Improving voltage stability by optimal reactive power dispatch based on genetic algorithm and linear programming technique

Rayudu, K.; Yesuratnam, G.; Jayalaxmi, A.

doi:10.1109/iceeot.2016.7754904

Cited by 8 publications

(10 citation statements)

References 16 publications

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“…Recently, many metaheuristic methods inspired from nature phenomenon or behavior of animals have been more widely and successfully applied for solving such ORPD problem. Many methods have been continually grown and become a big family of methods like the variants of genetic algorithm (GA) [15][16][17][18][19], variants of differential evolution (DE) [20][21][22][23][24], variants of particle swarm optimization (PSO) [25][26][27][28][29][30][31], variants of gravitational search algorithm (GSA) [32][33][34][35], and many new standard methods [36][37][38][39][40][41][42][43][44][45][46][47][48][49]. In adaptive genetic algorithm (AGA) [15], the method changed both mutation probability and crossover probability based on comparison of the maximum fitness value and average fitness value of the population to enhance global search quality and fast convergence speed.…”

Section: Complexitymentioning

confidence: 99%

“…As a result, in the proposed technique, we suggest formulas like (15) and the first model in formula (16) should be canceled and replaced with more effective formulas. At the beginning, we introduce two new formulas (18) and (19), which are used to measure quality of each solution among the current population. In the two formulas, ûFF d is fitness function deviation between fitness function of the dth point FF(Point d ) and that of best point FF(Point best ) while ûFF mean is the fitness function deviation between mean fitness function of population FF mean and fitness function of the best point FF(Point best ).…”

Section: The Third Modificationmentioning

confidence: 99%

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Optimal Dispatch of Reactive Power Using Modified Stochastic Fractal Search Algorithm

Nguyen

Tran

et al. 2019

Complexity

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This paper applies a proposed modified stochastic fractal search algorithm (MSFS) for dealing with all constraints of optimal reactive power dispatch (ORPD) and finding optimal solutions for three different cases including power loss optimization, voltage deviation optimization, and L-index optimization. The proposed MSFS method is newly constructed in the paper by modifying three new solution update mechanisms on standard stochastic fractal search algorithm (SSFS). The first modification is to keep only one formula and abandon one formula in the diffusion process while the second modification and the third modification are used in the first update and the second update. In two updates of SSFS, solutions with low quality are updated with high probability while other solutions with high quality do not get chances to be updated. This manner results in the fact that some promising solutions around the high quality solutions can be missed. In order to tackle this restriction, the second modification of MSFS is to newly update the worst solutions in the first update and the best solutions in the second update. In the third modification, all existing formulas of SSFS in the two updates are abandoned and the same new proposed technique is used for updating such solutions in two updates. Compared to SSFS, the three modifications can bring advantages to MSFS such as using smaller number of produced solutions per iteration, spending shorter execution time, finding better optimal solutions, and owning more stable search ability. Furthermore, the proposed method also sees its effectiveness and robustness over SSFS by testing on IEEE 30-bus system and IEEE 118-bus system with three different single objectives for each system. The proposed method can find less minimum, average, and maximum for all the cases in addition to faster search speed. Besides, the proposed method is also compared to other methods such as PSO-based method group, GA-based method group, DE-based method group, and other recent methods. Result comparisons also indicate that the proposed method can be more efficient than almost all these methods with respect to less minimum and smaller values of control parameters. As a result, evaluation of the performance of the proposed method is that it should be used for seeking solutions of ORPD problem.

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Section: Complexitymentioning

confidence: 99%

Section: The Third Modificationmentioning

confidence: 99%

Optimal Dispatch of Reactive Power Using Modified Stochastic Fractal Search Algorithm

Nguyen

Tran

et al. 2019

Complexity

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“…The static VSI‐based method uses static VSIs such as VCPI [19–23], MSV [20, 24–26] and L‐index [20, 27–31] as an objective function or constraint of the OPF problem. Although these VSIs approximately indicate the proximity of the system to the voltage collapse point, there is no established way to determine the appropriate threshold value corresponding to the required VSM.…”

Section: Introductionmentioning

confidence: 99%

Modified tangent vector‐based voltage stability constrained optimal power flow considering limit‐induced bifurcation

Omi

Shirai

2020

IET Generation, Transmission & Distribution

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A modified tangent vector (TV)-based voltage stability constrained optimal power flow method is proposed. The proposed method determines an optimal stable equilibrium point (SEP) satisfying the required voltage stability margin (VSM) considering limit-induced bifurcation (LIB). LIB, which occurs when a generator reaches a reactive power limit during load increasing, may cause an optimistic overestimation of voltage stability and inadequate operation. The key of the proposed method is to use approximated TV for considering LIB as a voltage stability constraint to ensure that the solution becomes an SEP and to avoid inappropriate operation caused by LIB. The validity of the approximation is evaluated analytically and numerically in this study. The threshold for the approximated TV is updated based on the continuation power flow calculation result to satisfy the required VSM. The proposed method was implemented on MATPOWER, and evaluated with a 2-machine 4bus system and an IEEJ standard WEST10-O/V system. The results show that the proposed method can determine the optimal SEP satisfying the required VSM even if LIB occurs.

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“…In [6], Genetic Algorithm (GA) has been implemented to solve optimal reactive power dispatch problem in minimizing the total power loss in IEEE 30-bus system. On the other hand, GA has been implemented in [7] for solving optimal reactive power dispatch problem to improve voltage profile of a practical Indian power system. The research compares the optimized results using GA with optimization results provided by Linear Programming (LP) technique, which revealed that GA is capable to produce  ISSN:2502-4752 Indonesian J Elec Eng & Comp Sci, Vol.…”

Section: Introductionmentioning

confidence: 99%

“…1, January 2018 : 123-130 124 higher quality results compared to LP. Authors in [8] has attempted to solve the same problems as in [7] by using Particle Swarm Optimization (PSO) technique and comparative study was conducted with respect to LP technique, resulting in PSO providing better results compared to LP. PSO was further improved by several researchers where authors in [9] has implemented modified Evolutionary PSO (EPSO) to solve optimal reactive power dispatch problem while authors in [10] has modified the acceleration coefficient of PSO technique which then produce a technique known as PSO with time varying acceleration coefficients (PSO-TVAC).…”

Section: Introductionmentioning

confidence: 99%

Gravitational Search Algorithm Based Technique for Voltage Stability Improvement

Zamani¹,

Musirin²,

Omar³

et al. 2018

IJEECS

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<p>Voltage instability problem has been known as a significant threat to power system operation since its occurrence can lead to power interruption. This phenomenon can be due to uncontrollable load increment, line and generator outage contingencies or unplanned load curtailment. Optimal reactive power dispatch involving reactive power support can be one of the options for improving voltage stability of a power system, which also requires optimization process. Optimal sizing and location can of reactive power support can avoid the system from experiencing over-compensated or under-compensated phenomena. The presence of optimization techniques has helped solving non-optimal phenomenon, nevertheless some setbacks have also been experienced in terms of inaccuracy and stuck in local optima. This paper presents the application of Gravitational Search Algorithm (GSA) technique in attempt to solve optimal reactive power dispatch problem in terms of reactive power support for voltage stability improvement. Optimization process tested on IEEE 14-bus Reliability Test System (RTS) has revealed its superiority with significant promising results in terms of voltage stability improvement in the test system. </p>

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Improving voltage stability by optimal reactive power dispatch based on genetic algorithm and linear programming technique

Cited by 8 publications

References 16 publications

Optimal Dispatch of Reactive Power Using Modified Stochastic Fractal Search Algorithm

Optimal Dispatch of Reactive Power Using Modified Stochastic Fractal Search Algorithm

Modified tangent vector‐based voltage stability constrained optimal power flow considering limit‐induced bifurcation

Gravitational Search Algorithm Based Technique for Voltage Stability Improvement

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