Study of differential evolution for optimal reactive power flow

Liang, Changyong; Chung, C.Y.; Wong, Kit Po; Duan, Xianzhong; Tse, C.T.

doi:10.1049/iet-gtd:20060123

Cited by 103 publications

(35 citation statements)

References 21 publications

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“…To further verify the accuracy of the computed results from GA, The same optimal problems are also solved by differential evolution algorithms (DE) [18,19]. The computed results from DE are as follows.…”

Section: Computation Resultsmentioning

confidence: 99%

Estimation and management of magnetic flux density produced by underground cables in multiple‐circuit feeders

Lai

Yang

2010

Int Trans Elec Energy Syst

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SUMMARYThe purpose of this paper is to estimate and reduce the magnetic flux density of multiple-circuit underground cable feeders with randomly varying loads. The load in each phase of feeder circuits is assumed to be normally distributed. The probability distribution function of maximum magnetic flux density above the underground cable feeders is determined by using statistical approach. The optimal-phase arrangement of feeder circuits with minimum magnetic flux density is also explored by using the genetic algorithms (GA).

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Section: Computation Resultsmentioning

confidence: 99%

Estimation and management of magnetic flux density produced by underground cables in multiple‐circuit feeders

Lai

Yang

2010

Int Trans Elec Energy Syst

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“…Comparisons were made among EP, PSO, typical DE, and results were in favor of the proposed modified DE. In [49], DE was comprehensively studied in terms of concept, mechanism, and parameter setting for solving OPF problems. The effectiveness of parallel computing technology for speeding up the computation was also analyzed.…”

Section: Differential Evolution Based Approachmentioning

confidence: 99%

A review on applications of heuristic optimization algorithms for optimal power flow in modern power systems

Ming

Wan

2014

J. Mod. Power Syst. Clean Energy

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Optimal power flow (OPF) is one of the key tools for optimal operation and planning of modern power systems. Due to the high complexity with continuous and discrete control variables, modern heuristic optimization algorithms (HOAs) have been widely employed for the solution of OPF. This paper provides an overview of the latest applications of advanced HOAs in OPF problems. The most frequently applied HOAs for solving the OPF problem in recent years are covered and briefly introduced, including genetic algorithm (GA), differential evolution (DE), particle swarm optimization (PSO), and evolutionary programming (EP), etc.

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“…But, the big obstacle of PI controller is tuning its parameters ( , ). The methods are used to tune ( , ) parameters are the Ziegler Nichol's method [7] and trial-and-error approach [8], [9], but these are not efficient with systems have [10], practical swarm optimizations [11]- [15], ant colony optimization [16], and genetic algorithms [17], [18] have been widely applied for PI controller tuning in parallel-interconnected power systems.…”

Section: Introductionmentioning

confidence: 99%

An Optimal LFC in Two-Area Power Systems Using a Meta-heuristic Optimization Algorithm

Najeeb¹,

Mansor²,

Feyad³

et al. 2017

IJECE

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In this study, an optimal meta-heuristic optimization algorithm for load frequency control (LFC) is utilized in two-area power systems. This metaheuristic algorithm is called harmony search (HS), it is used to tune PI controller parameters ( , ) automatically. The developed controller (HS-PI) with LFC loop is very important to minimize the system frequency and keep the system power is maintained at scheduled values under sudden loads changes. Integral absolute error (IAE) is used as an objective function to enhance the overall system performance in terms of settling time, maximum deviation, and peak time. The two-area power systems and developed controller are modelled using MATLAB software (Simulink/Code). As a result, the developed control algorithm (HS-PI) is more robustness and efficient as compared to PSO-PI control algorithm under same operation conditions. Keyword:LFC Meta-heuristic optimization Algorithm (HS) Integral absolute error (IAE) MATLAB environment

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Study of differential evolution for optimal reactive power flow

Cited by 103 publications

References 21 publications

Estimation and management of magnetic flux density produced by underground cables in multiple‐circuit feeders

Estimation and management of magnetic flux density produced by underground cables in multiple‐circuit feeders

A review on applications of heuristic optimization algorithms for optimal power flow in modern power systems

An Optimal LFC in Two-Area Power Systems Using a Meta-heuristic Optimization Algorithm

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