Modified Shuffled Frog Leaping Algorithm for Solving Economic Load Dispatch Problem

Abstract

In the recent restructured power system scenario and complex market strategy, operation at absolute minimum cost is no longer the only criterion for dispatching electric power. The economic load dispatch (ELD) problem which accounts for minimization of both generations cost and power loss is itself a multiple conflicting objective function problem. In this paper, a modified shuffled frog-leaping algorithm (MSFLA), which is an improved version of memetic algorithm, is proposed for solving the ELD problem. It is a relatively new evolutionary method where local search is applied during the evolutionary cycle. The idea of memetic algorithm comes from memes, which unlike genes can adapt themselves. The performance of MSFLA has been shown more efficient than traditional evolutionary algorithms for such type of ELD problem. The application and validity of the proposed algorithm are demonstrated for IEEE 30 bus test system as well as a practical power network of 203 bus 264 lines 23 machines system.

Frog Inspired Algorithms

“…• Power system optimization (Rameshkhah et al 2010a(Rameshkhah et al , b, 2011Nejad et al 2010a;Gómez-González and Jurado 2011;Narimani 2011;Sedighizadeh et al 2011;Payam et al 2011;Bijami et al 2011;Jahani et al 2010, Jahani et al 2011aJalilzadeh et al 2011;Ebrahimi et al 2011;Yammani et al 2012;Malekpour et al 2012;Niknam and Farsani 2010;Nejad et al 2010b;Niknam et al 2011aNiknam et al , b, c, 2012bKhorsandi et al 2011;Roy and Chakrabarti 2011).…”

Wind power optimization using modified memetic algorithm

“…Our MSFLA framework adheres to the same principles as the original SFLA. For a visual representation, refer to Figure 3, which outlines the flowchart of our proposed algorithm, adapted from references [13][14].…”

“…MSFLA techniques are newly introduced in [12]. The applications of MSFLA are found in [13][14][15][16][17]. It combines the advantages of the genetic-based memetic algorithm (MA) and the social behavior-based Particle Swarm Optimization (PSO) algorithm.…”

Optimal Generation Dispatch of Ethiopian Power System Using Hybrid Genetic Algorithm-Hopfield Neural Network

“…The new vector Uij (t+1) is selected based on the comparison of fitness of both target vector, Pi and trial vector, Ui. Compute generation after generation to meet the stopping criteria tmax [29].…”