A new-fangled adaptive mutation breeder genetic optimization of global multi-machine power system stabilizer

Linda, M. Mary; Nair, N. Kesavan

doi:10.1016/j.ijepes.2012.06.005

Cited by 31 publications

(3 citation statements)

References 16 publications

(19 reference statements)

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“…a PSS was designed and implemented on a weak connected three-machine test system. The work given in 19 proposes a GA that simultaneously adjusts multiple PSS. PSS designing is supposed to be unvaried including essentially lead-lag filters.…”

Section: Introductionmentioning

confidence: 99%

Improved chaotic Bat algorithm for optimal coordinated tuning of power system stabilizers for multimachine power system

Tadj,

Chaib,

Choucha

et al. 2024

Sci Rep

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Power systems exhibit nonlinearity. causing dynamic instability and complex power oscillations. This research proposes an innovative strategy using the Novel Bat Algorithm (NBA) to achieve ideal Power System Stabilizers (PSSs) in a multimachine power system. The approach shifts electromechanical modes to specific areas in the s-plane. Enhancing the multi-machine power system and establishing stabilizer parameters for dynamic performance. The study examines the designed approach aptitude for standard lead-lag PSSs configurations. In order to elevate the global search problem and transfer some static operators for the optimum optimization process. the chaos mapping. also known as CNBA. is introduced into NBA. Four different forms of chaos maps are compared in experiments to resolve unconstrained mathematical issues in order to illustrate CNBA performance. In any other case. the challenge of designing PSS under a wide range of loading situations is transformed into an optimization challenge with the damping ratio of electromechanical modes with low damping as the target function. The optimal stabilizers’ gains are gotten by employing the CNBA algorithm. Second plan. an effective technique is astutely established to delineate the PSS location and quantity using CNBA and another side using participation factor. To examine the efficacy of the proposed CNBA-based PSS on a large system; it is tested on the interconnected of New-England/New-York (16 generators and 68 buses) power grid. and verified by comparative study with NBA through eigenvalue analysis and nonlinear simulation to provide evidence the algorithmic competence of CNBA. The CNBA approach yields a minimum damping ratio of 37%. which is consistent with the its eigenvalue. In contrast, the NBA approach achieves a minimum damping ratio of 31%. The simulation results reveal the fine performance of the proposed CNBA-PSS in a convincing manner and its capacity to provide an excellent damping for inter-area and local oscillations under diverse operating cases compared to NBA-PSS then in the case of PSS location.

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Section: Introductionmentioning

confidence: 99%

Improved chaotic Bat algorithm for optimal coordinated tuning of power system stabilizers for multimachine power system

Tadj,

Chaib,

Choucha

et al. 2024

Sci Rep

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“…Meta-heuristic algorithms possess two important characteristics like intensification (or exploitation) and diversification (or exploration) is considered as upper-level methods for the optimization. Genetic algorithm [38,39] and particle swarm optimization [40,19,41] are the typical types of meta-heuristic algorithms for global optimization in the design of a power system stabilizer.…”

Section: Introductionmentioning

confidence: 99%

Design of Modified Maiden Power System Stabilizer Using Cuckoo Search Algorithm

Sambariya¹

2016

aep

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This article presents an improved maiden power system stabilizer (PSS) for enhancement of small signal stability of a power system. The free coefficients of proposed PSS are determined using optimization technique with the cuckoo search algorithms (CS-PSS). The performance of the CS-PSS is validated on single-machine infinite-bus power and extended to a multi-machine power system. These results are compared to the newly introduced maiden PSS structure and found superior in terms of settling time and performance indices.

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“…(Yassami, Darabi, & Rafiei, 2010) introduced a multi-objective optimization approach named strength parento approach for design PSS of power system. (Linda, & Nair, 2013) investigated the application of adaptive mutation breeder genetic algorithm to tune PSS parameters. However, the related parameters were not easy to set up and also the computation time was long.…”

Section: Introductionmentioning

confidence: 99%

Optimal Design of Single Machine Power System Stabilizer using Chemical Reaction Optimization Technique

Paul¹,

Roy²

2015

International Journal of Energy Optimization and Engineering

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PSSs are added to excitation systems to enhance the damping during low frequency oscillations. The non-linear model of a machine is linearized at different operating points. Chemical Reaction optimization (CRO), a new population based search algorithm is been proposed in this paper to damp the power system low-frequency oscillations and enhance power system stability. Computation results demonstrate that the proposed algorithm is effective in damping low frequency oscillations as well as improving system dynamic stability. The performance of the proposed algorithm is evaluated for different loading conditions. In addition, the proposed algorithm is more effective and provides superior performance when compared other population based optimization algorithms like differential evolution (DE) and particle swarm optimization (PSO).

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A new-fangled adaptive mutation breeder genetic optimization of global multi-machine power system stabilizer

Cited by 31 publications

References 16 publications

Improved chaotic Bat algorithm for optimal coordinated tuning of power system stabilizers for multimachine power system

Improved chaotic Bat algorithm for optimal coordinated tuning of power system stabilizers for multimachine power system

Design of Modified Maiden Power System Stabilizer Using Cuckoo Search Algorithm

Optimal Design of Single Machine Power System Stabilizer using Chemical Reaction Optimization Technique

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