A comprehensive review of microgrid control methods: Focus on AI, optimization, and predictive techniques

•A review of recent control techniques, with a focus on AI, optimization, and predictive methods, is presented.•Control techniques are reviewed based on the control objectives, architecture, and microgrid characteristics.•This assessment highlights the benefits and limitations of various control met...

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Vydáno v:Computers & electrical engineering Ročník 125; s. 110442
Hlavní autoři: Limouni, Tariq, Yaagoubi, Reda, Bouziane, Khalid, Guissi, Khalid, Baali, El Houssain
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.07.2025
Témata:
Artificial intelligence
Fault detection
Hybrid control technique
Metaheuristics algorithms
Microgrid control
Model predictive control
Optimization algorithms
Power and energy management
MPC
DE
DEMPC
DG
MILP
LP
PV
LR
ELN
ELM
Optimization algorithms
DL
QTLBO
AWPSO
CDM
BBO
MLP
DT
Model predictive control
BPNN
HDMPC
RNN
FFT
MB
ssNN
MG
FS-MPC
ANFIS
LSA
DMPC
QP
ML
BSO
MIQP
FFNN
AC
HSO
SMA
AI
EMS
AIS
VSG
PSO
SFLA
FCN
EV
MIP
GAN
FPA
RL
FA
EMPC
HBMO
MAS
BA
ANN
CNN
ABC
Microgrid control
SoC
MVO
BHO
SVM
FHO
COOT
SA
CSA
Metaheuristics algorithms
GSA
ISA
GOA
GA
SFO
GWO
LSTM
ESS
WOA
MINLP
PID
kNN
SMPC
Power and energy management
ACO
RCGA
SSO
SCA
DER
Fault detection
WCA
BAS
ARIMA
PI
Hybrid control technique
Artificial intelligence
DC
ISSN:0045-7906
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Abstract •A review of recent control techniques, with a focus on AI, optimization, and predictive methods, is presented.•Control techniques are reviewed based on the control objectives, architecture, and microgrid characteristics.•This assessment highlights the benefits and limitations of various control methods.•This review explores the potential and challenges for hybridizing control techniques and emphasizes the need for more intelligent solutions.•Key research directions for future studies on microgrid control were identified. With the depletion of fossil fuels, the integration of renewable energy sources as distributed energy resources has become mandatory. However, the uncertainty and intermittent nature of these sources introduce significant challenges to their integration into microgrids. Effective control systems are essential for ensuring smooth integration, managing energy storage systems, and maintaining microgrid safety. In this study, a review of recent control methods applied in microgrid management was conducted with a focus on AI, optimization, and predictive techniques. These advanced and intelligent control methods were chosen for their potential to address current challenges. This study examined the benefits, limitations, and areas for future improvement. In addition, it explores the potential and the challenges of hybrid control techniques, which are less discussed in the literature, to further enhance control system efficiency and performance.
AbstractList •A review of recent control techniques, with a focus on AI, optimization, and predictive methods, is presented.•Control techniques are reviewed based on the control objectives, architecture, and microgrid characteristics.•This assessment highlights the benefits and limitations of various control methods.•This review explores the potential and challenges for hybridizing control techniques and emphasizes the need for more intelligent solutions.•Key research directions for future studies on microgrid control were identified. With the depletion of fossil fuels, the integration of renewable energy sources as distributed energy resources has become mandatory. However, the uncertainty and intermittent nature of these sources introduce significant challenges to their integration into microgrids. Effective control systems are essential for ensuring smooth integration, managing energy storage systems, and maintaining microgrid safety. In this study, a review of recent control methods applied in microgrid management was conducted with a focus on AI, optimization, and predictive techniques. These advanced and intelligent control methods were chosen for their potential to address current challenges. This study examined the benefits, limitations, and areas for future improvement. In addition, it explores the potential and the challenges of hybrid control techniques, which are less discussed in the literature, to further enhance control system efficiency and performance.
ArticleNumber 110442
Author Limouni, Tariq
Yaagoubi, Reda
Bouziane, Khalid
Baali, El Houssain
Guissi, Khalid
Author_xml – sequence: 1
  givenname: Tariq
  orcidid: 0000-0002-5781-4510
  surname: Limouni
  fullname: Limouni, Tariq
  email: t.limouni@iav.ac.ma
  organization: Energy and Agro-equipment Department, Hassan II Institute of Agronomy and Veterinary, Rabat 10112, Morocco
– sequence: 2
  givenname: Reda
  surname: Yaagoubi
  fullname: Yaagoubi, Reda
  organization: School of Geomatics and Surveying Engineering, Hassan II Institute of Agriculture and Veterinary Medicine, Rabat 10112, Morocco
– sequence: 3
  givenname: Khalid
  orcidid: 0000-0001-6924-2495
  surname: Bouziane
  fullname: Bouziane, Khalid
  organization: LERMA, Higher School of Energy Engineering International University of Rabat Campus de l’UIR, Parc Technopolis Rocade de Rabat-Salé 11100 Sala Al Jadida, Morocco
– sequence: 4
  givenname: Khalid
  surname: Guissi
  fullname: Guissi, Khalid
  organization: Energy and Agro-equipment Department, Hassan II Institute of Agronomy and Veterinary, Rabat 10112, Morocco
– sequence: 5
  givenname: El Houssain
  surname: Baali
  fullname: Baali, El Houssain
  organization: Energy and Agro-equipment Department, Hassan II Institute of Agronomy and Veterinary, Rabat 10112, Morocco
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Keywords MPC
DE
DEMPC
DG
MILP
LP
PV
LR
ELN
ELM
Optimization algorithms
DL
QTLBO
AWPSO
CDM
BBO
MLP
DT
Model predictive control
BPNN
HDMPC
RNN
FFT
MB
ssNN
MG
FS-MPC
ANFIS
LSA
DMPC
QP
ML
BSO
MIQP
FFNN
AC
HSO
SMA
AI
EMS
AIS
VSG
PSO
SFLA
FCN
EV
MIP
GAN
FPA
RL
FA
EMPC
HBMO
MAS
BA
ANN
CNN
ABC
Microgrid control
SoC
MVO
BHO
SVM
FHO
COOT
SA
CSA
Metaheuristics algorithms
GSA
ISA
GOA
GA
SFO
GWO
LSTM
ESS
WOA
MINLP
PID
kNN
SMPC
Power and energy management
ACO
RCGA
SSO
SCA
DER
Fault detection
WCA
BAS
ARIMA
PI
Hybrid control technique
Artificial intelligence
DC
Language English
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PublicationTitle Computers & electrical engineering
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SubjectTerms Artificial intelligence
Fault detection
Hybrid control technique
Metaheuristics algorithms
Microgrid control
Model predictive control
Optimization algorithms
Power and energy management
Title A comprehensive review of microgrid control methods: Focus on AI, optimization, and predictive techniques
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