https://doi.org/10.37815/rte.v37n1.1343
Original articles
Estrategi=
as
efectivas para mitigar fluctuaciones de tensión y frecuencia en microrredes
aisladas: Una revisión de literatura
Santiago
Arcos-EcheverrÃa
Danny
Ochoa-Correa
=
1Uni=
versidad
de Cuenca, Fac=
ultad de
IngenierÃa
2Uni=
versidad
de Cuenca, Fac=
ultad de
IngenierÃa, Departamento de IngenierÃa Eléctrica, Electrónica y
Telecomunicaciones, Cuenca, Ecuador
Sent:Â Â Â Â = Â 2025/06/22<= o:p>
Accepted:Â Â Â Â Â Â 2025/10=
/29
Published: Â Â Â Â Â 2025/12=
/15Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â =
Abstract
Territorial expansion has posed new
challenges for electrical systems, driving the need to electrify remote rur=
al
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—particula=
rly
during overloads or transitions between isolated and grid-connected modes. =
This
article presents a literature review focusing on strategies to mitigate the=
se
fluctuations, analyzing 28 recent publications. The findings highlight adap=
tive
controllers, smart inverter compensation, and the integration of energy sto=
rage
systems as dynamic support tools, showing a preference for solutions based =
on
power electronics and predictive control algorithms.
=
Keywords: r=
enewable
energy, energy storage systems, voltage fluctuations, frequency fluctuation=
s,
low-inertia systems.
Summary: Introductio=
n, Methodology, Descriptive Analysis of Literature, Isolated
Microgrids, Control Strategies for the Stability of Isolated Microgrid=
s, Conclusions. How to cite: Arcos-Echev=
errÃa,
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 desafÃos para los sistemas eléctricos, impulsando la nece=
sidad
de electrificar zonas rurales de difÃcil acceso y territorios insulares. E=
sta
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 cone=
ctado
a red. Este artÃculo presenta una revisión de literatura sobre estrategia=
s para
mitigar estas fluctuaciones, analizando 28 publicaciones recientes. Entre l=
os
enfoques identificados se destacan los controladores adaptativos, la
compensación mediante inversores inteligentes, y la incorporación de
almacenamiento energético como mecanismo de soporte dinámico, evidencián=
dose
una preferencia por soluciones basadas en electrónica de potencia y algori=
tmos
predictivos.
Introduction
I=
mplementing
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 th=
ese
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 dynamicall=
y control
the voltage at the alternating current (AC) node to maintain stability. To
address fluctuations in isolated microgrids, most solutions in the literatu=
re
modify the conventional inverter control scheme using various techniques to
mitigate short-term transients and prevent outages caused by random events.=
<= o:p>
F=
or
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 capa=
city
due to its analysis in an isolated microgrid adapted from the IEEE 13-node =
test
feeder.
<= o:p>
T=
o address
frequency fluctuations in photovoltaic units, Pilehvar and Mirafzal (2020c)
propose using an adaptive piecewise droop (APD) curve in inverters. In anot=
her
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.
<= o:p>
F=
urthermore,
energy storage systems used in renewable energy-based electrical systems, s=
uch
as wind and solar, play a crucial role in storing excess electricity and
providing system stability (Ochoa & Martinez, 2021).
<= o:p>
A=
nother
approach, the virtual synchronous generator, has been shown to enhance the
inertia and damping of inverter-based distributed generators, thereby impro=
ving
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, 202=
4).
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).
<= o:p>
T=
here 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-sequ=
ence
controller and a negative-sequence controller, yielding favourable results =
even
in the presence of time-varying loads.
<= o:p>
A=
nother
method analyzed involves implementing a frequency controller, which utilizes
the load's sensitivity to operating voltages to achieve load regulation (Ko=
kila
Vani et al., 2021). This method eliminates the need for additional
communication infrastructure by relying solely on local frequency and volta=
ge
for feedback.
<= o:p>
F=
or the
same purpose, an adaptive switched filter compensator (ASFC) with a PID
controller has been proposed by Elmetwaly et al. (2020) to improve the dyna=
mic
performance of the microgrid. The Grasshopper Optimization Algorithm (GOA) =
has
been applied to this controller to allow it to adapt and self-tune accordin=
g to
changes in system conditions.
<= o:p>
G=
iven 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 distribut=
ed
generation with low or virtually no mechanical inertia, making them inheren=
tly
more susceptible to voltage and frequency instabilities—particularly duri=
ng
load transients, mode transitions, or fault conditions. While numerous stud=
ies
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 ener=
gy
storage or virtual synchronous generators) or address either voltage or
frequency regulation separately, without offering an integrated analysis ac=
ross
multiple approaches.
<= o:p>
T=
his
literature review addresses that gap by identifying, classifying, and analy=
zing
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 researc=
hers
and practitioners seeking to enhance the dynamic performance of low-inertia
electrical systems.
<= o:p>
Meth=
odology
T=
he
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 a=
l.
(2015), which can be categorized into administrative information, introduct=
ion,
and methods.
O=
nce 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 journa=
ls
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 m=
ake
it a reliable source for high-quality, peer-reviewed publications. The
database's interdisciplinary content and features, such as citation analysi=
s,
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:
<= o:p>
A=
LL
(voltage AND fluctuation AND microgrid AND island) AND PUBYEAR > 2017 AND
PUBYEAR < 2026.
<= o:p>
T=
he search
was conducted on May 25, 2025, and yielded 1641 results in the Scopus datab=
ase.
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).
<= o:p>
W=
e employed
VOSviewer, a powerful bibliometric software, to conduct an in-depth analysi=
s of
the identified articles. VOSviewer facilitates the creation and visualizati=
on
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 ch=
osen
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.
<= o:p>
Figure 1
VOSviewer
configuration to create the bibliographic map
<=
span
style=3D'mso-spacerun:yes'>Â
<= o:p>
T=
his
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.
<= o:p>
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 |
<= o:p>
T=
he
acquired outcomes were systematically categorized into clusters and visually
represented in a network graph. In this graphical representation, the obser=
ver
can discern the frequency of occurrence of each keyword relative to the siz=
e of
its indicator. Furthermore, an analysis of results by publication year allo=
wed
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<=
/i>
exhibited the highest occurrence frequencies. Building on these findings, t=
he
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.
<= o:p>
Figure 2
Cluster
chart based on the articles found
Figure 3
Cluster
resulting from the selection of the term inverter
<= o:p>
S=
ubsequently,
definitive filtering was executed using the terms recommended by VOSviewer,
specifically the inverter microgrid. This refined curation identifie=
d 19
articles directly pertinent to the research topic.
<= o:p>
Desc=
riptive
Analysis of Literature
A
systematic evaluation of articles was conducted to construct a comprehensive
descriptive literature review, encompassing key parameters such as field, y=
ear
of publication, journal or conference, authors, and language. This multifac=
eted
analysis aimed to provide a nuanced understanding of the literature landsca=
pe,
facilitating a thorough exploration of trends and contributors.
<= o:p>
Publ=
ication
Year
As
indicated earlier, the accepted publication years for this work span from 2=
018
to 2025. Figure 4 illustrates a discernible t=
rend,
highlighting the current and sustained interest in this research topic.
<= o:p>
Figure 4
Line
diagram by year of publication
Clas=
sification
by Journal or Conference
O=
f the 28
analyzed articles, only two publication types were identified: journal arti=
cles
and conference papers, as shown in Figure 5. However, an in-depth exami=
nation
of Table 2 reveals no clear preference=
for any
specific journal or conference. Instead, the publications display a relativ=
ely
even distribution, with most sources contributing only one or, at most, two
articles each.
<= o:p>
Table 2
Journals
or conferences featuring the analyzed articles
|
Name of the journal or conference |
Articles |
|
Appl.
Energy |
1 |
|
Assoc=
iation
for Computing Machinery |
1 |
|
Dianli
Xitong Zidonghue/Automation of Electric Power Systems |
1 |
|
Dianw=
ang
Jishu/Power System Technology |
1 |
|
EEA
Electrotec. Electron. Autom. |
1 |
|
Elect=
r.
Power Comp. Syst. |
1 |
|
Elect=
ronics
(Switzerland) |
1 |
|
Energy
Reports |
1 |
|
e-Pri=
me –
Advances in Electrical Engineering. |
1 |
|
Front=
iers
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 |
|
Insti=
tute
of Electrical and Electronics Engineers Inc. |
5 |
|
Insti=
tute
of Physics Publishing |
1 |
|
Iraqi. J.
Electr. Electron. Eng. |
1 |
|
Micro=
electronics
Reliability |
1 |
|
Sprin=
ger
Science and Business Media Deutschland GmbH |
1 |
|
Zhong=
guo
Dianji Gongcheng Xuebao |
1 |
|
Energ=
ies |
3 |
|
Total |
28 |
<= o:p>
Figure =
5=
Bar chart
showing the type of publication
I=
t 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.
<= o:p>
Auth=
or
Characterization
T=
he
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.
<= o:p>
T=
his
suggests a dichotomy in the authors' engagement with the subject matter—e=
ither
they are relatively new entrants exploring this research domain, or they ha=
ve
selectively opted to diverge from it for unspecified reasons. The comprehen=
sive
list of authors is detailed in Table 3.
<= o:p>
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.; Khat=
ir,
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.; Sai=
m,
A.; Trabelsi, H. |
1 |
|
Hsu, C.-T.; Cheng, T.-J.; Huang, H.-M.; L=
ee,
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.; Jia=
ng,
Z. |
1 |
|
Shi, Y.; Liu, Z.; Liu, J.; Wang, W.; An, =
R. |
1 |
|
Singh, S.K.; Rawal, M.; Rawat, M.S.; Gupt=
a,
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.; Wa=
ng,
X. |
1 |
|
Zheng, F.; Lin, X.; Lin, Y.; Zhang, Y.;
Zhang, Y. |
1 |
|
Total |
28 |
<= o:p>
Lang=
uage
Classification
I=
t is
essential to acknowledge that the search was conducted exclusively in Engli=
sh,
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 w=
ere
written in Chinese.
<= o:p>
T=
he
selection of the final set of articles for this review was guided by a seri=
es
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 fluctuat=
ion
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 cont=
rol
architectures, stability enhancement techniques, or simulation/experimental
validation in isolated or mixed-inertia contexts.
<= o:p>
S=
tudies
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 additi=
on,
the language filter was intentionally set to English to ensure consistency =
in
terminology and technical interpretation, and to facilitate citation tracki=
ng
and quality assessment using established bibliometric tools.
<= o:p>
A=
rticles
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.
<= o:p>
A=
s 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 constitut=
e 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.
<= o:p>
Item exclusion report
|
Art. Num. |
Ref. |
Title |
Reason for
exclusion |
|
1 |
|
A Comprehensive Power Quality Control Strategy
for Microgrid Based on Three-phase Multi-function Inverters |
Excluded by language (Chinese) |
|
2 |
|
A Control Design of Grid-Forming and
Grid-Following Inverters with a Seamless Transition in Microgrid |
Not excluded |
|
3 |
|
A Decentralized Secondary Voltage Control Met=
hod
with Unbalance Voltage Compensation Capability for Parallel Inverters in
Islanded Microgrids |
Not excluded |
|
4 |
|
A Novel H∞ Robust Control Strategy for Volt=
age
Source Inverter in Microgrid |
Not excluded |
|
5 |
|
A Review on Mode Transition Strategies between
Grid-Connected and Stand-alone Operation of Voltage Source Inverters-Based
Microgrids |
Not excluded |
|
6 |
|
Coordinated Q-V/P-f Control Strategy Using Virtual Power Factor for Autonomous AC Microgrid with PV Smart Inverters<= o:p> |
Not excluded |
|
7 |
|
Decentralized Control for Multiple
Network-Forming Inverters in a Solar PV-BESS Based Stand-alone Microgrid
System |
Not excluded |
|
8 |
|
Decentralized Dynamic Disturbance Compensation
Control Strategy for Multiple Parallel Inverters in Microgrid |
Excluded by language (Chinese) |
|
9 |
|
Decentralized Dynamic Disturbance Compensation
Control Strategy for Multiple Parallel Inverters in Microgrid |
Exclude due to lack of access |
|
10 |
|
Design and FPGA Implementation of an Islanding
Detection cum Re-synchronization Technique for a Grid Connected Inverter =
in a
DC Microgrid |
Not excluded |
|
11 |
|
Design of a novel hybrid control strategy for=
es
grid-connected inverter for smooth microgrid transition operation |
Not excluded |
|
12 |
|
Energy-storage fed smart inverters for mitiga=
tion
of voltage fluctuations in islanded microgrids |
Not excluded |
|
13 |
|
Frequency and voltage support by batteryâ€fed
smart inverters in mixedâ€inertia microgrids |
Not excluded |
|
14 |
|
Grid Forming Inverters: A Review of the State=
of
the Art of Key Elements for Microgrid Operation |
Not excluded |
|
15 |
|
Grid-Forming and Grid-Following Based Microgr=
id
Inverters Control |
Not excluded |
|
16 |
|
Hybrid islanding detection technique for inve=
rter
based microgrid |
Not excluded |
|
17 |
|
Identifying Power Oscillation Factors and
Improving Stability in Microgrids Comprised of Inverter-Based Resources |
Excluded by language (Japanese) |
|
18 |
|
Inverter-based islanded microgrid: A review on
technologies and control |
Not excluded |
|
19 |
|
Investigating and addressing synchronous
instabilities in inverter-based resources within microgrids |
Not excluded |
|
20 |
|
Modelling simulation and inverter control
strategy research of microgrid in grid-connected and island mode |
Not excluded |
|
21 |
|
Multi-objective decentralized model predictive
control for inverter air conditioner control of indoor temperature and
frequency stabilization in microgrid |
Not excluded |
|
22 |
|
Over frequency control of photovoltaic invert=
ers
in an island microgrid |
Not excluded |
|
23 |
|
PV-fed smart inverters for mitigation of volt=
age
and frequency fluctuations in islanded microgrids |
Not excluded |
|
24 |
|
Research on Adaptive Control Strategy of
Microgrid Inverter based on Virtual Synchronous Generator |
Not excluded |
|
25 |
|
Resistance capacitive inverter allocation met=
hod
based on fast reactive support based on Microgrid |
Not excluded |
|
26 |
|
Seamless Transferring Control Strategy for
Master-Slave Microgrid Inverter in Whole Off-grid Process |
Excluded by language (Chinese) |
|
27 |
|
Transient Response of Generator- and
Inverter-Based Microgrids to Rapid Load Changes |
Not excluded |
|
28 |
|
Voltage Regulator Using Sliding Mode Controll=
er
for Inverter Based Islanded Microgrid |
Excluded due to lack of access |
<= o:p>
Isol=
ated
Microgrids
Microgrids are composed of distributed generation sources, energy
storage systems, electrical loads, monitoring devices, and protection devic=
es
that can operate in either grid-connected or isolated mode (Wang et al., 20=
22).
Microgrids represent a crucial approach for ensuring the sustainability of
electricity supply, particularly in rural areas where extending the main gr=
id
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 sc=
heme
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.
T=
he
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). Â REF _Ref215845851 \h Figure 8 illustrates a more dynamic
microgrid scheme, encompassing all its components—generation, storage, and
energy consumption. In microgrids with air-conditioning inverters, regulati=
ng
power consumption reduces frequency fluctuations.
<= o:p>
Figure 8
Microgrid
scheme with a parallel inverter system
Source: case of st=
udy
taken from Shi, et al., 2025.
<= o:p>
<=
span
style=3D'mso-tab-count:1'>Â Â Â Â Â Â Â Â Â Â Â In Hmad et al. (202=
3), 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 illustra=
ted
in Figure 9.
<= o:p>
Figure 9
Control
system of the PV microgrid
Source: microgrid =
type
network formation taken from Attou, et al., 2023.
<= o:p>
Mixe=
d Inertia
Microgrids
A=
mong the
various microgrid configurations, the most used today is the mixed-inertia
configuration. This configuration consists of a microgrid generator group t=
hat
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 oc=
curs
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).
<= o:p>
A=
mong the
most common ways to mitigate these imbalances are the use of diesel generat=
ors
for voltage and frequency regulation (Pilehvar & Mirafzal, 2020b) and t=
he
employment of energy storage systems to inject or absorb reactive power to =
the
grid, thereby improving stability quickly during transients (Pilehvar &
Mirafzal, 2020c).
<= o:p>
T=
his type
of microgrid is illustrated in Figure 10, which shows diesel generat=
ion,
photovoltaic generation, a grid connection switch, and load.
<= o:p>
Figure 10
Schematic
of the mixed-inertia microgrid
Source: microgrid =
scheme
consulted in Pilehvar y Mirafzal, 2020c.
<= o:p>
Isol=
ation
Detection Methods in Microgrids
I=
solation
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).
<= o:p>
L=
ocal
methods, as the name suggests, are physically tied to the microgrid and are
further divided into active, passive, and hybrid (Anttila et al., 2022).
<= o:p>
A=
ctive
methods involve injecting harmonics or disturbances into the grid to detect
isolation, thereby reducing isolation detection time and avoiding deteriora=
tion
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).
<= o:p>
P=
assive
methods rely on measuring parameters such as voltage, current, impedance,
power, and frequency (Matthee et al., 2024; Samanta et al., 2021). Their ma=
in
drawbacks are the isolation detection time and the presence of a non-detect=
ion
zone (Samanta et al., 2021), although they do not affect power quality (Sam=
anta
et al., 2021). Passive methods include ROCOP (rate of change of output powe=
r),
ROCOF (rate of change of output frequency), and the phase hopping detection
method (Anttila et al., 2022).
<= o:p>
I=
n S. K.
Singh et al. (2021), the passive ROCOF and VU (voltage unbalance) methods a=
re
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 ROC=
OF
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.
<= o:p>
Figure 11
Block
diagram of the ROCOF method for isolation detection
Source: ROCOF diag=
ram
published in Singh et al., 2021.
Figure 12
Block
diagram of the VU method for isolation detection
Source: block diag=
ram
presented in Singh, et al., 2021.
<= o:p>
Figure 13
Block diagram of the passive-hybrid method
combining ROCOF and VU methods for isolation
Source: block diag=
ram of
ROCOF taken from Singh, et al., 2021.
H=
ybrid
methods integrate active and passive approaches to compensate for the
limitations of each. For example, the voltage unbalance and frequency set p=
oint
method combines voltage displacement and reactive power (Anttila et al., 20=
22).
<= o:p>
U=
nlike
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 (Anttil=
a 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).
<= o:p>
I=
n 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 (20=
22).
<= o:p>
Cont=
rol
Strategies for the Stability of Isolated Microgrids
Mitigation Strategies for Voltage Fluctua=
tions
in Isolated Microgrids
Voltage is one of the most unstable param= eters in isolated microgrids, due to typical events that alter system operation.<= o:p>
Among the works reviewed for this literat=
ure
review, one proposes the H∞ method, which, despite its mathematical compl=
exity,
focuses on controlling cross-coupled multivariate systems (H. Shi et al.,
2021). It involves adding an adaptive virtual impedance group to mitigate t=
he
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 mod=
ifying
the conventional control scheme of the battery energy storage system to enh=
ance
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) disc=
uss 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 r=
apid
reactive power support at the common connection point, stabilizing the volt=
age
and suppressing resonance between the impedances.
Finally, Luo et al. (2022) propose a dyna=
mic
compensation control strategy based on the generator's residual robustness,
thereby compensating for voltage variations.
Â
Frequency Variation Mitigation Strategies=
in
Isolated Microgrids
Frequency is another fundamental paramete= r of microgrids, as it helps to understand the behaviour of electrical signals.<= o:p>
Among the papers considered for this revi=
ew,
two methods were specifically developed to stabilize the frequency in isola=
ted
microgrids.
Hsu et al. (2019) analyse the impact of p=
ower
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 reliabili=
ty
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 compensati=
ng
for system frequency fluctuations. Figure 15 shows the frequency response curve with the proposed method.
Finally, Joshal & Gupta (2023) presen=
t the
PLL (phase-locked loop) method, which involves the connection and disconnec=
tion
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 a=
nd
Frequency Variations Jointly
Among the articles reviewed, four differe=
nt
methods were identified for stabilizing voltage and frequency simultaneousl=
y,
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., 201=
9).
It consists of a predictive controller with a two-degree-of-freedom algorit=
hm
and modified droop control, enabling a smooth transition between grid-conne=
cted
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 c=
ontrol
Source:
statistics extracted from Zheng, et al., 2019.
The same PLE method, as explained above f=
or
voltage stabilization (Pilehvar & Mirafzal, 2020a), is employed in Pile=
hvar
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 <=
span
style=3D'mso-no-proof:yes'>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 perfor=
mance
in dynamic response of the system
Source:
curves reported by Pilehvar y Mirafzal, 2020b.
Figure 20
Comparison of linear droop a=
nd 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 outp=
ut
conditions (Wang et al., 2022). In the active power control loop, the frequ=
ency
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 pro=
posed
Source:
schematic taken from Wang, et al., 2022.
Figure 22
Voltage changes at typical nodes before a=
nd
after the events explained
Source:
results published by Wang, et al., 2022.
Figure 23
Frequency changes at typical nodes, consi=
dering
the events mentioned
Source:
statistics reported by Wang, et al., 2022.
Finally, Pilehvar and Mirafzal (2020c) pr=
opose
a traditional PV generation controller to improve the dynamics of isolated
microgrids by reducing voltage and frequency variations. This method implem=
ents
a piecewise adaptive droop curve in PV units to achieve faster supply-demand
balance during transients. Reactive power is also injected/absorbed to impr=
ove
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 c=
urves
resulting from the APD method analyzed
Source:
curves taken from Pilehvar y Mirafzal, 2020c.
This review examin=
ed
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 conventi=
onal
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 revie=
wed
methods demonstrate promising results, they vary considerably in complexity=
and
implementation requirements. Techniques such as adaptive droop control, vir=
tual
impedance tuning, and predictive optimization algorithms have shown strong
potential to enhance the dynamic performance of low-inertia systems. Howeve=
r,
their effectiveness is closely tied to the specific configuration and opera=
ting
conditions of the microgrid.
The growing number=
of
publications over the last decade underscores the increasing relevance of t=
his
research field. Nonetheless, the dispersion of contributions across journals
and authors suggests the absence of a consolidated research community or st=
andardized
evaluation benchmarks.
This dispersion al= so 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 applicabi= lity may be constrained by hardware limitations or by the lack of interoperabili= ty between devices from different manufacturers. Therefore, future studies sho= uld not only assess technical performance but also address scalability, cost-effectiveness, and ease of integration with existing infrastructures.<= o:p>
Furthermore, this
review highlights a methodological gap in the comparative evaluation of con=
trol
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 co=
mmon
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 desi=
gn
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 fra=
mework.
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 renewab=
le
output variability. However, such approaches must be critically evaluated u=
nder
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 adapt=
able
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<=
/span>.
<= o:p>
Acknowledgeme=
nts and
Declarations
T=
his 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.
<= o:p>
A=
ccording
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 result=
s,
and preparing the manuscript.
<= o:p>
T=
he authors
declare that, in the preparation of this article, artificial intelligence t=
ools
(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 origi=
nal
intellectual work of the authors.
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Effective Strategies for
Mitigating Voltage and Frequency Fluctuations in Isolated Microgrids: A
Literature Review