Systematic Review of Microgrids Protection: Challenges, Methods, and Solutions

In e na ional Jou nal o Inno a i e Technology and Explo ing Enginee ing (IJITEE)
ISSN: 2278-3075 (Online), Volume-14 Issue-12, No embe 2025
13
Published By:
Blue Eyes In elligence Enginee ing
and Sciences Publica ion (BEIESP)
© Copy igh : All igh s ese ed.
Re ie al Numbe : 100.1/iji ee.A118215011225
DOI: 10.35940/iji ee.A1182.14121125
Jou nal Websi e: www.iji ee.o g
Abs ac : Mic og ids, pi o al in mode n powe sys ems, ace
unique p o ec ion challenges due o bidi ec ional powe lows,
dynamic opologies, and in e e -based esou ces (IBRs). This
sys ema ic e iew c i ically analyzes 55 pee - e iewed s udies
(2020-2024) o e alua e mic og id p o ec ion challenges, me hods,
and eme ging solu ions. We syn hesize indings om IEEE
Xplo e, MDPI, Sp inge , Wiley, and Taylo & F ancis da abases
using he PRISMA amewo k. Key challenges include
bidi ec ional powe low (36% o s udies), low aul cu en s
(33%), and p o ec ion coo dina ion ailu es (62%). Con en ional
me hods like o e cu en and dis ance p o ec ion s uggle wi h
adap abili y, while adap i e, communica ion-assis ed, and
in elligen s a egies show p omise bu ace complexi y and
cybe secu i y isks. AI-d i en me hodologies achie e a
aul -de ec ion accu acy o 99.2%. Howe e , hey equi e
subs an ial da ase s and conside able compu a ional esou ces.
Resilience amewo ks emain inadequa ely de eloped, wi h
me ely 10% o he li e a u e add essing c i ical me ics such as
eliabili y and eco e y. This e iew unde sco es he impe a i e
o hyb id solu ions and he es ablishmen o s anda dised
esilience me ics. I also highligh s he impo ance o alida ing
indings in eal-wo ld con ex s o ensu e he p ac ical applica ion
o heo e ical p og ess. Fu u e in es iga ions should emphasise
he impo ance o cybe secu i y measu es, he implemen a ion o
modula enhancemen s o legacy sys ems, and he de elopmen
o explainable a i icial in elligence o econcile heo e ical
p og ess wi h p ac ical applica ion.
Keywo ds: Adap i e P o ec ion, Con en ional P o ec ion,
In elligen P o ec ion, Mic og id, Sys ema ic Re iew.
Nomencla u e:
KPIs: Key Pe o mance Indica o s
HIFs: High-Impedance Faul s
DERs: Dis ibu ed Ene gy Resou ces
RES: Renewable Ene gy Sou ces
DOCP: Di ec ional o e cu en p o ec ion
IBRs: In e e -Based Resou ces
CTs: Cu en T ans o me s
DGs: Dis ibu ed Gene a o s
MTD: Mo ing Ta ge De ence
TCCs: Time-Cu en Cu es
PMUs: Phaso Measu emen Uni s
TCV: Time-Cu en -Vol age
Manusc ip ecei ed on 01 No embe 2025 | Re ised
Manusc ip ecei ed on 10 No embe 2025 | Manusc ip
Accep ed on 15 No embe 2025 | Manusc ip published on 30
No embe 2025.
*Co espondence Au ho (s)
D . Houssem Ben A ibia*, Depa men o Elec ical and Elec onics
Enginee ing, College o Enginee ing and Compu e Science, Jazan
Uni e si y, Jizan, Saudi A abia. Email ID: hbena [email protected],
ORCID ID: 0009-0007-9085-3689
D . Fe chichi Nou eddine, Na ional High Enginee ing School o Tunis,
Tunisia. Email ID: [email protected], ORCID ID:
0009-0000-2726-7176
D . Slim Abid, Depa men o Elec ical and Elec onics Enginee ing,
College o Enginee ing and Compu e Science, Jazan Uni e si y, Jizan,
Saudi A abia. Email ID: [email protected], ORCID ID:
0009-0002-0655-6088
© The Au ho s. Published by Blue Eyes In elligence Enginee ing and
Sciences Publica ion (BEIESP). This is an open-access a icle unde he
CC-BY-NC-ND license h p://c ea i ecommons.o g/licenses/by-nc-nd/4.0/
ML: Machine Lea ning
AI: A i icial In elligence
ANNs: A i icial Neu al Ne wo ks
SVMs: Suppo Vec o Machines
MAS: Mul i-Agen Sys ems
PMUs: Phaso Measu emen Uni s
TW: T a elling Wa e
DSDRs: Dual-Se ing Di ec ional Reclose s
FRT: Faul Ride-Th ough
TCV: Time-Cu en -Vol age
ENS: Ene gy No Se ed
I. INTRODUCTION
Mic og ids, including esiden ial, comme cial, and
indus ial a ian s, ha e e olu ionized con empo a y powe
sys ems by inco po a ing dis ibu ed ene gy esou ces
(DERs), imp o ing eliabili y, esilience, and sus ainabili y.
Unlike adi ional cen alized g ids, hese mic og ids ope a e
independen ly o in g id-connec ed modes, dynamically
Howe e , hese unique ope a ional cha ac e is ics c ea e
managing local gene a ion, s o age, and loads. signi ican
p o ec ion challenges as con en ional p o ec ion schemes
s uggle o handle bidi ec ional powe lows, islanding
ansi ions, and luc ua ing sho -ci cui le els [1]. As
mic og ids expand, esea che s mus de elop ad anced
p o ec ion s a egies ha ensu e selec i i y, eliabili y, and
adap abili y unde a ying g id condi ions [2].
O e he pas decade, esea che s ha e p oposed nume ous
mic og id p o ec ion me hods, including adap i e p o ec ion,
a i icial in elligence (AI)-based app oaches, and
communica ion-assis ed echniques [3], [4]. Despi e his
p og ess, no comp ehensi e s udy sys ema ically compa es
he e ec i eness, adap abili y, and implemen a ion
complexi y o hese me hods. In his sys ema ic e iew, we
c i ically examine he ex an li e a u e, ca ego ise he
p incipal challenges in p o ec ion, and e alua e he mos
iable solu ions. Ou me hodical amewo k gua an ees an
impa ial and anspa en assessmen o esea ch ou comes,
he eby assis ing enginee s and policymake s in making
well-in o med choices ega ding p ospec i e mic og id
p o ec ion me hodologies [5].
This sys ema ic e iew aims o answe he ollowing key
ques ions:
▪Ques ion 1: Wha a e he main challenges in mic og id
p o ec ion, and how do hey di e om con en ional
powe sys em p o ec ion?
This ques ion aims o iden i y and classi y challenges in
mic og id p o ec ion and o analyse he in luence o
enewable ene gy sou ces on aul de ec ion, selec i i y, and
p o ec ion sys em coo dina ion.
▪Ques ion 2: Wha a e he
mos commonly used
mic og id p o ec ion
me hods? How do hey
Houssem Ben A ibia, Fe chichi Nou eddine, Slim Abid
Sys ema ic Re iew o Mic og ids P o ec ion:
Challenges, Me hods, and Solu ions
Sys ema ic Re iew o Mic og ids P o ec ion: Challenges, Me hods, and Solu ions
14
Published By:
Blue Eyes In elligence Enginee ing
and Sciences Publica ion (BEIESP)
© Copy igh : All igh s ese ed.
Re ie al Numbe : 100.1/iji ee.A118215011225
DOI: 10.35940/iji ee.A1182.14121125
Jou nal Websi e: www.iji ee.o g
compa e in pe o mance, adap abili y, and
implemen a ion complexi y? How do hey imp o e
aul de ec ion and sys em esilience?
This ques ion aims o compa e and e alua e adi ional and
mode n p o ec ion app oaches.
▪ Ques ion 3: Wha a e he ecen ad ances in in elligen
mic og id p o ec ion sys ems?
This ques ion explo es he ole o AI, machine lea ning, and
communica ion-based app oaches in imp o ing mic og id
p o ec ion.
These h ee ques ions o m he basis o he wo k, and e e y
decision made du ing i s de elopmen will aim o answe
hem success ully.
This e iew pape o ganizes i s analysis in o i e dis inc
sec ions:
The i s sec ion in oduces he pape .
The second sec ion demons a es he me iculous,
sys ema ic e iew me hod used o de elop he e iew,
ensu ing he c edibili y and ho oughness o ou esea ch.
The hi d sec ion shows he de ails o ou analysis's esul s.
I discusses he implica ions o he key indings o mic og id
p o ec ion challenges, enewable ene gy in eg a ion,
p o ec ion me hods, and ad ances in in elligen p o ec ion.
The ou h sec ion summa izes he conclusions and sugges s
u u e esea ch di ec ions.
II. SYSTEMATIC REVIEW METHOD
A. In o ma ion Sou ces
This e iew ga he ed li e a u e om i e well-known
da abases:
▪ IEEE Xplo e
▪ MDPI
▪ Taylo & F ancis
▪ Sp inge
▪ Wiley
B. Sea ch S a egy
The speci ic sea ch e ms employed included "Mic og id,"
"Isola ed g id," "Dis ibu ed ene gy esou ces," "P o ec ion,"
"Faul p o ec ion," "Relay coo dina ion," "Challenges,"
"Me hods," and "Solu ions."
The que y s ings, which include combina ions o key e ms
like "Mic og id," "Isola ed g id," "Dis ibu ed ene gy
esou ces," "P o ec ion," "Faul p o ec ion," "Relay
coo dina ion," "Challenges," "Me hods," and "Solu ions,"
we e designed o na ow down he sea ch esul s o he mos
ele an pape s.
A il e was applied o he ini ial sea ch esul s, educing he
numbe o pape s o a manageable le el. The numbe o
documen s p esen ed wi hou his es ic ion is 2241.
We conside ed he ollowing il e s:
▪ This e iew used only pee - e iewed jou nal pape s and
igo ously e i ied and c edible esea ch while
emphasizing mic og id p o ec ion s udies. This a ge ed
app oach ensu es ha he e iew emains ele an and
comp ehensi e, explo ing bo h heo e ical and applied
aspec s o mic og id p o ec ion h ough modeling,
simula ion, and p ac ical case s udies.
▪ This e iew used only pape s published be ween 2020
and 2024, ensu ing ha he in o ma ion in his s udy is
up- o-da e. By ocusing on s udies published o e he
pas i e yea s, he jou nal cap u es he la es ad ances
and con empo a y me hodologies, e lec ing he cu en
s a e o esea ch and echnological p og ess.
▪ This e iew used only pape s in English, a language
conside ed he mos common o scien i ic esea ch. By
ocusing on English, we aimed o ensu e he b oades
accessibili y and comp ehensibili y, as i is he
p edominan language o scien i ic communica ion,
keeping ou audience in o med and knowledgeable.
The di e en ools employed o o ganize and e alua e he
pape s we e:
- Mendeley Re e ence Manage : Elimina e duplica es, ead,
ake no es, and o ganize pape s h oughou he p ocess.
- Mic oso Excel: A ange and e alua e da a.
C. Selec ion P ocess
i. P isma Me hodology
This e iew employs he PRISMA 2020 S a emen
(P e e ed Repo ing I ems o Sys ema ic Re iews and
Me a-Analyses) [5] o guide i s li e a u e selec ion p ocess,
minimizing po en ial biases and imp o ing anspa ency.
This sys ema ic app oach consis s o ou s ages:
▪ Iden i ica ion
▪ Sc eening
▪ Eligibili y & Inclusion
▪ Syn hesis
Figu e 1 illus a es an o e iew o he PRISMA
me hodology.
[Fig.1: Li e a u e Re iew P ocess Based on PRISMA
Me hodology]
ii. Iden i ica ion S age
In he Iden i ica ion s age, we e ie ed 347 i ems using he
sea ch s a egy de ined in he
in o ma ion sou ces
subsec ion. We in oduced a
coding sys em
In e na ional Jou nal o Inno a i e Technology and Explo ing Enginee ing (IJITEE)
ISSN: 2278-3075 (Online), Volume-14 Issue-12, No embe 2025
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Published By:
Blue Eyes In elligence Enginee ing
and Sciences Publica ion (BEIESP)
© Copy igh : All igh s ese ed.
Re ie al Numbe : 100.1/iji ee.A118215011225
DOI: 10.35940/iji ee.A1182.14121125
Jou nal Websi e: www.iji ee.o g
o each i em acco ding o he da abase consul ed. Table I
p esen s he iden i ied ex ac ed i ems.
Table I: The Coding Sys em o he Ex ac ed I ems
Da a Base
Coding Sys em
IEEE Xplo e
xxxx-IEEE
MDPI
xxxx-MDPI
Taylo & F ancis
xxxx-Taylo
Sp inge
xxxx-Sp inge
Wiley
xxxx-Wiley
We signi ican ly educed he isk o edundan analysis and
bias by diligen ly emo ing duplica e en ies. Wi h he aid o
Mendeley Re e ence Manage , we iden i ied and e adica ed
22 duplica e eco ds, esul ing in a p ecise o al o 325 unique
i ems o ou esea ch.
Figu e 2 p esen s a comp ehensi e o e iew o he i em
dis ibu ion ac oss he da abases, p o iding a clea pic u e o
ou esea ch scope: 94 i ems om IEEE Xplo e, 115 i ems
om MDPI, 14 i ems om Taylo & F ancis, 34 i ems om
Sp inge , and 68 i ems om Wiley.
[Fig.2: S a is ics o he Pape s Found in he Iden i ica ion S age]
iii. Sc eening S age
In he Sc eening s age, we ho oughly e iewed he i les
and abs ac s o e i y hei ele ance o he esea ch
objec i es, using p ede ined inclusion and exclusion c i e ia.
We ca e ully de ined hese c i e ia o ensu e he selec ion o
he mos ele an and high-quali y s udies o p o ec ing
mic og ids.
▪ Inclusion C i e ion (IC)
IC1: We included pape s published be ween 2020 and 2024
in English-language jou nals ocusing on p o ec ing
mic og ids o powe sys ems in eg a ed wi h dis ibu ed
gene a o s.
▪ Exclusion C i e ia (EC)
EC1: We exclude s udies published be o e 2020 and
documen s such as edi o ials and con e ence pape s. Ou
ocus is on o iginal con ibu ions ha p o ide new empi ical
indings o me hodologies.
EC2: We exclude abs ac s ha show he s udy does no
ocus on a mic og id o powe sys em wi h dis ibu ed
gene a o s.
EC3: We exclude e iew pape s, ea i ming ou
commi men o only conside p ima y sou ces, he eby
ensu ing he eliabili y o ou esea ch.
[Fig.3: Sc eening S age P ocess]
Figu e 3 shows he Sc eening s age p ocess, which esul ed
in he exclusion o 82 i ems (25% o he da abase's o al) and
he inclusion o 243 i ems (75% o he da abase's o al). The
included i ems appea ac oss he da abases as ollows:
▪ 75 i ems om IEEE Xplo e
▪ 82 i ems om MDPI
▪ 9 i ems om Taylo & F ancis
▪ 23 i ems om Sp inge
▪ 54 i ems om Wiley
i .Eligibili y and Inclusion S age
In he Eligibili y and Inclusion s age, we assessed he
ull- ex e sions o he selec ed pape s using p ede ined Key
Pe o mance Indica o s (KPIs) o ensu e ele ance, quali y,
and con ibu ion o ou e iew objec i es. We es ablished a
e i ica ion ma ix, as summa ized in Table II, o e alua e
each s udy based on:
▪ The discussion o mic og id p o ec ion challenges.
▪ The impac o enewable ene gy.
▪ The p o ec ion me hods.
▪ The ad ancemen s in
in elligen p o ec ion sys ems.
A se o c i e ia guided us
selec ion p ocess. We
Sys ema ic Re iew o Mic og ids P o ec ion: Challenges, Me hods, and Solu ions
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Published By:
Blue Eyes In elligence Enginee ing
and Sciences Publica ion (BEIESP)
© Copy igh : All igh s ese ed.
Re ie al Numbe : 100.1/iji ee.A118215011225
DOI: 10.35940/iji ee.A1182.14121125
Jou nal Websi e: www.iji ee.o g
p io i ized s udies ha comp ehensi ely iden i ied p o ec ion
challenges, classi ied p o ec ion echniques, analyzed
pe o mance me ics, and assessed adap abili y in mic og id
condi ions. We also a ou ed pape s ha in es iga ed he
impac o enewable ene gy in eg a ion on p o ec ion
eliabili y and selec i i y. Fu he mo e, we e alua ed s udies
on AI-based and communica ion-based p o ec ion me hods
o hei con ibu ions o sys em esilience. To ensu e he
highes me hodological igou , we conside ed ci a ion coun
and he le el o expe imen al alida ion. Each pape was
assigned a o al sco e, and only hose ha me he minimum
h eshold o 20 poin s ou o 24 (85%) we e included in ou
inal da ase , ensu ing he inclusion o highly ele an ,
high-quali y s udies.
Table II: Ve i ica ion Ma ix
Ca ego y
Key Pe o mance Indica o s (KPIs)
Desc ip ion
Sco ing C i e ia
Challenges in
Mic og id
P o ec ion
CIS: Challenge Iden i ica ion Sco e
Discusses mic og id-speci ic
p o ec ion challenges
0 = No
1 = B ie Men ion
2 = De ailed Discussion
CCP: Compa ison wi h Con en ional
P o ec ion
Compa es mic og id p o ec ion
wi h con en ional powe sys em
p o ec ion
0 = No
1 = Gene al Men ion
2 = In-dep h Analysis
Impac o
Renewable Ene gy
on P o ec ion
RIC: Renewable In eg a ion Co e age
E alua es he impac o enewable
ene gy on mic og id p o ec ion
0 = No
1 = B ie Men ion
2 = De ailed Impac Assessmen
RSA: Reliabili y & Selec i i y
Assessmen
Analyzes how enewable ene gy
a ec s p o ec ion sys em
eliabili y and selec i i y
0 = No
1 = Quali a i e
2 = Quan i a i e
(simula ions/expe imen s)
E alua ion o
P o ec ion Me hods
MCS: Me hod Classi ica ion Sco e
Ca ego izes p o ec ion me hods
0 = No
1 = Some me hods
2 = Comp ehensi e classi ica ion
PMD: Pe o mance Me ics Discussion
E alua es me hods based on
de ec ion speed, sensi i i y, and
alse ala m a e.
0 = No
1 = Basic discussion
2 = De ailed nume ical compa ison
ACA: Adap abili y and Complexi y
Analysis
Assesses he adap abili y o
me hods unde di e en ope a ing
condi ions
0 = No
1 = Basic men ion
2 = Case s udy/simula ion
Ad ances in
In elligen
P o ec ion
AIS: AI & ML In eg a ion Sco e
Discusses AI, ML, o deep
lea ning o mic og id p o ec ion
0 = No
1 = Men ioned
2 = Algo i hm p esen ed/ es ed
CBP: Communica ion-Based
P o ec ion
Co e s communica ion-based o
adap i e p o ec ion schemes
0 = No
1 = Men ioned
2 = Analyzed in de ail
RI: Resilience Imp o emen
Shows how in elligen me hods
imp o e esilience du ing aul s
0 = No
1 = Theo e ical discussion
2 = Expe imen al/simula ed p oo
Gene al Pape
Quali y Indica o s
Expe imen a ion Le el (EL)
Le el o alida ion
0 = Theo e ical only
1 = Simula ion-based
2 = Real-wo ld alida ion
Ci a ion Coun (CC)
Numbe o ci a ions
0 = <10
1 = 10–50
2 = >50
We e alua ed he 243 i ems om he Sc eening s age using
he Table I c i e ia, esul ing in 55 pape s being included in
his e iew. We used an MS Excel shee o assess he
documen s and included hose sco ing 85% o highe (20
poin s ou o 24).
Figu e 4 illus a es he Eligibili y and Inclusion s age
esul s, which led o he exclusion o 188 i ems (77% o he
da abase) and he inclusion o 55 i ems (23% o he da abase).
The sco ing dis ibu ion based on KPIs indica es ha mos
included pape s sco ed be ween 17 and 20 poin s. The
included i ems wi h a sco e o 85% o highe (20 poin s ou o
24) a e dis ibu ed ac oss he da abases as ollows:
▪ 37 i ems om IEEE Xplo e
▪ 9 i ems om MDPI
▪ 0 i ems om Taylo & F ancis
▪ 1 i em om Sp inge
▪ 8 i ems om Wiley
In e na ional Jou nal o Inno a i e Technology and Explo ing Enginee ing (IJITEE)
ISSN: 2278-3075 (Online), Volume-14 Issue-12, No embe 2025
17
Published By:
Blue Eyes In elligence Enginee ing
and Sciences Publica ion (BEIESP)
© Copy igh : All igh s ese ed.
Re ie al Numbe : 100.1/iji ee.A118215011225
DOI: 10.35940/iji ee.A1182.14121125
Jou nal Websi e: www.iji ee.o g
[Fig.4: Eligibili y and Inclusion S age]
. Syn hesis S age
This s age aims o classi y and in e p e esea ch
con ibu ions, and o iden i y signi ican ends and opics in
mic og id p o ec ion. We combined syn hesis me hods wi h
lowcha s o each esea ch ques ion o p o ide igo ous,
ep oducible answe s. This me hod is consis en wi h he
PRISMA sys ema ic e iew guidelines, a amewo k known
o i s anspa ency and ac i e syn hesis, which eassu es he
eade o he eliabili y o ou s udy. Figu e 5 p esen s a
lowcha ou lining he sys ema ic b eakdown o how each
ques ion was syn hesised.
Figu e 5 p esen s he Syn hesis me hod used o ques ions
1 (Q1), 2 (Q2), and 3 (Q3).
[Fig.5: Syn hesis Me hod]
III. RESULTS AND DISCUSSIONS
A. Challenges in Mic og id P o ec ion and Di e ences
om Con en ional Sys ems
i. No el Taxonomy o Challenges
The g owing pene a ion o dis ibu ed ene gy esou ces
(DERs) d i es he apid de elopmen o mic og ids, which,
in u n, in oduce p o ec ion challenges ha di e
signi ican ly om hose in con en ional powe sys ems. In
his e iew, we add ess he ques ion, "Wha a e he main
challenges in mic og id p o ec ion, and how do hey di e
om con en ional powe sys em p o ec ion?" by
syn hesising insigh s om 55 pape s ([6]-[60]). To iden i y
dominan challenges, we implemen ed a bibliome ic
analysis. Table III p esen s a quan i a i e and hema ic
b eakdown o challenges in mic og id p o ec ion and hei
di e ences om con en ional g ids.
Table III: Quan i a i e and Thema ic B eakdown o
Challenges in Mic og id
Challenge
F equency
All Pape s Add essing he
Challenge
Bidi ec ional
powe low
20 ou o 55
pape s
36%
[6], [10], [11], [14], [15], [17], [22],
[24], [25], [30], [31], [40], [43],
[48], [49], [50], [54], [57], [58], [59]
Low/limi ed aul
cu en s
18 ou o 55
pape s
33%
[7], [10], [12], [13], [14], [20], [25],
[27], [29], [30], [31], [36], [46],
[49], [54], [55], [56], [60]
Faul cu en
a iabili y
(g id-connec ed -
islanded)
17 ou o 55
pape s
31%
[6], [12], [15], [22], [26], [28], [34],
[38], [40], [43], [44], [47], [50],
[51], [52], [55], [59]
Communica ion
dependency
20 ou o 55
pape s
36%
[7], [8], [13], [25], [26], [29], [30],
[31], [32], [33], [36], [37], [43],
[44], [46], [48], [53], [54], [55], [57]
High-impedance
aul (HIF)
de ec ion
9 ou o 55
pape s
16%
[13], [14], [15], [18], [23], [28],
[40], [41], [56]
Sensi i i y o noise
5 ou o 55
pape s
9%
[7], [13], [29], [41], [54]
Vol age/ equency
ins abili y
6 ou o 55
pape s
11%
[16], [26], [41], [49], [50], [53]
In e e -based
esou ce (IBR)
limi a ions
17 ou o 55
pape s
31%
[7], [10], [12], [13], [19], [25], [27],
[28], [30], [31], [44], [46], [49],
[55], [56], [57], [60]
P o ec ion blinding
Miscoo dina ion
34 ou o 55
pape s
62%
[6], [8], [10], [11], [15], [16], [17],
[19], [21], [22], [23], [24], [25],
[27], [28], [30], [31], [33], [34],
[42], [43], [44], [45], [46], [47],
[48], [49], [50], [51], [53], [57],
[58], [59], [60]
ii. Bidi ec ional Powe Flow
Bidi ec ional powe low in mic og ids complica es aul
de ec ion and elay coo dina ion. Unlike con en ional
sys ems wi h unidi ec ional powe low, mic og ids ende
adi ional di ec ional p o ec ion schemes ine ec i e and
inc ease he isk o sympa he ic ipping, as eclose - use
coo dina ion o en ails unde e e se-powe - low
condi ions.
iii. Va iable and Low Faul Cu en Le els
In e e -based mic og ids limi aul cu en s o 1.2–2 p.u.,
a below he 5–10 p.u. ange. ypically gene a ed by
synch onous gene a o s in con en ional g ids. This lowe
cu en ange p e en s adi ional o e cu en elays om
unc ioning eliably, pa icula ly in islanded mode, and
lea es high-impedance aul s (HIFs) nea ly unde ec able.
While he luc ua ing na u e o enewable ene gy sou ces
(RES) educes he sensi i i y o con en ional p o ec ion
me hods, po en ially delaying aul clea ance and aising
misope a ion isks, localised gene a ion simul aneously
s eng hens esilience. Fo example, RES in islanded mode
can supply backup powe du ing g id dis u bances,
sus aining c i ical loads. Achie ing his ad an age, howe e ,
equi es deploying ad anced p o ec ion s a egies ha apidly
isola e aul s and sho en ou age
du a ions.

Sys ema ic Re iew o Mic og ids P o ec ion: Challenges, Me hods, and Solu ions
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i . Dynamic Topology and Ope a ing Modes
Mic og ids equen ly swi ch be ween g id-connec ed and
islanded modes, causing signi ican a ia ions in aul cu en
magni udes and ne wo k con igu a ions. In islanded mode,
aul cu en s can d op o jus 2–3 imes he a ed cu en , a
lowe han hose obse ed when connec ed o he p ima y
g id. These shi ing ope a ional s a es demand adap i e
p o ec ion schemes ha dynamically adjus elay se ings in
eal ime, unlike con en ional sys ems, which ely on s a ic
opologies and ixed con igu a ions.
. In e e -Based Mic og ids Limi a ions
In e e -based mic og ids gene a e non-sinusoidal aul
cu en s wi h ha monic dis o ions and con olled phase
angles, complica ing phaso es ima ion and elay
coo dina ion. Dis ance elays, o example, equen ly
misope a e when exposed o he a ypical aul beha iou s o
in e e -based mic og ids. Unlike synch onous machines,
hese mic og ids canno gene a e s able sinusoidal
wa e o ms du ing aul s. Fu he mo e, ha monics p oduced
by in e e s dis up elay aul -de ec ion algo i hms, o cing
enginee s o in eg a e ad anced il e ing me hods o imp o e
accu acy.
i.High-Impedance Faul s (HIFs) and Sensi i i y Issues
High-impedance aul s p oduce low-magni ude cu en s
ha o e lap wi h load cu en s, making aul de ec ion in
mic og ids challenging. Unde high enewable ene gy
pene a ion, his "p o ec ion blindness" becomes mo e
p onounced, as adi ional o e cu en p o ec ion elies on
he high aul cu en s ypical o con en ional sys ems.
ii.Communica ion and Synch oniza ion Requi emen s
Ad anced p o ec ion schemes ely on high-bandwid h
communica ion ne wo ks o eal- ime coo dina ion. This
eliance exposes mic og ids o isks such as delays,
synch oniza ion issues, and cybe -a acks like alse-da a
injec ion ha comp omise elay ope a ions, unlike he
simple , decen alized p o ec ion ound in con en ional
sys ems.
iii. P o ec ion Coo dina ion Challenges
The in e mi en ou pu o RES and a iable aul cu en s
dis up s coo dina ion among p ima y elays, backup de ices,
eclose s, and uses. In mic og ids, RES back- eed cu en s
can igge sympa he ic ipping, disconnec heal hy eede s
and complica e ixed coo dina ion s a egies ha wo k well
in s a ic, adial con en ional ne wo ks.
ix. G ounding and Re-Synch oniza ion Issues
Du ing islanded ope a ion, mic og ids lose he p ima y
g id’s g ounding e e ence, which complica es g ound aul
de ec ion. Addi ionally, e-synch oniza ion du ing g id
econnec ion in oduces ol age and equency de ia ions
ha o ce dynamic adjus men s in elay se ings o main ain
sys em s abili y.
x. Cybe -Physical Vulne abili ies
Many s udies emphasize ha he in eg a ion o RES
inc eases he eliance on sophis ica ed con ol s a egies and
obus communica ion ne wo ks. While hese sys ems enable
adap i e p o ec ion by con inuously upda ing elay se ings,
hey also in oduce ulne abili ies ela ed o communica ion
delays and po en ial cybe h ea s, and expose mic og ids o
cybe -a acks such as alse-da a injec ion (FDI), which can
dis up elay coo dina ion. These ulne abili ies pose
signi ican isks o p o ec ion eliabili y and sys em s abili y,
con en ional sys ems, wi h simple decen alized p o ec ion,
ace ewe such h ea s due o p edic able aul beha io .
xi. Wea he -Dependen Faul Cu en Va iabili y
Renewable ene gy sou ces (RES) c ea e in e mi en aul
cu en s because sola i adiance and wind speeds a y
unp edic ably. These wea he -dependen a ia ions
complica e he coo dina ion o p o ec i e elays, o cing
enginee s o adop s ochas ic modelling o ensu e eliable
sys em ope a ion. In con as , con en ional powe sys ems
ely on s able synch onous gene a ion, which inhe en ly
a oids such unp edic abili y.
Figu e 6 p esen s a comp ehensi e mind map ou lining he
key challenges in mic og id p o ec ion and highligh ing how
hey di e om hose in con en ional powe sys em
p o ec ion.
[Fig.6: Mind Map o Key Challenges in Mic og id
P o ec ion]
Mic og id challenges a e classi ied in o ou in e connec ed
ca ego ies ha e lec hei echnical, ope a ional, economic,
and egula o y dimensions.
In e na ional Jou nal o Inno a i e Technology and Explo ing Enginee ing (IJITEE)
ISSN: 2278-3075 (Online), Volume-14 Issue-12, No embe 2025
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Table IV: Mic og id Challenges Ca ego ies
Ca ego y
Sub-Challenges
Key Pape s
Technical
Bidi ec ional powe low
51 ou o 55
pape s
93%
Low/inconsis en aul cu en s (IBR
limi a ions)
Relay coo dina ion ailu es
High-impedance aul (HIF) de ec ion
Vol age/ equency ins abili y
Ope a ional
Mode ansi ions (g id-connec ed ↔
islanded)
18 ou o 55
pape s
33%
Dynamic opology changes
DG pene a ion a iabili y
Communica ion la ency/packe loss
Economic
High cos o di e en ial p o ec ion
5 ou o 55
pape s
9%
Communica ion in as uc u e
expenses
Re o i ing legacy sys ems
Regula o y
Lack o mic og id-speci ic s anda ds
3 ou o 55
pape s
5%
In e e compliance issues
Cybe secu i y manda es
Tables III and IV show ha mos esea che s ocus
p ima ily on echnical challenges in mode n powe sys ems,
wi h 93% o he pape s explo ing bidi ec ional issues. This
subs an ial ocus unde sco es enginee s' need o e amp
adi ional sys ems o accommoda e ene gy om dis ibu ed
sou ces. The esea ch also in es iga es issues such as low and
inconsis en aul cu en s om in e e -based sou ces, elay
coo dina ion p oblems, di icul ies in de ec ing
high-impedance aul s, and ol age and equency s abili y
issues. Abou 33% o he s udies examine ope a ional
challenges, such as he in icacies o swi ching be ween
g id-connec ed and islanded modes, changes in ne wo k
layou s, a ia ions in dis ibu ed gene a ion, and
communica ion delays o losses ha can dis up sys em
con ol. Only 9% o he esea ch add esses economic
challenges, such as he high cos o di e en ial p o ec ion,
sugges ing ha cos issues and ou da ed sys em upda es a e
no he p ima y ocus. Finally, jus 5% o he pape s add ess
egula o y challenges, highligh ing he need o es ablish
speci ic s anda ds, imp o e in e e compliance, and
s eng hen cybe secu i y o unde pin new g id echnologies.
B. Linking Challenges o Real-Wo ld Failu es
While many s udies ely on simula ions, i 's a e o a small
subse o au ho s o b idge heo e ical challenges wi h
p ac ical ou comes success ully. This excep ional app oach
alida es heo e ical models and unde sco es he u gen need
o add ess hese issues in eal-wo ld applica ions. Wi h only
2% o s udies (1 ou o 55) di ec ly co ela ing hese
challenges wi h documen ed eal-wo ld inciden s, he
signi ican gap be ween esea ch and p ac ical inciden
analysis becomes e en mo e p onounced.
The Uk ainian G id A ack (2015) se es as a s a k
eminde o he po en ial de as a ion o a synch onized and
coo dina ed cybe a ack. This inciden comp omised h ee
Uk ainian egional elec ic powe dis ibu ion companies,
leading o powe ou ages ha a ec ed app oxima ely
225,000 cus ome s o se e al hou s. The exace ba ion o
cascading ou ages due o communica ion ailu es in adap i e
p o ec ion [9] unde sco es he g a i y o he si ua ion.
U.S. Wind/Sola Cybe a acks (2019): A denial-o -se ice
a ack le g id ope a o s empo a ily blinded o se e al wind
and sola a m gene a ion si es in he U.S. Spoo ed elay
se ings delayed aul clea ing [9]. Case s udies b idge
heo e ical esea ch and p ac ical implemen a ion. Only 13%
o s udies (7/55) alida e indings wi h eal-wo ld da a.
C. Mapping Challenges o Mic og id A che ypes
The li e a u e di e en ia es mic og id p o ec ion issues
based on sys em a chi ec u e. Pape s ha explo e cen alized
e sus dis ibu ed con igu a ions o compa e g id-connec ed
wi h islanded modes e eal ha challenges a y signi ican ly
wi h sys em design. Fo ins ance, he unique challenges
posed by low aul cu en s in in e e -based islanded
mic og ids and he mo e p essing issues c ea ed by
communica ion delays in la ge, dis ibu ed ne wo ks
highligh he ield's complexi y. Mapping hese dis inc ions
enables enginee s o cus omize p o ec ion s a egies o
speci ic mic og id a che ypes (Table V), ensu ing solu ions
balance e ec i eness and cos -e iciency.
Table V: Mic og id A che ypes
A che ype
Key Challenges
Key
Pape s
G id-Conne
c ed
▪ Islanding de ec ion and p e en ion
▪ Bidi ec ional powe low complica es aul
cu en con ibu ions
▪ Coo dina ion be ween mic og id and cen al
g id p o ec ion sys ems
▪ Dynamic ne wo k opology equi ing
adap i e se ings
Impac o cybe secu i y ulne abili ies in
communica ion-based schemes
33 ou o
55 pape s
60%
Islanded
(IBR-Domi
na ed)
▪ Reduced aul cu en le els and lack o
ex e nal suppo
▪ F equency and ol age egula ion challenges
▪ Limi ed backup p o ec ion and ine ia
▪ Adap i e p o ec ion schemes equi ed o
isola ed ope a ion
Main aining s abili y wi hou a g id e e ence
16 ou o
55 pape s
29%
AC
Mic og id
▪ In e e -based esou ce beha iou educes
aul cu en le els
▪ Sensi i i y issues wi h adi ional o e cu en
elays
▪ Coo dina ion wi h legacy p o ec ion sys ems
▪ Va iable aul con ibu ions om enewable
sou ces
Necessi y o adap i e and as -ac ing
p o ec ion schemes
6 ou o
55 pape s
11%
DC
Mic og id
▪ Lack o na u al cu en ze o c ossings,
complica ing a c aul de ec ion
▪ Fas ansien aul de ec ion and isola ion
equi emen s
▪ Limi ed a ailabili y o s anda d p o ec ion
de ices
▪ O e ol age and sho -ci cui p o ec ion
challenges
Rapid esponse needs o aul isola ion
1 ou o
55 pape s
2%
Hyb id
Mic og id
▪ Coo dina ing p o ec ion be ween AC and DC
subsys ems
▪ B idging di e en ol age le els and aul
cha ac e is ics
▪ Inconsis en aul p opaga ion ac oss
domains
▪ Complex sys em in eg a ion and adap i e
se ing challenges
Communica ion delays be ween he AC and
DC p o ec ion laye s
2 ou o
55 pape s
4%
Mul i-Mic
og id
Clus e s
▪ Complex in e -mic og id p o ec ion
coo dina ion
▪ Cascading aul p opaga ion isks
▪ Communica ion and la ency challenges
ac oss di e en mic og ids
▪ Mul i-laye ed p o ec ion se ings equi ing
synch oniza ion
Ensu ing consis ency in adap i e p o ec ion
schemes ac oss a dis ibu ed ne wo k
3 ou o
55 pape s
5%
D. Resilience Sco ing
F amewo k
Resilience me ics a e i al
o assessing and enhancing
Sys ema ic Re iew o Mic og ids P o ec ion: Challenges, Me hods, and Solu ions
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mic og id eliabili y in he ace o unce ain ies such as
componen ailu es, ex eme wea he , o cybe a acks.
Resea che s and p ac i ione s commonly emphasize he
ollowing key esilience me ics and concep s in he
li e a u e:
i. Reliabili y and A ailabili y Me ics
▪ Loss o Load P obabili y (LOLP): is a p ac ical
me ic ha quan i ies he p obabili y o he a ailable
supply ailing o mee he load demand du ing a
speci ic pe iod. This me ic is no jus a heo e ical
concep bu a ool o assessing and imp o ing he
eliabili y o a mic og id in eal-wo ld scena ios.
▪ Expec ed Ene gy No Se ed (EENS): es ima es
ha he ene gy sys em ails o deli e c i ical loads
du ing ou ages.
▪ The Sys em A e age In e up ion F equency
Index (SAIFI) and Du a ion Index (SAIDI):
These indices accu a ely assess he equency and
du a ion o powe in e up ions in he con ex o
mic og ids, making hem highly ele an and
applicable o ene gy sys ems and mic og id
echnology.
ii. Reco e y and Res o a ion Me ics
▪ Mean Time o Reco e y (MTTR): Measu es he
a e age ime i akes o he mic og id o eco e
a e a dis up i e e en .
▪ Time o Resilience (TR): Me ic ha may include
es o a ion ime and he ime equi ed o e-es ablish
ull ope a ional unc ionali y, including
synch oniza ion wi h he p ima y g id i needed.
iii. Robus ness and Flexibili y
▪ Con ingency Analysis (N-1, N-2, e c.): The
mic og id can sus ain ope a ion when one o mo e
componen s ail.
▪ Rese e Ma gin: Ex a capaci y o mee demand
du ing unexpec ed ou ages o load spikes.
▪ Di e si y o Ene gy Sou ces: Mix and edundancy
o gene a ion esou ces can indica e esilience.
i . Ope a ional Resilience Me ics
▪ Sel -Healing Capabili ies: Measu es how
e ec i ely a mic og id can au oma ically
econ igu e o isola e aul s o p e en cascading
ailu es.
▪ Cybe -Physical Resilience Indica o s: Me ics
assessing he physical in as uc u e and i s
cybe secu i y.
. Economic and Pe o mance-Based Me ics
▪ Cos o Resilience: E alua e he economic
ade-o s in ol ed in inco po a ing esilience
measu es.
▪ Pe o mance Deg ada ion Unde S ess:
Moni o s how sys em pe o mance deg ades unde
s ess condi ions and how quickly i can e u n o
op imal le els.
Only 6 (11%) o he 55 pape s di ec ly o indi ec ly add ess
he c ucial opic o esilience. This esea ch is pa amoun in
ou ield, as i p o ides aluable insigh s in o he cu en
esilience o ene gy sys ems.
Pape [19] ocuses on sel -healing capabili ies and
con ingency handling as key esilience ea u es. I alida es
hese h ough dynamic econ igu a ion and aul eco e y in
g id-connec ed and islanded modes. Howe e , i does no
add ess economic ade-o s, cybe -physical esilience, o
o mal eliabili y me ics (LOLP, SAIDI). The esilience
amewo k is p ima ily echnical, emphasizing p o ec ion
logic, in e e s abili y, and au oma ed econ igu a ion.
Pape [32] add esses esilience h ough eliabili y me ics
(PSuccess, LOu age), sel -healing ia agen nego ia ion and
aul isola ion, and con ingency handling o mul iple aul s.
Pape [53] add esses obus ness ( ia con ingency handling
and VSM op imiza ion) and ope a ional esilience ( h ough
p io i y-based load shedding). Howe e , i lacks an explici
discussion o adi ional esilience me ics such as LOLP,
SAIDI, MTTR, and cybe -physical indica o s. This could
limi he esea ch's applicabili y in eal-wo ld se ings. The
ocus emains on echnical pe o mance (de ec ion accu acy,
ol age s abili y) a he han comp ehensi e esilience
amewo ks.
Pape [28] men ions " esilience" in he abs ac and
conclusion, linking he p oposed s a egy o imp o ed g id
esilience. The ocus is on mi iga ing p o ec ion blindness ia
adap i e se ings and aul -cu en limi a ion, he eby
indi ec ly suppo ing esilience h ough imp o ed aul
managemen .
Pape [36] ocuses on he design o p o ec ion schemes and
low-cos communica ion o aul de ec ion in
in e e -domina ed mic og ids. In con as , i enhances
ope a ional eliabili y and indi ec ly suppo s esilience (e.g.,
as aul isola ion and communica ion edundancy). The
esilience- ela ed e ms men ioned (" eliabili y,"
"sel -healing") a e quali a i e and no quan i ied.
Pape [45] add esses p o ec ion sys em op imiza ion
(adap i e elay coo dina ion) o enhance eliabili y and
speed. While i indi ec ly ouches on obus ness ( ia
DG/ opology a ia ions) and ope a ional adap abili y, none
o he esilience me ics a e explici ly analyzed.
E. P o ec ion S a egies in Mic og id
i. No el Taxonomy o S a egies
Resea che s ha e in es iga ed a wide ange o p o ec ion
s a egies o add ess mic og ids' unique challenges. This
e iew add esses he ques ion, " Wha a e he mos
commonly used mic og id p o ec ion me hods? How do hey
compa e in pe o mance, adap abili y, and implemen a ion
complexi y, and how do hey imp o e aul de ec ion and
sys em esilience?", " Wha a e he ecen ad ances in
in elligen mic og id p o ec ion sys ems?" by syn hesizing
insigh s om 55 pape s ([6]-[60]). We implemen ed a
bibliome ic analysis o iden i y dominan p o ec ion
s a egies. Table VI p esen s a quan i a i e and hema ic
b eakdown o mic og id p o ec ion
s a egies.
In e na ional Jou nal o Inno a i e Technology and Explo ing Enginee ing (IJITEE)
ISSN: 2278-3075 (Online), Volume-14 Issue-12, No embe 2025
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and Sciences Publica ion (BEIESP)
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DOI: 10.35940/iji ee.A1182.14121125
Jou nal Websi e: www.iji ee.o g
Table VI: Quan i a i e and Thema ic B eakdown o
Mic og id P o ec ion S a egies
P o ec ion S a egies
F equency
All Pape s Add essing
P o ec ion S a egies
Communica ion-Based
P o ec ion
11 ou o 55 pape s
20%
[8]-[14]-[30]-[35]-[39]-
[44]-[47]-[48]-[56]
Di e en ial P o ec ion
6 ou o 55 pape s
11%
[9]-[23]-[24]-[32]
In e e -Based
P o ec ion
7 ou o 55 pape s
13%
[16]-[18]-[19]-[25]-[34]-
[36]-[39]
Adap i e P o ec ion
14 ou o 55 pape s
25%
[11]-[28]-[30]-[32]-[35]-
[38]-[41]-[45]-[58]
Di ec ional
O e cu en P o ec ion
5 ou o 55 pape s
9%
[24]-[32]-[40]
Dis ance (Impedance)
P o ec ion
4 ou o 55 pape s
7%
[32]-[52]-[53]-[54]
O e cu en (OC)
P o ec ion
6 ou o 55 pape s
11%
[17]-[21]-[37]
Reclose and Fuse
P o ec ion
2 ou o 55 pape s
4%
[17]-[29]
Vol age-Based
P o ec ion
1 ou o 55 pape s
2%
F equency-Based
P o ec ion
2 ou o 55 pape s
4%
[22]
In elligen P o ec ion
7 ou o 55 pape s
13%
[55]
T a elling
Wa e-Based
P o ec ion
7 ou o 55 pape s
13%
[18]-[19]-[30]-[49]-[54]
Hyb id and No el
Schemes
5 ou o 55 pape s
9%
[20]-[26]-[40]-[46]
We classi y mic og id p o ec ion s a egies in o six
ca ego ies o p o ide a comp ehensi e unde s anding o how
o ailo hese s a egies o add ess he dynamic challenges
posed by mic og ids, as discussed in he p e ious sec ion.
Table VII p esen s da a om a axonomy ha p o ides a
s uc u ed amewo k highligh ing he e olu ion om
con en ional app oaches o eme ging, adap i e, and
in eg a ed solu ions. This axonomy plays a c ucial ole in
his e iew pape by o ganizing exis ing esea ch in o clea ,
mu ually exclusi e ca ego ies and iden i ying gaps and
oppo uni ies o u u e wo k.
Table VII: Mic og id P o ec ion Ca ego ies
Ca ego y
Techniques
Key Pape s
Con en ional
P o ec ion
O e cu en (OC) P o ec ion
Dis ance (Impedance) P o ec ion
Di e en ial P o ec ion
Di ec ional O e cu en P o ec ion
Reclose and Fuse P o ec ion
19 ou o 55
pape s
35%
Adap i e
P o ec ion
Adap i e P o ec ion
Vol age-Based P o ec ion
14 ou o 55
pape s
25%
Communica io
n-Assis ed
P o ec ion
Communica ion-Based P o ec ion
11 ou o 55
pape s
20%
In e e /DER-S
peci ic
P o ec ion
In e e -Based p o ec ion
7 ou o 55
pape s
13%
In elligen &
Da a-D i en
Me hods
In elligen P o ec ion
F equency-Based P o ec ion
T a elling Wa e-Based P o ec ion
14 ou o 55
pape s
25%
Hyb id/In eg a
ed Sys ems
Hyb id and No el Schemes
5 ou o 55
pape s
9%
The bibliome ic analysis shows ha esea che s emphasise
a di e si ied app oach o p o ec ion s a egies. Con en ional
p o ec ion echniques, including o e cu en elays, dis ance
p o ec ion, di e en ial p o ec ion, di ec ional o e cu en
p o ec ion, and eclose and use p o ec ion, appea in 35%
(19 pape s) o he li e a u e, demons a ing con inued
eliance on es ablished me hods. Resea che s also ocus on
adap i e and ol age-based p o ec ion, which accoun s o
25% (14 pape s), as hey de elop dynamic sys ems ha
swi ly espond o changing g id condi ions. Howe e ,
esea che s inc easingly emphasize communica ion-assis ed
p o ec ion in he li e a u e, highligh ing his app oach in 20%
(11 pape s). This end unde sco es he inc easing
impo ance o in eg a ing eal- ime da a exchange o imp o e
sys em eliabili y. The li e a u e also shows ha
in e e /DER-speci ic p o ec ion accoun s o 13% (7 pape s)
and add esses he challenges associa ed wi h enewable
ene gy in eg a ion. Meanwhile, in elligen and da a-d i en
me hods, including in elligen p o ec ion, equency-based
p o ec ion, and a elling-wa e-based p o ec ion, accoun o
25% (14 pape s) o he esea ch, as in es iga o s le e age
inno a i e echnologies o enhance esilience. Finally,
esea che s a e explo ing hyb id o in eg a ed sys ems, as
e idenced by 9% (5 pape s) ha p esen hyb id and no el
schemes ha blend adi ional and inno a i e app oaches o
achie e obus p o ec ion.
ii. Con en ional Me hods
T adi ional schemes de eloped o adial, cen ally
gene a ed g ids ely on ixed se ings and simple
coo dina ion me hods.
iii. O e cu en P o ec ion (OCP)
T adi ional o e cu en elays a e widely used in
con en ional sys ems because hey a e cos -e ec i e and
s aigh o wa d. Howe e , se e al s udies highligh ha OCP
is less e ec i e in mic og ids. The low aul cu en le els,
especially in islanded ope a ion, and he bidi ec ional powe
low o en led o miscoo dina ion and alse ipping. While
OCP has low implemen a ion complexi y, i s pe o mance
and adap abili y a e limi ed in mic og ids.
The adap abili y o o e cu en p o ec ion (OCP) in
mic og ids, pa icula ly i s abili y o handle bidi ec ional
powe lows and low aul cu en s inhe en o in e e -based
esou ces (IBRs), is a key aspec o his p o ec ion.
Implemen ing OCP in mic og ids is a complex ask ha
in ol es balancing cos -e ec i eness wi h he need o
adap i e se ings o handle dynamic ope a ing condi ions.
The limi a ions o ixed elay se ings pose a signi ican
challenge o OCP, unde sco ing he need o mo e
ad anced, adap able solu ions in mic og ids.
▪ False ipping due o bidi ec ional lows [11] p oposes
ol age- es ained elays (51V) o mi iga e his.
▪ Limi ed sensi i i y o high-impedance aul s,
add essed in [12] using Mahalanobis dis ance-based
de ec ion.
i . Di e en ial P o ec ion
Di e en ial elaying compa es cu en measu emen s a
bo h ends o a p o ec ed zone, p o iding high sensi i i y and
selec i i y e en unde bidi ec ional condi ions. This me hod
excels a accu a ely isola ing aul s bu ypically equi es
obus communica ion in as uc u e and synch onised
measu emen uni s, which
inc ease cos s and
implemen a ion complexi y.
Despi e hese challenges,
Sys ema ic Re iew o Mic og ids P o ec ion: Challenges, Me hods, and Solu ions
28
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DOI: 10.35940/iji ee.A1182.14121125
Jou nal Websi e: www.iji ee.o g
▪ Dual-se ing di ec ional o e cu en elays (DOCRs)
in eg a e smoo hly wi h exis ing in as uc u e, capping
e o i ing cos s a 15–20% [33].
These solu ions ep esen a p agma ic comp omise,
enhancing p o ec ion pe o mance wi hou o e whelming
in as uc u e demands.
xxii.Reliabili y and Resilience
Reliabili y desc ibes a sys em's capaci y o aul - ee
ope a ion unde no mal condi ions, while esilience
quan i ies i s abili y o eco e om dis up ions.
Con en ional p o ec ion me hods deli e high eliabili y in
s a ic g ids bu al e in DER-domina ed mic og ids, whe e
hey canno adap o inhe en powe luc ua ions [39].
Communica ion-assis ed schemes apidly isola e aul s bu
isk p olonged down ime (up o 62%) du ing ne wo k
ou ages.
Adap i e and in elligen me hods coun e hese limi a ions
by embedding sel -healing algo i hms ha sus ain 95%
up ime e en du ing cybe a acks. Hyb id sys ems u he
enhance esilience; ha monic injec ion, o example,
decouples p o ec ion unc ions om con inuous
communica ion dependency. DER-speci ic echniques, such
as i ual impedance app oaches, add obus ness by
emula ing synch onous gene a o esponses du ing aul s,
he eby imp o ing sys em eco e y.
xxiii. Scalabili y and In e ope abili y
Scalabili y measu es a me hod's abili y o scale o la ge ,
mo e complex sys ems, while in e ope abili y ensu es
compa ibili y wi h legacy in as uc u e. Con en ional
me hods o en exhibi poo scalabili y in DER- ich g ids due
o hei ixed con igu a ions [33]. In con as , in elligen
me hods demons a e s ong scalabili y po en ial; ede a ed
lea ning, hough unde explo ed in his ield, could
decen alize AI aining and enhance adap abili y ac oss
dis ibu ed mic og ids. Hyb id sys ems u he boos
in e ope abili y h ough modula amewo ks ha enable
inc emen al upg ades and seamless in eg a ion wi h legacy
sys ems [25]. Eme ging 5G wi eless p o ocols, while no ye
widely s udied in his con ex , could also scale
communica ion-assis ed schemes, pa icula ly bene i ing
u al mic og id applica ions.
xxi . Cybe secu i y Conside a ions
Cybe secu i y is c i ical, as p o ec ion schemes mus be
obus agains a ange o cybe h ea s.
Communica ion-assis ed p o ec ion me hods a e pa icula ly
p one o spoo ing and da a injec ion a acks, wi h s udies
epo ing up o 12% o alse ips [9]. In elligen me hods a e
also ulne able o ad e sa ial machine lea ning a acks,
posing signi ican isks in en i onmen s whe e da a in eg i y
is pa amoun . Con en ional me hods, while low isk om a
cybe pe spec i e due o hei analogue na u e, a e no
adap able o DER luc ua ions. In eg a ing quan um- esis an
enc yp ion and Mo ing Ta ge De ence (MTD) echniques is
c i ical o u u e-p oo adap i e and communica ion-assis ed
sys ems, a unique insigh highligh ed by ecen esea ch.
xx . Cos and Economic Feasibili y
Cos -e ec i eness and economic easibili y a e essen ial
when conside ing la ge-scale mic og id deploymen .
Con en ional o e cu en p o ec ion is no ed o i s low
ini ial and ope a ional cos s bu o e s limi ed e u ns in
DER- ich g ids. Adap i e p o ec ion me hods incu mode a e
ini ial cos s; howe e , hei high ROI in indus ial
applica ions can jus i y he high main enance cos associa ed
wi h AI componen s. While o e ing ul a- as aul isola ion,
communica ion-assis ed sys ems incu high ini ial and
ope a ional cos s due o ne wo k main enance, making hem
be e sui ed o u ban en i onmen s. Hyb id sys ems s ike a
balance be ween mode a e expenses, making hem he mos
economically iable op ion o mixed- opology ne wo ks.
Cos -bene i analyses in he Pape suppo hese insigh s [20]
and ope a ional expendi u e s udies in Pape [26].
xx i. Real-Wo ld Valida ion
Field alida ion is c ucial o assessing he p ac ical
iabili y o p o ec ion s a egies. S udies show ha
con en ional me hods alida e in app oxima ely 70% o
cases, ye hey o en unde pe o m in DER scena ios [39].
Ad anced echniques such as adap i e, in elligen , and
hyb id sys ems ha e unde gone eal-wo ld es ing in only
9–15% o cases— o ins ance, success ul ials in Inne
Mongolia wind a ms [35]. Hyb id sys ems ha e shown
100% selec i i y in CIGRE benchma k ield es s [25]. A
signi ican gap pe sis s in s anda dising c oss-s udy
compa isons, unde sco ing he need o uni ied alida ion
amewo ks.
xx ii. Fu u e P ospec s and Recommenda ions
Se e al u u e di ec ions can help b idge he gap be ween
labo a o y inno a ion and widesp ead mic og id deploymen .
The e is a p essing need o in eg a e sus ainabili y me ics
in o p o ec ion s a egies, linking elay coo dina ion di ec ly
o ca bon educ ion and imp o ed ene gy e iciency (e.g.,
educed Ene gy No Se ed, ENS). Modula upg ades, such
as e o i ing legacy elays wi h plug-and-play AI and
communica ion modules, o e a p ac ical pa hway o
enhancing exis ing sys ems [33]. Howe e , de eloping
Explainable AI is no jus ano he s ep bu a c i ical one in
building indus y us h ough anspa en decision-making
p ocesses. Addi ionally, es ablishing IEEE/IEC guidelines
o AI model benchma king and hyb id sys em
in e ope abili y will be i al in s anda dising p o ec ion
solu ions. Finally, cybe secu i y mus e ol e by adop ing
quan um- esis an enc yp ion and ad anced Mo ing Ta ge
De ence echniques o sa egua d mic og id ope a ions
agains eme ging h ea s.
xx iii. Imp o emen s in Faul De ec ion and Sys em
Resilience
▪ Collec i ely, hese ecen ad ances con ibu e o
he ollowing imp o emen s: Fas e and Mo e
Accu a e Faul De ec ion: AI/ML and ad anced signal
p ocessing play pi o al oles in achie ing quicke ,
mo e accu a e aul de ec ion. These echnologies
enable in elligen p o ec ion sys ems o de ec aul s in
sub-cycle imes (less han 16 ms), a signi ican
imp o emen o e con en ional me hod.
▪ Enhanced Adap abili y: Adap i e schemes and
hyb id app oaches a e ins umen al in main aining
high sensi i i y and
selec i i y. These
app oaches allow
p o ec ion se ings o

In e na ional Jou nal o Inno a i e Technology and Explo ing Enginee ing (IJITEE)
ISSN: 2278-3075 (Online), Volume-14 Issue-12, No embe 2025
29
Published By:
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and Sciences Publica ion (BEIESP)
© Copy igh : All igh s ese ed.
Re ie al Numbe : 100.1/iji ee.A118215011225
DOI: 10.35940/iji ee.A1182.14121125
Jou nal Websi e: www.iji ee.o g
be dynamically adjus ed o he mic og id's cu en
ope a ing mode and DER con igu a ion, ensu ing
Enhanced Adap abili y e en unde a iable
condi ions.
▪ Inc eased Sys em Resilience: The abili y o
seamlessly ansi ion be ween g id-connec ed and
islanded modes is a key ac o in enhancing
mic og ids' esilience. This ea u e, along wi h
communica ion-based and decen alized a chi ec u es
and aul ide- h ough capabili ies p o ided by
in elligen elays, helps p e en cascading ailu es and
minimize powe ou ages.
▪ Robus ness o Communica ion Failu es: Se e al
p oposed schemes educe dependency on
high-bandwid h communica ion by employing local
measu emen echniques o edundan communica ion
channels, ensu ing con inued p o ec ion e en when
communica ion links a e comp omised.
IV. CONCLUSION
This sys ema ic e iew syn hesises ad ancemen s,
challenges, and gaps in mic og id p o ec ion, d awing on 55
con empo a y s udies. The e iew highligh s ha
bidi ec ional powe lows, a iable aul cu en s, and
dynamic opologies ende con en ional p o ec ion me hods
inadequa e. I also emphasizes ha while adap i e schemes,
communica ion-assis ed s a egies, and AI-d i en echniques
show p omise, hey in oduce complexi y, cybe secu i y
ulne abili ies, and scalabili y limi a ions. The e iew
sugges s hyb id sys ems, combining adi ional and
in elligen me hods, could o e a p agma ic balance, bu
in e ope abili y and cos ba ie s emain.
A. Resea ch Gaps and Fu u e Di ec ions
▪ Resilience Me ics: Only 10% o s udies add ess
esilience holis ically. Fu u e wo k mus in eg a e
s anda dized me ics (SAIDI, MTTR) wi h
DER-speci ic con ingencies and cybe -physical
in e ac ions.
▪ Real-Wo ld Valida ion: Wi h only 13% o s udies
alida ing indings expe imen ally, he need o ield
ials in di e se mic og id a che ypes (DC, hyb id)
becomes e en mo e c i ical. These ials a e essen ial
o assess scalabili y and eliabili y in p ac ical
se ings.
▪ Cybe secu i y: Communica ion-assis ed and AI
me hods emain ulne able o spoo ing and
ad e sa ial a acks. Quan um- esis an enc yp ion and
Mo ing Ta ge De ence (MTD) amewo ks equi e
u gen explo a ion.
▪ Sus ainabili y In eg a ion: P o ec ion s a egies
mus align wi h deca boniza ion goals. Op imizing
elay coo dina ion o minimize Ene gy No Se ed
(ENS) and enhance g id e iciency can make
signi ican s ides in sus ainabili y.
▪ Legacy Sys em Upg ades: Modula e o i ing o
elec omechanical elays wi h AI modules and 5G
communica ion could enable cos -e ec i e ansi ions
o adap i e p o ec ion.
▪ S anda diza ion: The absence o uni ied guidelines
o AI benchma king, hyb id sys em in e ope abili y,
and DER-g id synch oniza ion unde sco es he need
o IEEE/IEC-led ini ia i es.
B. A eas o Imp o emen
▪ Adap i e Th esholds: De elop dynamic elay
se ings using eal- ime DER o ecas ing o mi iga e
p o ec ion blinding.
▪ Explainable AI: Enhance us in in elligen me hods
h ough anspa en decision-making models.
▪ Cos -Bene i F amewo ks: E alua e he economic
iabili y o hyb id sys ems in u al e sus u ban
mic og ids.
▪ Decen alized A chi ec u es: Reduce
communica ion dependency ia ede a ed lea ning
and edge compu ing o dis ibu ed ne wo ks.
By add essing hese gaps, u u e esea ch can accele a e
he ansi ion om heo e ical inno a ion o esilien , scalable
mic og id p o ec ion sys ems, ensu ing eliable in eg a ion o
enewable ene gy in o mode n g ids.
DECLARATION STATEMENT
A e agg ega ing inpu om all au ho s, I mus e i y he
accu acy o he ollowing in o ma ion as he a icle's au ho .
▪ Con lic s o In e es / Compe ing In e es s: Based on
my unde s anding, his a icle has no con lic s o
in e es .
▪ Funding Suppo : This a icle has no been unded by
any o ganiza ions o agencies. This independence
ensu es ha he esea ch is conduc ed wi h objec i i y
and wi hou any ex e nal in luence.
▪ E hical App o al and Consen o Pa icipa e: The
con en o his a icle does no necessi a e e hical
app o al o consen o pa icipa e wi h suppo ing
documen a ion.
▪ Da a Access S a emen and Ma e ial
A ailabili y: The adequa e esou ces o his a icle a e
publicly accessible.
▪ Au ho ’s Con ibu ions: The au ho ship o his a icle
is con ibu ed equally o all pa icipa ing indi iduals.
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31
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Blue Eyes In elligence Enginee ing
and Sciences Publica ion (BEIESP)
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AUTHOR’S PROFILE
D . Houssem Ben A ibia ea ned his Bachelo 's and
Mas e 's Deg ees in Elec ical Enginee ing om he
Na ional School o Enginee s o S ax, Tunisia. In 2008,
he comple ed his PhD in Elec ical Enginee ing a he
same ins i u ion. F om 2009 o 2012, he se ed as a
esea che and assis an p o esso in he Elec ical
Enginee ing Depa men a he Na ional School o Enginee s o S ax,
Tunisia. Since 2012, he has been an associa e p o esso in he Elec ical and
Elec onics Enginee ing Depa men a he College o Enginee ing and
Compu e Science, Jazan Uni e si y, in Jazan, Saudi A abia.
D . Fe chichi Nou eddine holds a Bachelo ’s and
Mas e ’s deg ee in Elec ical Enginee ing om
Moguile College o Enginee ing, Bela us. In 1998, he
ea ned a PhD in Elec ical Machines and D i es om
Minsk S a e Poly echnic Academy, Bela us. F om 2000
o 2007, he se ed as a esea che and assis an
p o esso in he Elec ical Enginee ing Depa men a he Na ional High
Enginee ing School o Tunis, Tunisia. Since 2008, he has been an associa e
p o esso in he Elec ical and Elec onics Enginee ing Depa men a he
College o Enginee ing and Compu e Science, Jazan Uni e si y, Jazan,
Saudi A abia.
D . Slim Abid ea ned his Bachelo ’s Deg ee and
Mas e ’s Deg ee in Elec ical Enginee ing om he
Na ional School o Enginee s o S ax, Tunisia. In 2009,
I comple ed a PhD in Elec ical Enginee ing om he
Na ional School o Enginee s o S ax. F om 2010 o
2013, he was a esea che and assis an p o esso in he Elec ical
Enginee ing Depa men – Na ional School o Enginee s o S ax, Tunisia,
and om 2014 o he p esen , he has been an assis an p o esso in he
Elec ical and Elec onics Enginee ing Depa men , College o Enginee ing
and Compu e Science – Jazan Uni e si y, Jazan, Saudi A abia.
Disclaime /Publishe ’s No e: The s a emen s, opinions and da a
con ained in all publica ions a e solely hose o he indi idual
au ho (s) and con ibu o (s) and no o he Blue Eyes In elligence
Enginee ing and Sciences Publica ion (BEIESP)/ jou nal and/o he
edi o (s). The Blue Eyes In elligence Enginee ing and Sciences
Publica ion (BEIESP) and/o he edi o (s) disclaim esponsibili y
o any inju y o people o p ope y esul ing om any ideas,
me hods, ins uc ions o p oduc s e e ed o in he con en .