An improved moth‐flame optimization algorithm for solving optimal power flow problem

Summary This paper proposes an improved moth flame optimization (IMFO) algorithm to effectively solve the optimal power flow (OPF) problems. The concept of moth flame optimization (MFO) is inspired from the movement of moth towards the moon direction. IMFO is mainly based on the concept of MFO with...

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Vydáno v:International transactions on electrical energy systems Ročník 29; číslo 3; s. e2743 - n/a
Hlavní autoři: Taher, Mahrous A., Kamel, Salah, Jurado, Francisco, Ebeed, Mohamed
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hoboken John Wiley & Sons, Inc 01.03.2019
Témata:
Algorithms
Butterflies & moths
Computer simulation
Convergence
Electric potential
Emissions control
improved moth flame optimization
metaheuristic
Moon
optimal power flow
Optimization
Optimization techniques
Power flow
Power loss
power system optimization
Robustness
Spirals
Voltage stability
ISSN:2050-7038, 2050-7038
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Abstract Summary This paper proposes an improved moth flame optimization (IMFO) algorithm to effectively solve the optimal power flow (OPF) problems. The concept of moth flame optimization (MFO) is inspired from the movement of moth towards the moon direction. IMFO is mainly based on the concept of MFO with modifying the path of moths in new spirals around the flame. Standard IEEE 30‐bus, IEEE 57‐bus and IEEE 118‐bus test systems are used to validate and prove the efficiency and robustness of IMFO algorithm. The validation of the proposed algorithm is based on 15 case studies in terms of different single and multi‐objective functions: fuel cost minimization, gas emission reduction, active power loss minimization, voltage profile improvement, and voltage stability enhancement. The simulation results of the proposed algorithm are compared with those obtained by other well‐known optimization techniques. The obtained results demonstrate the capability and robustness of IMFO algorithm to solve OPF problems. The results reveal that IMFO algorithm is capable of finding precise and better OPF solutions compared with the other techniques. A comparison among the convergence characteristics of IMFO technique and the other techniques proves the prevalence of IMFO to attain the optimal power flow solution with fast convergence.
AbstractList This paper proposes an improved moth flame optimization (IMFO) algorithm to effectively solve the optimal power flow (OPF) problems. The concept of moth flame optimization (MFO) is inspired from the movement of moth towards the moon direction. IMFO is mainly based on the concept of MFO with modifying the path of moths in new spirals around the flame. Standard IEEE 30‐bus, IEEE 57‐bus and IEEE 118‐bus test systems are used to validate and prove the efficiency and robustness of IMFO algorithm. The validation of the proposed algorithm is based on 15 case studies in terms of different single and multi‐objective functions: fuel cost minimization, gas emission reduction, active power loss minimization, voltage profile improvement, and voltage stability enhancement. The simulation results of the proposed algorithm are compared with those obtained by other well‐known optimization techniques. The obtained results demonstrate the capability and robustness of IMFO algorithm to solve OPF problems. The results reveal that IMFO algorithm is capable of finding precise and better OPF solutions compared with the other techniques. A comparison among the convergence characteristics of IMFO technique and the other techniques proves the prevalence of IMFO to attain the optimal power flow solution with fast convergence.
Summary This paper proposes an improved moth flame optimization (IMFO) algorithm to effectively solve the optimal power flow (OPF) problems. The concept of moth flame optimization (MFO) is inspired from the movement of moth towards the moon direction. IMFO is mainly based on the concept of MFO with modifying the path of moths in new spirals around the flame. Standard IEEE 30‐bus, IEEE 57‐bus and IEEE 118‐bus test systems are used to validate and prove the efficiency and robustness of IMFO algorithm. The validation of the proposed algorithm is based on 15 case studies in terms of different single and multi‐objective functions: fuel cost minimization, gas emission reduction, active power loss minimization, voltage profile improvement, and voltage stability enhancement. The simulation results of the proposed algorithm are compared with those obtained by other well‐known optimization techniques. The obtained results demonstrate the capability and robustness of IMFO algorithm to solve OPF problems. The results reveal that IMFO algorithm is capable of finding precise and better OPF solutions compared with the other techniques. A comparison among the convergence characteristics of IMFO technique and the other techniques proves the prevalence of IMFO to attain the optimal power flow solution with fast convergence.
Author Kamel, Salah
Jurado, Francisco
Taher, Mahrous A.
Ebeed, Mohamed
Author_xml – sequence: 1
  givenname: Mahrous A.
  surname: Taher
  fullname: Taher, Mahrous A.
  organization: Hydro Power Plants Company
– sequence: 2
  givenname: Salah
  surname: Kamel
  fullname: Kamel, Salah
  organization: Aswan University
– sequence: 3
  givenname: Francisco
  orcidid: 0000-0001-8122-7415
  surname: Jurado
  fullname: Jurado, Francisco
  email: fjurado@ujaen.es
  organization: University of Jaén
– sequence: 4
  givenname: Mohamed
  surname: Ebeed
  fullname: Ebeed, Mohamed
  organization: Sohag University
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Snippet Summary This paper proposes an improved moth flame optimization (IMFO) algorithm to effectively solve the optimal power flow (OPF) problems. The concept of...
This paper proposes an improved moth flame optimization (IMFO) algorithm to effectively solve the optimal power flow (OPF) problems. The concept of moth flame...
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StartPage e2743
SubjectTerms Algorithms
Butterflies & moths
Computer simulation
Convergence
Electric potential
Emissions control
improved moth flame optimization
metaheuristic
Moon
optimal power flow
Optimization
Optimization techniques
Power flow
Power loss
power system optimization
Robustness
Spirals
Voltage stability
Title An improved moth‐flame optimization algorithm for solving optimal power flow problem
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fetep.2743
https://www.proquest.com/docview/2190733210
Volume 29
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