https://doi.org/10.37815/rte.v37n1.1343

Original articles

Effective Strategies for Mitigating Voltage and
Frequency Fluctuations in Isolated Microgrids: A Literature Review

Estrategias
efectivas para mitigar fluctuaciones de tensión y frecuencia en microrredes
aisladas: Una revisión de literatura

Santiago
Arcos-Echeverría1 https://orcid.org/0009-0001-3133-2257,

Danny
Ochoa-Correa2  https://orcid.org/0000-0001-5633-1480

1Universidad
de Cuenca, Facultad de
Ingeniería , Cuenca, Ecuador

[email-masked]

2Universidad
de Cuenca, Facultad de
Ingeniería, Departamento de Ingeniería Eléctrica, Electrónica y
Telecomunicaciones, Cuenca, Ecuador

[email-masked]

Sent:       2025/06/22

Accepted:       2025/10/29

Published:       2025/12/15

Abstract

Territorial expansion has posed new
challenges for electrical systems, driving the need to electrify remote rural
areas and island territories. This demand has fostered the development of
electrical microgrids based on distributed renewable generation, which, due to
their low inertia, experience voltage and frequency instability—particularly
during overloads or transitions between isolated and grid-connected modes. This
article presents a literature review focusing on strategies to mitigate these
fluctuations, analyzing 28 recent publications. The findings highlight adaptive
controllers, smart inverter compensation, and the integration of energy storage
systems as dynamic support tools, showing a preference for solutions based on
power electronics and predictive control algorithms.

Keywords: renewable
energy, energy storage systems, voltage fluctuations, frequency fluctuations,
low-inertia systems.

Summary: Introduction, Methodology, Descriptive Analysis of Literature, Isolated
Microgrids, Control Strategies for the Stability of Isolated Microgrids, Conclusions.

How to cite: Arcos-Echeverría,
S. & Ochoa-Correa, D. (2025). Effective Strategies for Mitigating
Voltage and Frequency Fluctuations in Isolated Microgrids: A Literature
Review. Revista Tecnológica - Espol, 37(2), 145-169. https://rte.espol.edu.ec/index.php/tecnologica/article/view/1343

Resumen

La expansión territorial ha
generado nuevos desafíos para los sistemas eléctricos, impulsando la necesidad
de electrificar zonas rurales de difícil acceso y territorios insulares. Esta
demanda ha fomentado el desarrollo de microrredes eléctricas basadas en
generación distribuida a partir de fuentes renovables, las cuales, debido a su
baja inercia, presentan inestabilidad en frecuencia y voltaje, especialmente
durante sobrecargas o transiciones entre modos de operación aislado y conectado
a red. Este artículo presenta una revisión de literatura sobre estrategias para
mitigar estas fluctuaciones, analizando 28 publicaciones recientes. Entre los
enfoques identificados se destacan los controladores adaptativos, la
compensación mediante inversores inteligentes, y la incorporación de
almacenamiento energético como mecanismo de soporte dinámico, evidenciándose
una preferencia por soluciones basadas en electrónica de potencia y algoritmos
predictivos.

Palabras
clave: energía renovable, sistemas de almacenamiento de
energía, fluctuaciones de tensión, fluctuaciones de frecuencia, sistemas de
baja inercia.

Introduction

Implementing
electrical microgrids in modern power systems is essential as societies
transition toward more sustainable and resilient energy infrastructures.
Isolated microgrids, which operate independently or in conjunction with the
main grid, face the critical challenge of managing voltage fluctuations. The
increasing integration of intermittent renewable energies, such as solar and
wind power, and the concurrent abandonment of traditional fossil fuels
exacerbate this challenge. The need for a robust solution is evident, as these
fluctuations can lead to inefficiencies and disruptions in power supply,
affecting the reliability of the entire power grid (Pilehvar & Mirafzal,
2020a). In contrast, microgrids connected to the public grid can dynamically control
the voltage at the alternating current (AC) node to maintain stability. To
address fluctuations in isolated microgrids, most solutions in the literature
modify the conventional inverter control scheme using various techniques to
mitigate short-term transients and prevent outages caused by random events.

For
example, in the context of blackouts, Bassey and Butler-Purry (2022) use the
mixed-integer linear programming (MILP) method to implement black start,
restoring the system as quickly as possible. However, authors Bassey and
Butler-Purry (Bassey & Butler-Purry, 2020) indicate that the MILP method
fails to compensate for load balance and requires higher computational capacity
due to its analysis in an isolated microgrid adapted from the IEEE 13-node test
feeder.

To address
frequency fluctuations in photovoltaic units, Pilehvar and Mirafzal (2020c)
propose using an adaptive piecewise droop (APD) curve in inverters. In another
study, the same authors (Pilehvar & Mirafzal, 2020a) employ a piecewise
linear-elliptic (PLE) drop in energy storage systems to improve inverter
stability and reduce voltage variations through reactive energy
injection/absorption during transients.

Furthermore,
energy storage systems used in renewable energy-based electrical systems, such
as wind and solar, play a crucial role in storing excess electricity and
providing system stability (Ochoa & Martinez, 2021).

Another
approach, the virtual synchronous generator, has been shown to enhance the
inertia and damping of inverter-based distributed generators, thereby improving
frequency regulation in isolated microgrids (Yuan et al., 2018).

A strategy
called 3P four-leg inverters (3P4LI) has also been proposed by Mohamed Salim
and El-Sayed Salem Aboraya (Mohamed Salim & El-Sayed Salem Aboraya, 2024).
This strategy is based on connecting DG to improve stability by employing a new
control architecture called triple loop compensation (TLC), which integrates
PI, PR, and feedforward schemes. This is achieved by optimizing the TLC
parameters (Mohamed Salim & El-Sayed Salem Aboraya, 2024).

There are
also methods based on distributed generators, such as the one proposed by A. R.
Singh et al. (2023), which minimize voltage unbalance using a positive-sequence
controller and a negative-sequence controller, yielding favourable results even
in the presence of time-varying loads.

Another
method analyzed involves implementing a frequency controller, which utilizes
the load's sensitivity to operating voltages to achieve load regulation (Kokila
Vani et al., 2021). This method eliminates the need for additional
communication infrastructure by relying solely on local frequency and voltage
for feedback.

For the
same purpose, an adaptive switched filter compensator (ASFC) with a PID
controller has been proposed by Elmetwaly et al. (2020) to improve the dynamic
performance of the microgrid. The Grasshopper Optimization Algorithm (GOA) has
been applied to this controller to allow it to adapt and self-tune according to
changes in system conditions.

Given the
increasing deployment of renewable-based microgrids in remote, rural, and
islanded areas, ensuring stable and reliable operation has become a critical
engineering challenge. These systems often rely on inverter-based distributed
generation with low or virtually no mechanical inertia, making them inherently
more susceptible to voltage and frequency instabilities—particularly during
load transients, mode transitions, or fault conditions. While numerous studies
have proposed isolated solutions to mitigate these issues, the rapid
proliferation of control strategies, coupled with the lack of standardized
evaluation frameworks, has resulted in a fragmented research landscape.
Existing reviews tend to focus on specific technologies (e.g., battery energy
storage or virtual synchronous generators) or address either voltage or
frequency regulation separately, without offering an integrated analysis across
multiple approaches.

This
literature review addresses that gap by identifying, classifying, and analyzing
28 peer-reviewed studies published between 2017 and 2025 that examine
mitigation methods involving smart inverters, energy storage systems, and
advanced control algorithms. The findings provide a comprehensive overview of
recent technological developments, highlighting trends, advantages, and
limitations of current solutions. This offers valuable insights for researchers
and practitioners seeking to enhance the dynamic performance of low-inertia
electrical systems.

Methodology

The
literature review presented in this article follows a structured approach,
incorporating elements of the PRISMA methodology for systematic literature
reviews (SLR) (PRISMA-P Group et al., 2015). This methodology specifies that
the review should have a well-defined methodological framework to ensure a
comprehensive explanation of the process, enabling potential replication of the
work. To achieve this, we considered the 17 items outlined by Shamseer et al.
(2015), which can be categorized into administrative information, introduction,
and methods.

Once the
context of the research topic was established, the search was conducted in the
SCOPUS bibliographic database. Scopus is a preferred database for literature
reviews due to its comprehensive coverage of articles from reputable journals
across diverse disciplines, including IEEE, MDPI, ScienceDirect, and others.
This extensive aggregation ensures inclusive representation of scholarly
research, enabling researchers to access diverse perspectives and findings.
Additionally, Scopus's commitment to quality control and its global reach make
it a reliable source for high-quality, peer-reviewed publications. The
database's interdisciplinary content and features, such as citation analysis,
further enhance its suitability for researchers seeking a comprehensive and
well-rounded understanding of their chosen subject. The Scopus search string
used was as follows:

ALL
(voltage AND fluctuation AND microgrid AND island) AND PUBYEAR > 2017 AND
PUBYEAR < 2026.

The search
was conducted on May 25, 2025, and yielded 1641 results in the Scopus database.
As shown, the only restriction added to the search string concerned the
publication year, focusing on the most recent 8 years (according to the
researcher's criteria).

We employed
VOSviewer, a powerful bibliometric software, to conduct an in-depth analysis of
the identified articles. VOSviewer facilitates the creation and visualization
of bibliometric networks derived from journals, research, or other
publications. Among its versatile features is the capability to analyse
inputted data through term co-occurrence or author recurrence within the chosen
subject (VOSviewer - Visualizing scientific landscapes, s. f.). This
entails exporting metadata in CSV format and subsequently processing it in
VOSviewer, following the configuration illustrated in Figure 1.

Figure 1

VOSviewer
configuration to create the bibliographic map

This
configuration utilizes a synonyms file, meticulously crafted to account for
variations in terms that essentially signify the same concept. The specific
synonyms considered for this analysis are comprehensively outlined in Table 1.

Table 1

Keywords
synonymous for analysis in VOSviewer

Keyword

Replace
by

micro
grid

microgrid

islanded
micro-grid

islanded
microgrid

islanded
microgrids

islanded
microgrid

micro-grid

microgrid

micro-grids

microgrid

microgrid
(mg)

microgrid

microgrids
(mgs)

microgrids

multi-microgrids

microgrids

small-signal
stability

small
signal stability

power
systems

power
system

The
acquired outcomes were systematically categorized into clusters and visually
represented in a network graph. In this graphical representation, the observer
can discern the frequency of occurrence of each keyword relative to the size of
its indicator. Furthermore, an analysis of results by publication year allowed
for the assessment of the currency of each term. As depicted in Figure 2, terms such as microgrid, energy
storage, energy management, charging, optimization, and electric inverters
exhibited the highest occurrence frequencies. Building on these findings, the
next step was to select a term of interest. In this instance, the term
"inverter" was chosen, revealing its associations with terms like
microgrid and electric inverters, as illustrated in Figure 3.

Figure 2

Cluster
chart based on the articles found

Figure 3

Cluster
resulting from the selection of the term inverter

Subsequently,
definitive filtering was executed using the terms recommended by VOSviewer,
specifically the inverter microgrid. This refined curation identified 19
articles directly pertinent to the research topic.

Descriptive
Analysis of Literature

A
systematic evaluation of articles was conducted to construct a comprehensive
descriptive literature review, encompassing key parameters such as field, year
of publication, journal or conference, authors, and language. This multifaceted
analysis aimed to provide a nuanced understanding of the literature landscape,
facilitating a thorough exploration of trends and contributors.

Publication
Year

As
indicated earlier, the accepted publication years for this work span from 2018
to 2025. Figure 4 illustrates a discernible trend,
highlighting the current and sustained interest in this research topic.

Figure 4

Line
diagram by year of publication

Classification
by Journal or Conference

Of the 28
analyzed articles, only two publication types were identified: journal articles
and conference papers, as shown in Figure 5. However, an in-depth examination
of Table 2 reveals no clear preference for any
specific journal or conference. Instead, the publications display a relatively
even distribution, with most sources contributing only one or, at most, two
articles each.

Table 2

Journals
or conferences featuring the analyzed articles

Name of the journal or conference

Articles

Appl.
Energy

1

Association
for Computing Machinery

1

Dianli
Xitong Zidonghue/Automation of Electric Power Systems

1

Dianwang
Jishu/Power System Technology

1

EEA
Electrotec. Electron. Autom.

1

Electr.
Power Comp. Syst.

1

Electronics
(Switzerland)

1

Energy
Reports

1

e-Prime –
Advances in Electrical Engineering.

1

Frontiers
in Energy Research

1

IEEE Access

1

IEEE Trans
Electromagn Compat

1

IEEE Trans
Power Electron

1

IEEJ Trans.
Electr. Electron. Eng

1

IEEJ Trans.
Power Energy

1

Institute
of Electrical and Electronics Engineers Inc.

5

Institute
of Physics Publishing

1

Iraqi. J.
Electr. Electron. Eng.

1

Microelectronics
Reliability

1

Springer
Science and Business Media Deutschland GmbH

1

Zhongguo
Dianji Gongcheng Xuebao

1

Energies

3

Total

28

Figure 5

Bar chart
showing the type of publication

It is
noteworthy that the primary source appears to be IEEE, with five articles
published across its journals and conferences, followed by MDPI, which
contributes two articles from the Energies journal.

Author
Characterization

The
examination of authorship reveals a pattern consistent with the observations
above. Among the analyzed articles, only one notable instance of prolific
authorship is identified: Pilehvar, M.S., and Mirafzal, B. each have three
publications, while all other authors contribute only one article each.

This
suggests a dichotomy in the authors' engagement with the subject matter—either
they are relatively new entrants exploring this research domain, or they have
selectively opted to diverge from it for unspecified reasons. The comprehensive
list of authors is detailed in Table 3.

Table 3

Relationship
between authors and the number of publications

Authors

Articles

Anttila, S.; Döhler, J.S.; Oliveira, J.G.; Boström, C.

1

Arou, A.J.; Tsuji, T.

1

Attou, N.; Zidi, S.-A.; Hadjeri, S.; Khatir,
M.

1

Cheng, Z.; Lin, H.; Liang, W.; Zhu, L.;
Zheng, Y.

1

Fani, B.; Shahgholian, G.; Haes Alhelou, H.;
Siano, P.

1

Hmad, J.; Houari, A.; Bouzid, A.E.M.; Saim,
A.; Trabelsi, H.

1

Hsu, C.-T.; Cheng, T.-J.; Huang, H.-M.; Lee,
Y.-D.; Chang, Y.-R.; Jiang, J.-L.

1

Hu, C.; Shi, X.; Luo, S.; Zhou, J.; Ma, R.;
Fan, H.

1

Ide, T.; Hirase, Y.; Yoshimura, E.; Umezu, Y.;
Bando, S.; Sugimoto, K.

2

Jasim, A.M.; Jasim, B.H.

1

Joshal, K.S.; Gupta, N.

1

Khan, S.; Iqubal, N.; Prasad, S.

1

Luo, S.; Peng, K.; Hu, C.; Shi, X.; Lu, H.

1

Matthee, A.; Moonen, N.; Sulaeman, I.;
Leferink, F.

1

Pahasa, J.; Potejana, P.; Ngamroo, I.

1

Pilehvar, M.S.; Mirafzal, B.

3

Samanta, S.; Datta, S.; Das, S.; Roy, B.K.;
Ganguly, A.

1

Shi, H.; zhang, J.; Zhou, J.; Li, Y.; Jiang,
Z.

1

Shi, Y.; Liu, Z.; Liu, J.; Wang, W.; An, R.

1

Singh, S.K.; Rawal, M.; Rawat, M.S.; Gupta,
T.N.

1

Sun, G.; Li, Y.; Jin, W.; Gao, Y.

1

Wang, H.; Wang, M.; Cheng, Q.; Lv, S.; Ji, X.

1

Xia, F.; Xia, Z.; Di, Z.; Yang, Z.; Huang,
X.; Song, L.

1

Zhang, C.; Xu, J.; Qing, H.; Chai, X.; Wang,
X.

1

Zheng, F.; Lin, X.; Lin, Y.; Zhang, Y.;
Zhang, Y.

1

Total

28

Language
Classification

It is
essential to acknowledge that the search was conducted exclusively in English,
as all identified articles included English versions of their abstracts and
keywords. Considering this, Table 4 provides a breakdown of the
exclusion criteria, noting that three articles were excluded because they were
written in Chinese.

The
selection of the final set of articles for this review was guided by a series
of inclusion and exclusion criteria designed to ensure thematic relevance,
methodological rigor, and accessibility of information. Given the technical
nature of the topic, focused specifically on voltage and frequency fluctuation
mitigation in inverter-based isolated microgrids, only peer-reviewed journal
articles and conference proceedings were considered. These documents were
required to provide concrete technical contributions, such as proposed control
architectures, stability enhancement techniques, or simulation/experimental
validation in isolated or mixed-inertia contexts.

Studies
addressing generic smart grid developments, policy frameworks, or
grid-connected systems, but not those tackling the challenges specific to
islanded operation, were excluded to maintain thematic coherence. In addition,
the language filter was intentionally set to English to ensure consistency in
terminology and technical interpretation, and to facilitate citation tracking
and quality assessment using established bibliometric tools.

Articles
for which only the abstract or partial content was accessible were excluded,
regardless of relevance, due to the inability to validate methodological
details. Furthermore, duplicate entries and documents whose focus was not
aligned with the key research questions, such as those emphasizing grid
protection, economic optimization, or load forecasting without explicit
treatment of dynamic control, were also omitted.

As shown in
Table 4, these criteria led to the
exclusion of six documents from the refined set of 28 initially identified
through keyword mapping with VOSviewer. The remaining 22 articles constitute a
curated body of evidence that directly addresses the core objective of this
review: evaluating advanced control strategies for voltage and frequency
stability in low-inertia, inverter-dominated, and islanded microgrids.

Table 4

Item exclusion report

Art. Num.

Ref.

Title

Reason for
exclusion

1

(Sun
et al., 2019)

A Comprehensive Power Quality Control Strategy
for Microgrid Based on Three-phase Multi-function Inverters

Excluded by language (Chinese)

2

(Attou
et al., 2023)

A Control Design of Grid-Forming and
Grid-Following Inverters with a Seamless Transition in Microgrid

Not excluded

3

(Y.
Shi et al., 2025)

A Decentralized Secondary Voltage Control Method
with Unbalance Voltage Compensation Capability for Parallel Inverters in
Islanded Microgrids

Not excluded

4

(H.
Shi et al., 2021)

A Novel H∞ Robust Control Strategy for Voltage
Source Inverter in Microgrid

Not excluded

5

(Hmad
et al., 2023)

A Review on Mode Transition Strategies between
Grid-Connected and Stand-alone Operation of Voltage Source Inverters-Based
Microgrids

Not excluded

6

(Arou
& Tsuji, 2024)

Coordinated Q-V/P-f Control Strategy Using
Virtual Power Factor for Autonomous AC Microgrid with PV Smart Inverters

Not excluded

7

(Joshal
& Gupta, 2023)

Decentralized Control for Multiple
Network-Forming Inverters in a Solar PV-BESS Based Stand-alone Microgrid
System

Not excluded

8

(Hu
et al., 2021)

Decentralized Dynamic Disturbance Compensation
Control Strategy for Multiple Parallel Inverters in Microgrid

Excluded by language (Chinese)

9

(Luo
et al., 2022)

Decentralized Dynamic Disturbance Compensation
Control Strategy for Multiple Parallel Inverters in Microgrid

Exclude due to lack of access

10

(Samanta
et al., 2021)

Design and FPGA Implementation of an Islanding
Detection cum Re-synchronization Technique for a Grid Connected Inverter in a
DC Microgrid

Not excluded

11

(Zheng
et al., 2019)

Design of a novel hybrid control strategy for es
grid-connected inverter for smooth microgrid transition operation

Not excluded

12

(Pilehvar
& Mirafzal, 2020a)

Energy-storage fed smart inverters for mitigation
of voltage fluctuations in islanded microgrids

Not excluded

13

(Pilehvar
& Mirafzal, 2020b)

Frequency and voltage support by battery‐fed
smart inverters in mixed‐inertia microgrids

Not excluded

14

(Anttila
et al., 2022)

Grid Forming Inverters: A Review of the State of
the Art of Key Elements for Microgrid Operation

Not excluded

15

(Jasim
& Jasim, 2022)

Grid-Forming and Grid-Following Based Microgrid
Inverters Control

Not excluded

16

(S.
K. Singh et al., 2021)

Hybrid islanding detection technique for inverter
based microgrid

Not excluded

17

(Ide
et al., 2025a)

Identifying Power Oscillation Factors and
Improving Stability in Microgrids Comprised of Inverter-Based Resources

Excluded by language (Japanese)

18

(Fani
et al., 2022)

Inverter-based islanded microgrid: A review on
technologies and control

Not excluded

19

(Ide
et al., 2025b)

Investigating and addressing synchronous
instabilities in inverter-based resources within microgrids

Not excluded

20

(Wang
et al., 2022)

Modelling simulation and inverter control
strategy research of microgrid in grid-connected and island mode

Not excluded

21

(Pahasa
et al., 2021)

Multi-objective decentralized model predictive
control for inverter air conditioner control of indoor temperature and
frequency stabilization in microgrid

Not excluded

22

(Hsu
et al., 2019)

Over frequency control of photovoltaic inverters
in an island microgrid

Not excluded

23

(Pilehvar
& Mirafzal, 2020c)

PV-fed smart inverters for mitigation of voltage
and frequency fluctuations in islanded microgrids

Not excluded

24

(Cheng
et al., 2022)

Research on Adaptive Control Strategy of
Microgrid Inverter based on Virtual Synchronous Generator

Not excluded

25

(Xia
et al., 2018)

Resistance capacitive inverter allocation method
based on fast reactive support based on Microgrid

Not excluded

26

(Zhang
et al., 2022)

Seamless Transferring Control Strategy for
Master-Slave Microgrid Inverter in Whole Off-grid Process

Excluded by language (Chinese)

27

(Matthee
et al., 2024)

Transient Response of Generator- and
Inverter-Based Microgrids to Rapid Load Changes

Not excluded

28

(Khan
et al., 2022)

Voltage Regulator Using Sliding Mode Controller
for Inverter Based Islanded Microgrid

Excluded due to lack of access

Isolated
Microgrids

Microgrids are composed of distributed generation sources, energy
storage systems, electrical loads, monitoring devices, and protection devices
that can operate in either grid-connected or isolated mode (Wang et al., 2022).
Microgrids represent a crucial approach for ensuring the sustainability of
electricity supply, particularly in rural areas where extending the main grid
is not feasible, or in completely isolated areas such as island territories
(Fani et al., 2022; Ide et al., 2025b).

Currently, inverter-based microgrids are gaining prominence because they
possess self-healing or islanding capabilities and demonstrate enhanced
operational stability (Fani et al., 2022). Two distinct microgrid cases are
shown in Figures 6 and 7. Figure 6 shows a grid-connected DC
microgrid, while Figure 7 depicts a typical inverter-based
microgrid scheme.

Figure 6

Structure
of a DC microgrid connected to the network

Source: control scheme
taken from S. Samanta et al., 2021.

Figure 7

Typical
schematic of an inverter-based microgrid

Source: microgrid scheme
take from Fani, et al., 2022.

The
benefits of microgrids include security of supply, utilization of renewable
energy with on-demand storage systems, and reduced operating costs.
Additionally, power fluctuations can be mitigated through energy storage
(Samanta et al., 2021; H. Shi et al., 2021; Zheng et al., 2019). Figure 8 illustrates a more dynamic
microgrid scheme, encompassing all its components—generation, storage, and
energy consumption. In microgrids with air-conditioning inverters, regulating
power consumption reduces frequency fluctuations.

Figure 8

Microgrid
scheme with a parallel inverter system

Source: case of study
taken from Shi, et al., 2025.

In Hmad et al. (2023), the microgrid
is analyzed from a control-system perspective, considering transition
strategies between grid-connected and isolated operation modes. Similarly,
Attou et al. (2023) present a control scheme for the microgrid under study,
which incorporates network formation and monitoring conditions, as illustrated
in Figure 9.

Figure 9

Control
system of the PV microgrid

Source: microgrid type
network formation taken from Attou, et al., 2023.

Mixed Inertia
Microgrids

Among the
various microgrid configurations, the most used today is the mixed-inertia
configuration. This configuration consists of a microgrid generator group that
integrates two or more types of energy sources—most frequently diesel
generation, often combined with photovoltaic or wind energy (Pilehvar &
Mirafzal, 2020a, 2020b, 2020c). However, this type of microgrid presents
drawbacks in terms of energy stability due to the low inertia of
non-conventional renewable energy sources, leading to an imbalance between
generation and consumption (Pilehvar & Mirafzal, 2020a, 2020b). This occurs
only in the isolated microgrid operating mode, since in a configuration
connected to the main grid, fluctuations are compensated by the public grid AC
bus's voltage and frequency regulation (Pilehvar & Mirafzal, 2020a).

Among the
most common ways to mitigate these imbalances are the use of diesel generators
for voltage and frequency regulation (Pilehvar & Mirafzal, 2020b) and the
employment of energy storage systems to inject or absorb reactive power to the
grid, thereby improving stability quickly during transients (Pilehvar &
Mirafzal, 2020c).

This type
of microgrid is illustrated in Figure 10, which shows diesel generation,
photovoltaic generation, a grid connection switch, and load.

Figure 10

Schematic
of the mixed-inertia microgrid

Source: microgrid scheme
consulted in Pilehvar y Mirafzal, 2020c.

Isolation
Detection Methods in Microgrids

Isolation
detection in microgrids is a significant challenge for ensuring operational
stability. These detection methods are generally categorized into local and
remote (Anttila et al., 2022).

Local
methods, as the name suggests, are physically tied to the microgrid and are
further divided into active, passive, and hybrid (Anttila et al., 2022).

Active
methods involve injecting harmonics or disturbances into the grid to detect
isolation, thereby reducing isolation detection time and avoiding deterioration
of power quality (Samanta et al., 2021). Among the most common active
techniques are impedance measurement, active frequency shunt, sliding mode
frequency shift, Sandia voltage shift, and Sandia frequency shift (Anttila et
al., 2022).

Passive
methods rely on measuring parameters such as voltage, current, impedance,
power, and frequency (Matthee et al., 2024; Samanta et al., 2021). Their main
drawbacks are the isolation detection time and the presence of a non-detection
zone (Samanta et al., 2021), although they do not affect power quality (Samanta
et al., 2021). Passive methods include ROCOP (rate of change of output power),
ROCOF (rate of change of output frequency), and the phase hopping detection
method (Anttila et al., 2022).

In S. K.
Singh et al. (2021), the passive ROCOF and VU (voltage unbalance) methods are
discussed. For the ROCOF method, illustrated in Figure 11, a detection time of 24 ms was
obtained. For the VU method detailed in Figure 12, the detection time was 53 ms. The
same study also proposes a passive-hybrid method combining the union of ROCOF
and VU methods. In this method, the three-phase voltage is controlled in the
DG, and VU is calculated. Then, ROCOF determines whether disconnection is
required. This approach achieved a detection time of 22 ms and is detailed in Figure 13.

Figure 11

Block
diagram of the ROCOF method for isolation detection

Source: ROCOF diagram
published in Singh et al., 2021.

Figure 12

Block
diagram of the VU method for isolation detection

Source: block diagram
presented in Singh, et al., 2021.

Figure 13

Block diagram of the passive-hybrid method
combining ROCOF and VU methods for isolation

Source: block diagram of
ROCOF taken from Singh, et al., 2021.

Hybrid
methods integrate active and passive approaches to compensate for the
limitations of each. For example, the voltage unbalance and frequency set point
method combines voltage displacement and reactive power (Anttila et al., 2022).

Unlike
local methods, remote methods have their origin in their utility (Anttila et
al., 2022) and are based on utility communication, power line carrier
communication, supervisory control, and data acquisition techniques (Anttila et
al., 2022). Intelligent methods based on decision trees, artificial neural
networks, fuzzy logic, support vector machines, etc., are also considered
(Samanta et al., 2021).

In this
context, the resynchronization of the system during the transition from on-grid
to off-grid plays a crucial role, allowing voltage or frequency variations to
be minimized using methods such as the MPPT analyzed in Jasim and Jasim (2022).

Control
Strategies for the Stability of Isolated Microgrids

In recent years, several control strategies have been developed to
mitigate various fluctuations in microgrids, while accounting for challenges
such as isolation detection and stability during state changes. Existing
control strategies are known to work satisfactorily only for one of the
microgrid modes: either connected to the grid or operating in isolation (Wang
et al., 2022).

Mitigation Strategies for Voltage Fluctuations
in Isolated Microgrids

Voltage is one of the most unstable parameters
in isolated microgrids, due to typical events that alter system operation.

Among the works reviewed for this literature
review, one proposes the H∞ method, which, despite its mathematical complexity,
focuses on controlling cross-coupled multivariate systems (H. Shi et al.,
2021). It involves adding an adaptive virtual impedance group to mitigate the
voltage deviation caused by load variations. This method is applied to the
voltage-source inverter and improves power quality (H. Shi et al., 2021).

Pilehvar and Mirafzal (2020a) discuss modifying
the conventional control scheme of the battery energy storage system to enhance
the dynamic performance of the microgrid. In the BESS, a piecewise linear
elliptic droop PLE is employed to improve the voltage profile by injecting/absorbing
reactive power during transients. In this method, the BESS becomes a smart
inverter. The results of this method are shown in Figure 14.

Figure 14

Comparison of voltage versus system
dynamic response for linear and PLE drops at the AC bus

Source:
result of voltage published in Pilehvar y Mirafzal, 2020a.

On the other hand, Xia et al. (2018) discuss a
fast reactive power support RC inverter method and its parallel power
allocation method. It introduces a virtual complex impedance of resistance and
capacitance in the inverter output current feedback. This method provides rapid
reactive power support at the common connection point, stabilizing the voltage
and suppressing resonance between the impedances.

Finally, Luo et al. (2022) propose a dynamic
compensation control strategy based on the generator's residual robustness,
thereby compensating for voltage variations.

Frequency Variation Mitigation Strategies in
Isolated Microgrids

Frequency is another fundamental parameter of
microgrids, as it helps to understand the behaviour of electrical signals.

Among the papers considered for this review,
two methods were specifically developed to stabilize the frequency in isolated
microgrids.

Hsu et al. (2019) analyse the impact of power
variation in a photovoltaic power plant on the frequency response of an
isolated microgrid with photovoltaic power and diesel thermal generation. A
comparison of the response to frequency variation with and without inverter
over-frequency compensation is detailed. This method improves the reliability
of the microgrid (Hsu et al., 2019).

The method proposed by Cheng et al. (2022), in
contrast, adjusts the synchronous virtual generator's frequency using an
adaptive droop coefficient that varies with system load, thereby compensating
for system frequency fluctuations. Figure 15 shows the frequency response curve with the proposed method.

Finally, Joshal & Gupta (2023) present the
PLL (phase-locked loop) method, which involves the connection and disconnection
of the DER system during microgrid operation.

Figure 15

Frequency
response curve

Source:
Results reported by Cheng, et al., 2022.

Proposed Strategies to Mitigate Voltage and
Frequency Variations Jointly

Among the articles reviewed, four different
methods were identified for stabilizing voltage and frequency simultaneously,
with the objective of increasing system reliability.

One of the strategies is a hybrid energy
storage control strategy based on the IEEE 1676 standard (Zheng et al., 2019).
It consists of a predictive controller with a two-degree-of-freedom algorithm
and modified droop control, enabling a smooth transition between grid-connected
and isolated modes while maintaining the energy storage connection. Its
operation is detailed in the diagram in Figure 16. This allows the voltage and frequency to be quickly restored. The
results are presented as bar diagrams in Figure 17.

Figure 16

Flow diagram of the predictive controller

Source:
control strategy taken from Zheng, et al., 2019.

Figure 17

Performance comparison of the method of control

Source:
statistics extracted from Zheng, et al., 2019.

The same PLE method, as explained above for
voltage stabilization (Pilehvar & Mirafzal, 2020a), is employed in Pilehvar
and Mirafzal (2020b), but with an approach that mitigates both frequency and
voltage variations simultaneously. In this case, the presence of a deadband in
the system is considered, which affects abrupt changes in active power, as
shown in Figure 18. The PLE method, applied during staggered variations in load demand, is
also analyzed, with the results shown in Figure 19. Finally, the efficiency of the PLE method during the transition
between grid-connected and stand-alone mode is examined, as illustrated in Figure 20.

Figure 18

Frequency (a) and voltage (b)
variations in the presence and absence of the deadband in linear droop

Source:
results published by Pilehvar y Mirafzal, 2022b.

Figure 19

Comparison of linear droop and PLE performance
in dynamic response of the system

Source:
curves reported by Pilehvar y Mirafzal, 2020b.

Figure 20

Comparison of linear droop and PLE
performance in enhanced dynamic response during transients

Source:
results taken from Pilehvar y Mirafzal, 2020b.

The virtual adaptive control loop method
involves modifying the virtual impedance value adaptively based on the output
conditions (Wang et al., 2022). In the active power control loop, the frequency
signal is extracted from the phase-locked loop and converted into a power
feedback variable via a signal transformation, thereby participating in the
power control process and enhancing control accuracy. Figure 21 shows the block diagram of the control strategy described. Voltage
changes are shown in Figure 22, and frequency changes in Figure 23.

Figure 21

Block diagram of the control strategy proposed

Source:
schematic taken from Wang, et al., 2022.

Figure 22

Voltage changes at typical nodes before and
after the events explained

Source:
results published by Wang, et al., 2022.

Figure 23

Frequency changes at typical nodes, considering
the events mentioned

Source:
statistics reported by Wang, et al., 2022.

Finally, Pilehvar and Mirafzal (2020c) propose
a traditional PV generation controller to improve the dynamics of isolated
microgrids by reducing voltage and frequency variations. This method implements
a piecewise adaptive droop curve in PV units to achieve faster supply-demand
balance during transients. Reactive power is also injected/absorbed to improve
voltage and frequency, as in Pilehvar and Mirafzal (2020a). The comparison of
curves with and without the APD method is shown in Figure 24.

Figure 24

Frequency (a) and voltage (b) stability curves
resulting from the APD method analyzed

Source:
curves taken from Pilehvar y Mirafzal, 2020c.

Conclusions

This review examined
28 recent studies addressing voltage and frequency fluctuations in isolated
microgrids, with a particular focus on control strategies involving smart
inverters, energy storage systems, and advanced regulation techniques. The
findings highlight that mixed inertia microgrids—those combining conventional
and renewable generation—pose the most significant operational challenges due
to the limited inertia of renewable sources. In these contexts, rapid and
accurate isolation detection is essential to prevent instability during mode
transitions.

Although the reviewed
methods demonstrate promising results, they vary considerably in complexity and
implementation requirements. Techniques such as adaptive droop control, virtual
impedance tuning, and predictive optimization algorithms have shown strong
potential to enhance the dynamic performance of low-inertia systems. However,
their effectiveness is closely tied to the specific configuration and operating
conditions of the microgrid.

The growing number of
publications over the last decade underscores the increasing relevance of this
research field. Nonetheless, the dispersion of contributions across journals
and authors suggests the absence of a consolidated research community or standardized
evaluation benchmarks.

This dispersion also
points to a lack of consensus on optimal design practices, particularly
regarding trade-offs among control complexity, communication requirements, and
real-time computational burden. While advanced control schemes often
demonstrate superior performance in simulations, their real-world applicability
may be constrained by hardware limitations or by the lack of interoperability
between devices from different manufacturers. Therefore, future studies should
not only assess technical performance but also address scalability,
cost-effectiveness, and ease of integration with existing infrastructures.

Furthermore, this
review highlights a methodological gap in the comparative evaluation of control
strategies, as most studies use different testbeds, metrics, or simulation
environments. This limits the generalizability of results and hinders the
establishment of standardized benchmarks. Coordinated efforts to develop common
microgrid test cases that incorporate representative disturbances, realistic
load profiles, and hybrid generation mixes would significantly improve the
comparability and replicability of future studies.

From a system design
perspective, there is an increasing need to move beyond isolated solutions and
explore integrated control layers that combine frequency regulation, voltage
support, energy storage coordination, and fault management in a unified framework.
Hybrid approaches that synergize predictive, adaptive, and data-driven
techniques (such as neural networks or fuzzy logic) may offer enhanced
resilience against stochastic events such as sudden load changes or renewable
output variability. However, such approaches must be critically evaluated under
both normal and abnormal operating conditions to assess their robustness.

Future work should
prioritize comparative validation of control strategies under unified test
conditions and promote the development of modular, scalable solutions adaptable
to diverse microgrid architectures. In addition, there is a need to further
explore hybrid approaches that integrate control, storage, and communication
layers to improve system resilience in the face of stochastic fluctuations.

Acknowledgements and
Declarations

This work
was supported by the Laboratorio de Micro-Red, Faculty of Engineering at the
Universidad de Cuenca, whose infrastructure and technical resources greatly
contributed to the analysis and validation of the findings presented in this
study.

According
to the CRediT taxonomy, both authors contributed equally to the conception,
development, and writing of the manuscript. Their collaboration included
defining research objectives, conducting data analysis, interpreting results,
and preparing the manuscript.

The authors
declare that, in the preparation of this article, artificial intelligence tools
(ChatGPT, GPT-5 version) were employed exclusively to improve the linguistic
quality and fluency of the English text. All ideas, methodological
developments, data interpretation, and scientific conclusions are the original
intellectual work of the authors.

References

Anttila, S.,
Döhler, J. S., Oliveira, J. G., & Boström, C. (2022). Grid Forming
Inverters: A Review of the State of the Art of Key Elements for Microgrid
Operation. Energies, 15(15). https://doi.org/10.3390/en15155517

Arou, A. J., &
Tsuji, T. (2024). Coordinated Q-V/P-f Control Strategy Using Virtual
Power Factor for Autonomous AC Microgrid with PV Smart Inverters. IEEJ
Transactions on Electrical and Electronic Engineering, 19(3), 327-341. https://doi.org/10.1002/tee.23980

Attou, N., Zidi,
S.-A., Hadjeri, S., & Khatir, M. (2023). A Control Design of
Grid-Forming and Grid-Following Inverters with a Seamless Transition in
Microgrid. EEA - Electrotehnica, Electronica, Automatica, 71(2), 10-18. https://doi.org/10.46904/eea.23.71.2.1108002

Bassey, O., &
Butler-Purry, K. L. (2020). Black start restoration of islanded
droop-controlled microgrids. Energies, 13(22). https://doi.org/10.3390/en13225996

Bassey, O., &
Butler-Purry, K. L. (2022). Islanded Microgrid Restoration Studies with
Graph-Based Analysis. Energies, 15(19). https://doi.org/10.3390/en15196979

Cheng, Z., Lin, H.,
Liang, W., Zhu, L., & Zheng, Y. (2022). Research on Adaptive Control
Strategy of Microgrid Inverter based on Virtual Synchronous Generator. ACM
Int. Conf. Proc. Ser., 1027-1031. https://doi.org/10.1145/3558819.3565462

Elmetwaly, A. H.,
Eldesouky, A. A., & Sallam, A. A. (2020). An Adaptive D-FACTS for
Power Quality Enhancement in an Isolated Microgrid. IEEE Access, 8, 57923-57942.
https://doi.org/10.1109/ACCESS.2020.2981444

Fani, B.,
Shahgholian, G., Haes Alhelou, H., & Siano, P. (2022). Inverter-based
islanded microgrid: A review on technologies and control. E-Prime - Advances in
Electrical Engineering, Electronics and Energy, 2. https://doi.org/10.1016/j.prime.2022.100068

Hmad, J., Houari,
A., Bouzid, A. E. M., Saim, A., & Trabelsi, H. (2023). A Review on Mode
Transition Strategies between Grid-Connected and Stand-alone Operation of
Voltage Source Inverters-Based Microgrids. Energies, 16(13). https://doi.org/10.3390/en16135062

Hsu, C.-T., Cheng,
T.-J., Huang, H.-M., Lee, Y.-D., Chang, Y.-R., & Jiang, J.-L. (2019). Over
frequency control of photovoltaic inverters in an island microgrid.
Microelectronics Reliability, 92, 42-54. https://doi.org/10.1016/j.microrel.2018.11.011

Hu, C., Shi, X.,
Luo, S., Zhou, J., Ma, R., & Fan, H. (2021). Decentralized Dynamic
Disturbance Compensation Control Strategy for Multiple Parallel Inverters in Microgrid.
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of
Electrical Engineering, 41(13), 4425-4438. https://doi.org/10.13334/j.0258-8013.pcsee.201258

Ide, T., Hirase, Y.,
Yoshimura, E., Umezu, Y., Bando, S., & Sugimoto, K. (2025a). Identifying Power
Oscillation Factors and Improving Stability in Microgrids Comprised of
Inverter-Based Resources. IEEJ Transactions on Power and Energy, 145(3),
299-310. https://doi.org/10.1541/ieejpes.145.299

Ide, T., Hirase, Y.,
Yoshimura, E., Umezu, Y., Bando, S., & Sugimoto, K. (2025b). Investigating and
addressing synchronous instabilities in inverter-based resources within
microgrids. Applied Energy, 377. https://doi.org/10.1016/j.apenergy.2024.124379

Jasim, A. M., &
Jasim, B. H. (2022). Grid-Forming and Grid-Following Based Microgrid
Inverters Control. Iraqi Journal for Electrical and Electronic Engineering,
18(1), 111-131. https://doi.org/10.37917/ijeee.18.1.13

Joshal, K. S.,
& Gupta, N. (2023). Decentralized Control for Multiple
Network-Forming Inverters in a Solar PV-BESS Based Stand-alone Microgrid
System. Electric Power Components and Systems. https://doi.org/10.1080/15325008.2023.2283860

Khan, S., Iqubal,
N., & Prasad, S. (2022). Voltage Regulator Using Sliding Mode Controller
for Inverter Based Islanded Microgrid. En Kumar J., Tripathy M., & Jena P. (Eds.), Lect.
Notes Electr. Eng. (Vol. 870, pp. 141-152). Springer Science and Business Media
Deutschland GmbH. https://doi.org/10.1007/978-981-19-0193-5_12

Kokila Vani, C.,
Sarangapani, E., & Kumaresan, R. (2021). Mitigation of Frequency
Variation Through Voltage Control in Islanded Microgrid. En G. Kumaresan,
N. S. Shanmugam, & V. Dhinakaran (Eds.), Advances in Materials Research
(Vol. 5, pp. 953-961). Springer Nature Singapore. https://doi.org/10.1007/978-981-15-8319-3_95

Luo, S., Peng, K.,
Hu, C., Shi, X., & Lu, H. (2022). Decentralized Dynamic Disturbance
Compensation Control Strategy for Multiple Parallel Inverters in Microgrid.
IEEE Ind. Electron. Soc. Annu. On-Line Conf., ONCON. 1st IEEE Industrial
Electronics Society Annual On-Line Conference, ONCON 2022. https://doi.org/10.1109/ONCON56984.2022.10126896

Matthee, A.,
Moonen, N., Sulaeman, I., & Leferink, F. (2024). Transient Response
of Generator- and Inverter-Based Microgrids to Rapid Load Changes. IEEE
Transactions on Electromagnetic Compatibility, 66(5), 1646-1654. https://doi.org/10.1109/TEMC.2024.3435732

Mohamed Salim, O.,
& El-Sayed Salem Aboraya, A. (2024). Power quality enhancement of
unbalanced Distributed-Resources based on triple-loop compensation. Ain
Shams Engineering Journal, 15(2), 102454. https://doi.org/10.1016/j.asej.2023.102454

Ochoa, D., &
Martinez, S. (2021). Analytical Approach to Understanding the Effects of
Implementing Fast-Frequency Response by Wind Turbines on the Short-Term
Operation of Power Systems. Energies, 14(12), 3660. https://doi.org/10.3390/en14123660

Pahasa, J., Potejana, P.,
& Ngamroo, I. (2021). Multi-objective decentralized model predictive control
for inverter air conditioner control of indoor temperature and frequency
stabilization in microgrid. Energies, 14(21). https://doi.org/10.3390/en14216969

Pilehvar, M. S., &
Mirafzal, B. (2020a). Energy-storage fed smart inverters for mitigation of
voltage fluctuations in islanded microgrids. IEEE Electr. Power Energy
Conf., EPEC. 2020 IEEE Electric Power and Energy Conference, EPEC 2020. https://doi.org/10.1109/EPEC48502.2020.9319911

Pilehvar, M. S., &
Mirafzal, B. (2020b). Frequency and voltage supports by battery‐fed smart
inverters in mixed‐inertia microgrids. Electronics (Switzerland), 9(11),
1-14. https://doi.org/10.3390/electronics9111755

Pilehvar, M. S.,
& Mirafzal, B. (2020c). PV-fed smart inverters for mitigation of
voltage and frequency fluctuations in islanded microgrids. Proc. - Int.
Conf. Smart Grids Energy Syst., SGES, 807-812. https://doi.org/10.1109/SGES51519.2020.00149

PRISMA-P Group,
Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M.,
Shekelle, P., & Stewart, L. A. (2015). Preferred reporting items for
systematic review and meta-analysis protocols (PRISMA-P) 2015 statement.
Systematic Reviews, 4(1), 1. https://doi.org/10.1186/2046-4053-4-1

Samanta, S., Datta,
S., Das, S., Roy, B. K., & Ganguly, A. (2021). Design and FPGA
Implementation of an Islanding Detection cum Re-synchronisation Technique for a
Grid Connected Inverter in a DC Microgrid. Int. Conf. Energy, Power
Environ.: Towards Clean Energy Technol., ICEPE. 3rd International Conference on
Energy, Power and Environment: Towards Clean Energy Technologies, ICEPE 2020. https://doi.org/10.1109/ICEPE50861.2021.9404503

Shamseer, L.,
Moher, D., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P.,
Stewart, L. A., & the PRISMA-P Group. (2015). Preferred reporting
items for systematic review and meta-analysis protocols (PRISMA-P) 2015:
Elaboration and explanation. BMJ, 349(jan02 1), g7647-g7647. https://doi.org/10.1136/bmj.g7647

Shi, H., zhang, J.,
Zhou, J., Li, Y., & Jiang, Z. (2021). A Novel H∞ Robust Control
Strategy for Voltage Source Inverter in Microgrid. Frontiers in Energy
Research, 9. https://doi.org/10.3389/fenrg.2021.731432

Shi, Y., Liu, Z.,
Liu, J., Wang, W., & An, R. (2025). A Decentralized Secondary
Voltage Control Method with Unbalance Voltage Compensation Capability for
Parallel Inverters in Islanded Microgrids. IEEE Transactions on Power
Electronics. https://doi.org/10.1109/TPEL.2025.3556302

Singh, A. R., Ray,
P., Seshu Kumar, R., & Salkuti, S. R. (2023). Introduction to Power
Quality in Microgrids. En S. R. Salkuti, P. Ray, & A. R. Singh (Eds.),
Power Quality in Microgrids: Issues, Challenges and Mitigation Techniques (Vol.
1039, pp. 1-21). Springer Nature Singapore. https://doi.org/10.1007/978-981-99-2066-2_1

Singh, S. K.,
Rawal, M., Rawat, M. S., & Gupta, T. N. (2021). Hybrid islanding
detection technique for inverter based microgrid. Int. Conf. Emerg.
Technol., INCET. 2021 2nd International Conference for Emerging Technology,
INCET 2021. https://doi.org/10.1109/INCET51464.2021.9456307

Sun, G., Li, Y.,
Jin, W., & Gao, Y. (2019). A Comprehensive Power Quality Control
Strategy for Microgrid Based on Three-phase Multi-function Inverters.
Dianwang Jishu/Power System Technology, 43(4), 1211-1219. https://doi.org/10.13335/j.1000-3673.pst.2018.1765

VOSviewer—Visualizing
scientific landscapes. (s. f.). VOSviewer. Last access: July 5th, 2023
from  https://www.vosviewer.com/

Wang, H., Wang, M.,
Cheng, Q., Lv, S., & Ji, X. (2022). Modelling simulation and
inverter control strategy research of microgrid in grid-connected and island
mode. Energy Reports, 8, 206-218. https://doi.org/10.1016/j.egyr.2022.09.117

Xia, F., Xia, Z.,
Di, Z., Yang, Z., Huang, X., & Song, L. (2018). Resistance
capacitive inverter allocation method based on fast reactive support based on
Microgrid. IOP Conf. Ser. Earth Environ. Sci., 170(4). https://doi.org/10.1088/1755-1315/170/4/042149

Yuan, C., Xie, P.,
Yang, D., & Xiao, X. (2018). Transient stability analysis
of islanded AC microgrids with a significant share of virtual synchronous
generators. Energies, 11(1). https://doi.org/10.3390/en11010044

Zhang, C., Xu, J.,
Qing, H., Chai, X., & Wang, X. (2022). Seamless Transferring Control
Strategy for Master-Slave Microgrid Inverter in Whole Off-grid Process.
Dianli Xitong Zidonghua/Automation of Electric Power Systems, 46(23),
125-133. https://doi.org/10.7500/AEPS20210914002

Zheng, F., Lin, X.,
Lin, Y., Zhang, Y., & Zhang, Y. (2019). Design of a novel hybrid
control strategy for es grid-connected inverter for smooth microgrid transition
operation. IEEE Access, 7, 171950-171965. https://doi.org/10.1109/ACCESS.2019.2955713