Bacteria foraging optimization algorithm based load frequency controller for interconnected power system

Ali, E. S.; Elazim, S.M. Abd

doi:10.1016/j.ijepes.2010.12.022

Cited by 430 publications

(217 citation statements)

References 13 publications

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“…For example, Abd-Elazim and Ali proposed an optimization algorithm BFOA for controlling the damping of the power system's electromechanical oscillations [18]. On the basis of literature [18], Ali and Abd-Elazim proposed a BFOA based Load Frequency Control (LFC) for the suppression of oscillations in power system [19]. In addition, Abd-Elazim and Ali developed an optimization algorithm BSO, which synergistically coupled the BFOA with the particle swarm optimization algorithm for the optimal design of the TCSC damping controller.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Chaotic S‐Box: Intertwining Logistic Map and Bacterial Foraging Optimization

Tian

2017

Mathematical Problems in Engineering

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As the unique nonlinear component of block ciphers, Substitution box (S-box) directly affects the safety of a cryptographic system. It is important and difficult to design strong S-box that simultaneously meets multiple cryptographic criteria such as bijection, nonlinearity, strict avalanche criterion (SAC), bit independence criterion (BIC), differential probability (DP), and linear probability (LP). Though many chaotic S-boxes have been proposed, the cryptographic performance of most of them needs to be further improved. A new chaotic S-box based on the intertwining logistic map and bacterial foraging optimization is designed in this paper. It firstly iterates the intertwining logistic map to construct many S-boxes and then applies a bacterial foraging optimization algorithm to find the optimal S-box. Moreover, bacterial foraging optimization algorithm considers the nonlinearity and differential uniformity as the fitness functions in the optimization process. We experiment that the proposed S-box can effectively resist multiple types of cryptanalysis attacks.

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Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Chaotic S‐Box: Intertwining Logistic Map and Bacterial Foraging Optimization

Tian

2017

Mathematical Problems in Engineering

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“…Other bacteria are stimulated by the substance they secrete and they are allowed to move towards the food. If the nutrient density is high there, the bacteria move in groups as they clamp [21,[35][36][37].…”

Section: Bacterial Swarm Optimization Algorithmmentioning

confidence: 99%

Load-Frequency Optimization With Heuristic Techniques in a Autonomous Hybrid Ac Microgrid

Öztürk¹,

Çelik²,

Özdemir³

2017

IJESG

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“…This analysis led to the establishment of tables used in the calculation of P, I and D from simple measurements [6]. Several other works have been proposed for tuning the PI and PID controller parameters such as Genetic Algorithm (GA) [12][13], Particle Swarm Optimization (PSO) [14], Bacterial Foraging Optimization Algorithm (BFOA) [15][16], Differential Evolution Algorithm (DEA) [11][12][13][14][15][16][17], Firefly Algorithm (FA) [18], H-infinity technique [19] and Gravitational Search Algorithm (GSA) [20]. A significant number of the published works attempted to apply the Fuzzy Logic and multi-stage Fuzzy [21].…”

Section: Introductionmentioning

confidence: 99%

A New Optimal Load Frequency Control Based on Hybrid Genetic Algorithm and Particle Swarm Optimization

Kouba¹,

Menaa²,

Hasni³

et al. 2017

ijeei

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This paper proposes an application of a new hybrid approach combining Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to optimal Load Frequency Control (LFC) design in interconnected power system. The proposed hybrid GA-PSO technique was applied to obtain the Proportional-Integral-Derivative (PID) controller parameters. The random nature of the GA operators makes the algorithm sensitive to initial population. However the GA algorithm may not converge if the initial population is not well selected. On other hand, PSO was shown to converge rapidly during the initial stages of a global search, but around global optimum, the search process will become very slow. The main idea of this paper is to propose a new algorithm which combines GA and PSO to solve the frequency regulation problem in interconnected power system. Time domain performance of the LFC controller, such as the maximum overshoot and settling time are being optimized based on the performance criteria like the Integral Square Error (ISE), Integral Absolute Error (IAE), Integral Time multiply Absolute Error (ITAE) and Integral Time multiply Square Error (ITSE), or their combination. To verify the effectiveness of the proposed algorithm, initially a two-area power system is used then the proposed approach was extended to the three-area interconnected power system. The obtained simulation results are compared to those yielded by the other classical and heuristic optimization techniques surfaced in the recent state-of-the-art literature. The comparative study demonstrates the validity and the potential of the proposed approach and shows its robustness to solve the optimal LFC problem.

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Bacteria foraging optimization algorithm based load frequency controller for interconnected power system

Cited by 430 publications

References 13 publications

Chaotic S‐Box: Intertwining Logistic Map and Bacterial Foraging Optimization

Chaotic S‐Box: Intertwining Logistic Map and Bacterial Foraging Optimization

Load-Frequency Optimization With Heuristic Techniques in a Autonomous Hybrid Ac Microgrid

A New Optimal Load Frequency Control Based on Hybrid Genetic Algorithm and Particle Swarm Optimization

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