An Extension of Particle Swarm Optimization (E-PSO) Algorithm for Solving Economic Dispatch Problem

Zakaria, Zaidi; Azmi, Azwan Iskandar; Laili, M. S.; Jamalil, Syed; Sulaiman, Mohd Herwan

doi:10.1109/aims.2013.32

Cited by 6 publications

(4 citation statements)

References 17 publications

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“…Untuk mengatasi masalah ini, beberapa metode heuristik telah terbukti keberhasilannya dalam menangani permasalahan ini yaitu constriction factor based particle swarm optimization (CFBPSO) dan kombinasi inertia weight contriction factor (IWCFPSO) [3], hybrid simulated annealing particle swarm optimization (SA-PSO) [4], multiple tabe search (MTS) [5], chaotic ant swarm optimization (CASO) [6], imperialist competitive algorithm (ICA) [7][8], extention particle swarm optimization (E-PSO) [9], differential evolution ant colony optimization (DE-ACO) [10], genetic algorithm (GA) [4]. Keunggulan dari metode GA terletak pada proses seleksi dan evaluasi yaitu crossover.…”

Section: Pendahuluanunclassified

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Pembangkitan Ekonomis pada Unit Pembangkit Listrik Tenaga Diesel Telaga Gorontalo Menggunakan Algoritma Genetika

Kanata¹

2017

JRE

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Section: Pendahuluanunclassified

“…Metode ini digunakan untuk mengatasi fungsi biaya yang bersifat non-linear dan menunjukkan metode ini lebih baik dengan PSO yang standar [9].…”

Section: Studi Pustakaunclassified

Pembangkitan Ekonomis pada Unit Pembangkit Listrik Tenaga Diesel Telaga Gorontalo Menggunakan Algoritma Genetika

Kanata¹

2017

JRE

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“…One crucial problem while applying Optimization to the ELD problem is that the solutions will not always satisfy the inequality and equality constraints simultaneously. Most ELD constraint optimization problems have adopted the Penalty Function Strategy (PFS) approach [17][18][19][20][21] to handling constraints because of its simple implementation. The penalty function approach involves several penalty parameters which need carefully determined tuning value to obtain a feasible solution.…”

Section: Introductionmentioning

confidence: 99%

The performance of COR optimisation using different constraint handling strategies to solve ELD

Azmi

Zali

Abdullah

et al. 2020

IJEECS

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This research compares the performance of Competitive Over Resources (COR) optimization method using a different type of constraint handling strategy to solve the economic load dispatch (ELD) problem. Previously, most research focused on proposing various optimization techniques using the Penalty Factor Strategy (PFS) to search for a better global optimum. The issue using the penalty factor is that it is difficult to find the correct tune of constant value that influences the algorithm to find the solution. The other technique is using Feasible Solution Strategy (FSS), the idea of which is to locate the infeasible particle to the feasible solution and avoid being trapped by the unsuccessful condition of constraint. This paper investigates the performance of PFS and FSS on the COR optimization method for solving ELD. Both strategies have been tested on two standard test systems to compare the performance in terms of a global solution, robustness and convergence. The simulation shows that FSS is a better solution compared to PFS.

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“…The proposed NBA has given a higher quality performance when it was applied for small scale power systems [3,4] . The NBA performance can be achieved by making comparison with other well-known optimization methods that they proved their efficiency and reliability in solving the EPD problem, such as Genetic Algorithm (GA) [5][6][7], Particle Swarm Optimization (PSO) [8][9][10][11] and Quadratic Programing (QP) [12][13][14], and the performance of NBA will be studied by comparing the obtained simulation results of it with the other optimization algorithms which they mentioned above.…”

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confidence: 99%

A New Bat Optimization Algorithm to Solve EPD Problem Solving with Transmission Loss

Rahebi

Al-jumaili

2020

Balkan Journal of Electrical and Computer Engineering

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While, researchers work to make the systems operate economically and reduce operational cost, in this study, we work to reduce the fuel costs to make the power station running economically as much as possible by utilizing the Economic Power Dispatch (EPD) and the optimization algorithms. The economic power dispatch (EPD) is an integral part of the power system, The major roles and the purpose of its use are for achieving a reliable and efficient operation out of power system generation networks, and this operation should be obtained by minimizing the generator fuel cost. Getting optimal solutions to EPD problem requires efficient optimization algorithms. Novel Bat Algorithm (NBA) is one of the most recent methods and it has already proven its efficiency and reliability for solving the EPD problem. This paper proposes Novel Bat Algorithm (NBA) in order to solve the EPD problem based on the large scale power system. The NBA has proved its efficiency and it gave a perfect performance for small-scale systems compared with the original Bat algorithm (BA), because of considering the Doppler Effect and assumed that bat can move between various habitats. The study of the EPD for large-scale power systems is more important than study it for small ones, because all power systems in countries are considered large networks. This is why all modern studies focus on the study of EPD for large systems. To test the performance of NBA during small and large scale power system, we have applied it to many systems, including 3thermal units, 6-thermal units, 31-Iraqi thermal units and IEEE 40-thermal units respectively, with transmission losses and generator limits, and we have made a comparison of the obtained results of NBA with other optimization methods. The Iraqi thermal units have been utilized as a new data.Index Terms-Novel Bat Algorithm (NBA), Economic Power Dispatch (EPD).

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An Extension of Particle Swarm Optimization (E-PSO) Algorithm for Solving Economic Dispatch Problem

Cited by 6 publications

References 17 publications

Pembangkitan Ekonomis pada Unit Pembangkit Listrik Tenaga Diesel Telaga Gorontalo Menggunakan Algoritma Genetika

Pembangkitan Ekonomis pada Unit Pembangkit Listrik Tenaga Diesel Telaga Gorontalo Menggunakan Algoritma Genetika

The performance of COR optimisation using different constraint handling strategies to solve ELD

A New Bat Optimization Algorithm to Solve EPD Problem Solving with Transmission Loss

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