acceptable operational limits, prompting under-frequency load shedding relays, a practice akin to larger grids. Conversely, traditional long-term frequency stability concerns in larger grids, such as overspeed controls of steam turbines and protection and control schemes for boilers and reactive power, do not typically apply to microgrids.

## 2) Stability of voltage

In microgrids, voltage instability differs significantly from conventional power systems primarily due to shorter feeder lengths that minimize voltage drops [164]. Unlike larger grids where long transmission lines often limit power transfer and contribute to voltage instability, microgrids face unique challenges related to the operational limits of distributed resources and the robustness of loads to supplied voltage. Voltage collapse, a sustained and gradual decline in voltage interactive with load retrieval and supply capacity of reactive power, is not typically detected in MGs. Instead, instability arises from factors such as fault-induced delayed voltage recovery (FIDVR) [165], particularly problematic with high penetration of induction motors that may cause voltage drops severe enough to lead to motor stall and subsequent system instability or significant load shedding because of reactive power shortages [166].

Furthermore, voltage instability in microgrids can be exacerbated by the dynamics of Voltage Source Converter (VSC)-based DERs. These DERs maintain voltage across dc-link capacitors, which can exhibit significant ripples when reactive power demand nears operational limits, affecting both active and reactive power injections [167]. Short-term voltage instabilities in microgrids stem from poor coordination of control systems or rapid fluctuations in power mismatches, while long-term instabilities arise as DERs approach their output limits over time, particularly under sustained increases in demand from thermoelectric loads. Managing these complexities requires tailored stability analyses and robust control strategies specific to microgrid dynamics, distinct from traditional concerns in larger grid systems.

### b) Control stability services

Stability issues in control systems can arise from inadequate design, such as harmonic resonance among parallel DERs, or from insufficient tuning of individual equipment controllers. In cases where controllers are poorly tuned, they become the main cause of instability, necessitating either retuning of the controller(s) or disconnection of the affected equipment to restore system stability.

This category of stability concerns control loops for electric machines and inverters, as well as components like LCL filters and Phase-Locked Loops (PLLs). It is further classified into Electric Machine and Converter Stability, addressing specific dynamics and interactions within these control systems.

### 1) Stability of electrical machine

Traditionally, stability analyses in power systems focus on synchronous machines' ability to re-synchronize with the grid after experiencing angular acceleration during faults. This specific behavior, however, is not observed in microgrids. In microgrid settings, the resistive nature can cause synchronous machines to slow down in the event of short circuits occurring at the feeder's end, as evidenced by experimental findings detailed in [168].

In conventional power systems, small-perturbation stability issues often manifest as either irregular increases or undamped oscillations in the rotor angle of synchronous generators [169]. Conversely, in the

context of microgrids, stability concerns predominantly stem from inadequate tuning of exciters and governors in synchronous machines [170].

### 2) Stability of converter

In microgrids, inverters are susceptible to both minor and significant instability issues. The precise tuning of inner voltage and current control loops poses a significant challenge and is crucial for maintaining small-perturbation stability within the system. Moreover, the tripping of DERs, particularly inverter-based RR, during large disturbances-often triggered by under-frequency and under-voltage protection schemes can lead to complete system blackouts, highlighting a critical concern.

Unlike low-frequency oscillations influenced by external power controls, high harmonic-frequency oscillations in microgrids can result from interactions within inner current and voltage control loops, typically ranging from hundreds of Hz to several kHz [171]. High-frequency switching activities can exacerbate this harmonic instability, causing resonances in LCL power filters or parasitic capacitors within feeders [171,172]. Additionally, resonances in inverter LCL filters can be induced by the inverter's control mechanism itself or through interactions with adjacent controllers. Active damping strategies are essential for preventing or mitigating these harmonic instabilities [173]. The widespread adoption of phase-locked loops (PLLs) for grid synchronization purposes in grid-following or grid-feeding inverters alters the admittance matrices of the power system, potentially introducing instabilities [174].

## Enhancement of stability

Enhancements in small signal stability are achieved through the implementation of additional control loops, stabilizers for distributed generations, coordinated distributed sources control, and energy management systems. Various strategies have been proposed for these improvements. Enhancing the small signal stability in a microgrid encompasses three main areas [175]: (a) optimization of controller parameters [176] (b) enhancements in droop control [177] and (c) optimized design of hierarchical control strategies [178]. The microgrid system faces instability challenges due to the constant power demand from numerous electronic devices. A technique to improve AC microgrid stability under constant load conditions is introduced in [179], proposing a storage-based virtual impedance power compensation method alongside active and reactive power compensation techniques as viable solutions. Reference [180] suggests an improvement for small signal stability in islanded microgrids through an advanced power control stage model within the hierarchical control framework, incorporating two additional feedforward loops. This method demonstrates the controller's robustness, frequency-domain modeling of the microgrid, and analyses of robustness and closed-loop stability.

## Clusters of MG

The expanding use of microgrids underscores the need for additional research on their interactions, especially within microgrid clusters. Studies highlight that microgrid clusters offer economic benefits by reducing emissions, lowering user costs, and supporting load growth [181]. They also enable efficient energy trading through cooperation. Additionally, reference [182] uses coalitional game theory to evaluate cooperative strategies in microgrid clusters, showing that the proposed approach reduces average power losses compared to non-cooperative methods. Furthermore, [183] applies game theory to examine price competition among interconnected microgrids, computing a unique Nash Equilibrium.

The study in [184] employs a game-theoretic framework to analyze strategic interactions among decision-making entities in decentralized microgrid environments, including smart agents and advanced communication systems. In [185], the focus is on two isolated microgrids that exchange energy peer-to-peer to minimize total energy costs
while meeting local demands. Additionally, [186] presents a microgrid cluster control system using Multi-Agent Systems (MAS) for improved communication and coordination among adjacent microgrids. The study in [187] introduces a microgrid cluster with a distributed hierarchical control system and Multi-Agent System (MAS) architecture. In [188], microgrid cluster control is organized into three levels: local controllers, a central microgrid controller, and a distribution management system, coordinated by a central autonomous management controller. Additionally, [189] proposes a hierarchical and decentralized approach for coordinating voltage and frequency control and for state estimation in microgrid clusters.

## Adaptive load frequency stabilization

Renewable energy sources play a significant role in contemporary power systems, particularly within distributed network configurations [190], highlighting the importance of adaptive frequency stabilization in microgrid operations [191]. Managing frequency stabilization is crucial for the operation and control of power systems to ensure the supply of reliable and high-quality electric power [192,193]. Additionally, a seamless transition between grid-connected and standalone modes is vital for the dependable functioning of microgrids [194,195].

Secondary control modifies the load orientation set points of selected generators to reestablish the power system's frequency following initial droop adjustments. Reference [196] presents a robust Proportional-Integral (PI) control strategy for stabilizing the system frequency of microgrid power systems, wherein the sturdiness of the classical PI controller is enhanced through an inverse preservative perturbation, framed as an optimization challenge, with Genetic Algorithms (GA) utilized to fine-tune and augment the PI control parameters. A comprehensive frequency stabilization strategy for autonomous microgrids is proposed in [197], employing an electronic load controller for microgrid frequency regulation via a centralized frequency stabilization controller, incorporating a combination of battery storage systems and smart loads. Reference [198] introduces an intelligent method employing fuzzy logic and Particle Swarm Optimization (PSO) techniques for the optimal adjustment of pre-existing PI-based frequency controllers in AC microgrid systems for the regulation of frequency. Further, [199] suggests a control strategy interactive on battery ESU and diesel powered generators for AC microgrid frequency regulation, tested under various scenarios including normal operations, emergencies (loss of distributed generation units), fluctuating demand conditions with actual communication delay time variation. Distributed averaging-integrated frequency as well as voltage contain for isolated microgrids are proposed in [200], leveraging close neighbor communication and local data within the controller for cooperative control actions. The influence of power variations from photovoltaic plants on the frequency response of standalone microgrids and diesel powered generators is examined in [201], with a system's one-line diagram established in simulation software for peak and off-peak load flow analysis in a steady-state.

## Communication

In microgrid systems, secondary control plays a critical role in maintaining voltage and frequency but is highly sensitive to the communication infrastructure. There are three main control architectures: decentralized, centralized, and distributed.

Decentralized control relies on multiple LCs, each managing its subsystem independently using local measurements. Techniques like distributed bus signaling and primary demand sharing enable basic coordination. While this approach reduces dependence on communication networks, it can suffer from reduced performance and stability under dynamic conditions. Low-cost networks, such as peer-to-peer setups using bus topology, are sometimes added to improve flexibility, though they often lack strong organization and security [202]. Communication

delays in this setup can still impair system responsiveness.

Centralized control uses a single central controller to collect data and manage the entire system. This setup is efficient and scalable (often implemented with star topology), but highly vulnerable to communication failures. Delays in data transmission can cause instability, overshoot, or system failure [203]. To enhance reliability, systems typically include redundant communication paths and latency-aware algorithms.

Distributed control combines aspects of the other two approaches. Each local controller communicates with its neighboring units and uses consensus algorithms to coordinate decisions. This structure is more resilient to partial communication failures, but it is also very sensitive to communication delays, which can lead to oscillations, inaccurate power sharing, and slow voltage/frequency restoration [204,205]. Techniques like redundancy, adaptive timing, and event-triggered communication help mitigate these issues.

Each control method has trade-offs between performance, resilience, communication needs, and implementation complexity.

## Artificial intelligence (AI) in MG operation

With the ongoing transformation of the energy sector and the increasing integration of DERs, artificial intelligence (AI) is anticipated to play an essential and irreplaceable role in modern power systems. At the primary control level, AI methodologies such as adaptive neurofuzzy inference systems have been leveraged to fine-tune droop control coefficients. This optimization facilitates more accurate power distribution and enhanced regulation of voltage and frequency, thereby improving the system's dynamic performance and overall stability [206].

At the secondary control layer, AI contributes through the implementation of multi-agent systems (MAS) and reinforcement learning approaches, such as Q-learning, to enable efficient voltage and frequency restoration. These techniques significantly strengthen system robustness and operational resilience under varying conditions [207]. In addition, authors [208] in have emphasized advancements in demand side management (DSM), particularly focusing on load scheduling methodologies and the supporting communication technologies that enable effective DSM implementation. Complementarily, Raza et al. [209] have conducted comprehensive reviews of AI-based approaches for load forecasting, with particular emphasis on models utilizing artificial neural networks.

## Uncertainty in MG management

The inherent variability and uncertainty associated with microgrid components—particularly the intermittent generation from renewable energy sources and fluctuating load demand—must be carefully accounted for in effective microgrid management strategies. Uncertainty-based programming offers a structured approach to addressing the inherent uncertainties of MG components. In this context, it is essential to first identify and characterize the uncertain parameters and system components before incorporating them into the optimization or control framework. Recent studies have taken into account various uncertain components in microgrid systems, including wind velocity [210], load demand, electricity tariffs, weather conditions, solar irradiance, electric vehicle (EV) storage capacity, disconnection timing from the main grid, and available facility capacity [211]. To address the challenges posed by uncertainty in microgrid systems, a variety of uncertainty modeling and management techniques have been proposed. Methods such as the K-means clustering technique and the backward reduction method are employed to minimize the number of scenarios, thereby simplifying the computational complexity of the problem. Additionally, several other approaches have been recently leveraged to manage uncertainties, including the point estimate technique [212], the Kumaraswamy distribution [213], the nominal distribution function [214], and model predictive control (MPC) [215].
# Manifold Barriers in MGs

Although microgrids offer considerable advantages, their development is not without its challenges and constraints. The primary obstacles faced by microgrids can be classified into four main groups, as depicted in Fig. 9.

## Operational barrier aspects

The primary management and operational barriers encountered by a microgrid include:

* During the initial stages of transitioning to island mode, the sudden surge in current intake can impact the system's frequency and voltages. This situation could lead to generators tripping and shutting down at the start-up phase. Addressing this issue necessitates an exploration of energy generation techniques in island mode and the creation of control systems specifically designed for MG operations.

* Energy regulation typically involves adjusting multiple parameters. Subsequently, these parameters must undergo simulation to identify optimal solutions. Determining the ideal values within microgrids presents a significant challenge due to the presence of varied uncertainties and non-specific occurrences, in addition to well-defined specific events [216].

* Microgrids, especially those based on renewable energy, necessitate distinct design, modeling, and planning approaches compared to traditional fuel-based systems, which are more commonly understood [217,218]. A significant factor contributing to the reduced lifespan of MGs is inadequate design. The development of renewable MGs requires an in-depth comprehension of both the available energy resources and the needs of the consumers [219].

* For every integrated power source versus load scenario within a microgrid, it is essential to identify and delineate specific circumstances, including temporary switching or emergency shedding. Given that a microgrid comprises loads and generators that exhibit diverse operational characteristics and behaviors, this stage is both crucial and complex [220,221].

* Maintaining system security requires the adoption of contingency plans and emergency procedures, such as demand-side management, load shedding, islanding, or unit shutdown. During contingencies, it is crucial to economically reschedule generation to control system

loading and preserve voltage/frequency at the load-end. Maintaining system security via emergency actions and strategic contingency planning, involving load shifting, management of distributed sources, isolating, and unit/system breakdown, is paramount.

* Ensuring quality of power within a microgrid necessitates maintaining a balance of active and reactive power in the short term. The central controllers and micro controllers (MCs) in an MG should integrate SCADA-based capabilities for metering, control, and protection, along with system diagnostics via state estimation functions. A thorough design and functional analysis are crucial for maximizing MG efficiency, with particular attention to the MG's operational modes and configurations when designing its control system, incorporating various effective control strategies [222,223].

* Load flow analysis is essential across all MG operational conditions to assess current flow and voltage levels, identifying critical loads and the complexities of variable load profiles [224,225]. Achieving a balance between generation and load in island mode is a common challenge, requiring constant management to prevent instability due to load fluctuations.

* System stability analysis is imperative for predicting, monitoring, and assessing transient events caused by typical and atypical disruptions. Given the diverse array of power sources and components within MGs, including inertia-supported generators and stationary converter-interactive solar PV, wind farm, and ESUs, maintaining stability is complex [226,227]. The inclusion of various converters, such as those utilizing power electronic components with virtual synchronous machines, adds further complexity to this issue. Manufacturers and designers must undertake extensive research and maintain a close connection with equipment to ensure system stability [228].

## Elements and interoperability

* Essential for conducting power system studies, system specifications and single-line diagrams are fundamental in detailing and analyzing the operational behavior of microgrids [229,230].

* While current feeder designs prioritize robust power generation and distribution, adapting these to meet the unique demands of MGs poses challenges [220].

<figure><img src="image_11.png" /><figcaption>Fig. 9. Obstacles to MG implementation.</figcaption></figure>
* Effective management, protection, and control of MGs depend on advanced telecommunications infrastructures and standardized communication protocols [231].

## Distributed resources amalgamation

When connected to the main grid, microgrids facilitate bidirectional power flows, leading to voltage rise issues due to the integration of numerous distributed generators, marking a significant technological challenge [232]. The intermittent nature of solar photovoltaic systems often results in short-term voltage fluctuations, disrupting power regulation and protection mechanisms, thereby potentially reducing the lifespan of the equipment [233].

## Security barrier

Key security challenges that may arise within a microgrid include:

* Limiting short-circuit current (ShC) are determined based on the highest and lowest currents resulting from power system faults. The challenge lies in the ShC's variability across different operating configurations due to various power sources and loads [226,234].

* Managing neutral earthing presents a complex aspect of protection strategy in MGs. This complexity is due to the MG's transitioning between power sources, utilization of multiple power sources (like spinning machines and converters), and its connection with the main grid. While local grid regulations primarily dictate earthing installation, the distribution and maintenance of neutral earthing can introduce specific challenges [235].

* Given the evident variability and low ShC levels, there is a pressing need for protection research. The configuration of a microgrid must encompass not only effective protection equipment and ensure personnel safety but also facilitate coordinated and sequential operation of protection devices. In MGs, traditional protection strategies might not be straightforward or effective, thereby requiring innovative solutions and compromises [221,236].

## Economic and market barriers

Investing in MGs is significant, with many of its components like fuel cells and smart grid technologies not yet commercially sustainable without financial incentives. For cost-effective operations, strategies such as economic load dispatch and efficient power flow are crucial. Hybrid systems increase complexity and might elevate electricity production costs.

Infrastructure costs, included in utility tariffs, could unfairly burden non-net metering users as individual generation reduces utility revenue, potentially impacting the funding for necessary grid upgrades [237]. Remote MGs installations face higher maintenance and transportation costs, and the substantial installation expenses of distributed resources might require government subsidies to promote investment towards meeting environmental goals.

Similarly, market barriers include potential energy supply pricing issues during outages, with MGs possibly exploiting a monopoly situation. Thus, a proper market infrastructure is essential for MGs' long-term development.

## Standardization and administrative barrier

As the MG sector is emerging, there is a need for the development and revision of standards and protocols. These should cover the integration of micro sources into both traditional and deregulated power markets, along with safety and protection guidelines. Standards such as G59/1 and IEEE 1547 require updates to facilitate the seamless integration of MGs with active distribution networks. Furthermore, there is a necessity for research to reassess the IEEE 2030.7-2017 standard for

MG's controllers. In addition, a uniform regulatory framework for MG operations is absent in many countries. While some governments are advocating for the expansion of sustainable electricity through MGs, standardized regulations for their future governance remain pending.

## Future research trajectories in MGs

The field of microgrids presents a dynamic area of study within power engineering, attracting significant research focus in recent studies. Despite this attention, there remain numerous critical challenges yet to be explored. Both AC and DC MGs offer a range of open research opportunities crucial for future advancements. This document outlines key areas that warrant further investigation in upcoming MG research endeavors.

* Future microgrids will require a system redesign to manage the increased complexity from plug-and-play power sources, ESUs, and loads.

* Research should focus on designing systems that enable MGs to transition smoothly between grid-connected and autonomous modes.

* Traditional fixed relay settings may not suffice for MGs, necessitating further research into developing comprehensive protection strategies for safe operation across all modes and transitions.

* A sophisticated control method is essential for managing system parameters in MGs, especially in standalone mode where operating elements have diverse characteristics.

* Coordinating renewable sources, storage systems, and loads requires strategic planning to optimize the use of power sources economically.

* Standalone MGs need efficient control strategies to balance generation and load.

* Future studies should explore the use of virtual-inertia with varied features to sustain MG inertia.

* With the growth of EVs, their integration with MGs presents a promising area for enhancing power system development.

* Investigating the combined use of nuclear energy and RRs could lead to a sustainable energy mix, requiring studies on hybrid energy systems and energy storage technologies.

* Establishing reliable signaling and communication infrastructure is crucial for coordinated operation among multiple MGs.

* Integration of smart metering and network control is essential in MGs for efficient operation.

* Developing a universally accepted framework of standards, regulations, and processes is vital for the global adoption and successful integration of MGs.

## Conclusion

This study aimed to offer a comprehensive overview of microgrids, acknowledging their potential significance. It delves into the principal technologies utilized in MGs and categorizes them into seven distinct groups based on their applications, infrastructure, and the needs of end-users. The review further examines MG control strategies, providing insights into these approaches, and elaborates on methods for enhancing stability. The advent of MGs undoubtedly paves the way for a more sustainable future and improved power delivery services. Yet, there remain several areas in need of refinement. Various research questions and obstacles pertinent to MGs have been pinpointed, with suggestions for future investigations to tackle these concerns. This review aims to capture the interest of scholars, professionals, and researchers in the field of MGs by presenting state-of-the-art information. However, it does not cover essential communication systems necessary for MG deployment, suggesting that future studies could focus on evaluating the progress in MG communications research.
CRediT authorship contribution statement

**Abdul Latif:** Writing – original draft, Methodology, Investigation, Formal analysis, Conceptualization. **Abdelhakim Saim:** Writing – review & editing, Validation, Supervision. **Azeddine Houari:** Writing – review & editing, Visualization, Supervision, Project administration. **Ali Djeriou:** Visualization, Supervision, Resources, Project administration.

Funding

This research was supported by the National Research Agency (ANR), LEAP RE "MiDiNA—Microgrids Development in North Africa" project, grant number "ANR-23-LERE-0002-01".

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

All authors approved the version of the manuscript to be published.

Data availability

No data was used for the research described in the article.

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