DSPSO–TSA for economic dispatch problem with nonsmooth and noncontinuous cost functions

Khamsawang, S.; Jiriwibhakorn, Somchat

doi:10.1016/j.enconman.2009.09.034

Cited by 111 publications

(49 citation statements)

References 18 publications

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“…Then, the updated distance is employed to be substituted into another (19) to calculate a new attractiveness. Then, the new position for the ith considered firefly can be determined corresponding to the generation of a new solution of the ith solution.…”

Section: Firefly Algorithmsmentioning

confidence: 99%

“…Equations (18), (19), and (20) continues to be determined for the ith solution until there are no more solutions that have lower fitness function.…”

Section: Firefly Algorithmsmentioning

confidence: 99%

“…However, the speed comparisons have been made only via execution time, leading to not good comparison criteria for conclusion. Different test systems considering constraints of transmission power network have been used to test the efficiency of PSO variants in [17][18][19]. PSO with pseudo-gradient and constriction factor (PG-CF-PSO) [17] has determined the best direction for updating velocity by using pseudo-gradient theory and used constriction factor to find good search zone.…”

Section: Introductionmentioning

confidence: 99%

“…These methods have had worse results than NAPSO but better results than standard PSO. Combination of particle swarm optimization and tabu search algorithm (PSO-TSA) [19] has used the ability of PSO for local search based on three different phases and TSA for global search by adjusting obtained solutions of PSO. The method has been compared to three difference implemented methods such as GA, PSO, and TSA, and it can be shown better objective function.…”

Section: Introductionmentioning

confidence: 99%

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Improved Firefly Algorithm: A Novel Method for Optimal Operation of Thermal Generating Units

2018

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This paper presents a novel improved firefly algorithm (IFA) to deal the problem of the optimal operation of thermal generating units (OOTGU) with the purpose of reducing the total electricity generation fuel cost. The proposed IFA is developed based on combining three improvements. The first is to be based on the radius between two solutions, the second is updated step size for each considered solution based on different new equations, and the third is to slightly modify a formula producing new solutions by using normally distributed random numbers and canceling uniform random numbers of conventional firefly algorithm (FA). The effect of each proposed improvement on IFA is investigated by executing five benchmark functions and two different systems. The performance of IFA is investigated on six other study cases consisting of different types of objective function and complex level of constraints. The objective function considers single fuel with quadratic form and nonconvex form, and multifuels with the sum of several quadratic and nonconvex functions while a set of constraints taken into account are power loss, prohibited zone, ramp rate limit, spinning reserve, and all constraints in transmission power networks. The obtained results indicate the proposed improvements in terms of high optimal solution quality, stabilization of search ability, and fast convergence compared with FA. In addition, the comparisons with other methods also lead to a conclusion that the proposed method is a very promising optimization tool for systems with quadratic fuel cost function and with complicated constraints.

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Section: Firefly Algorithmsmentioning

confidence: 99%

“…Equations (18), (19), and (20) continues to be determined for the ith solution until there are no more solutions that have lower fitness function.…”

Section: Firefly Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Improved Firefly Algorithm: A Novel Method for Optimal Operation of Thermal Generating Units

2018

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“…Transmission losses are ignored and system date can be found in [29]. The experimental results are also compared with other algorithms reported in literature, including CGA_MU [2], IGA_MU [2], ACO [5], ED-DE [32], ARCGA [33], PSO-GM [25], NPSO [24], NPSO-LRS [24], PSO-GM [25], CBPSO-RVM [25], APSO [27], GA [34], DSPSO-TSA [34], which are given in Table 5. It can be seen that SQPSO can get a minimum generation cost of 623.8319($/H), which is the best solution among all the methods.…”

Section: The Ed Problem With Multi-fuel Option and Valve-point Effectsmentioning

confidence: 99%

An Improved Quantum-Behaved Particle Swarm Optimization Method for Economic Dispatch Problems with Multiple Fuel Options and Valve-Points Effects

et al. 2012

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Quantum-behaved particle swarm optimization (QPSO) is an efficient and powerful population-based optimization technique, which is inspired by the conventional particle swarm optimization (PSO) and quantum mechanics theories. In this paper, an improved QPSO named SQPSO is proposed, which combines QPSO with a selective probability operator to solve the economic dispatch (ED) problems with valve-point effects and multiple fuel options. To show the performance of the proposed SQPSO, it is tested on five standard benchmark functions and two ED benchmark problems, including a 40-unit ED problem with valve-point effects and a 10-unit ED problem with multiple fuel options. The results are compared with differential evolution (DE), particle swarm optimization (PSO) and basic QPSO, as well as a number of other methods reported in the literature in terms of solution quality, convergence speed and robustness. The simulation results confirm that the proposed SQPSO is effective and reliable for both function optimization and ED problems.

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Solving economic load dispatch problems using chaotic self-adaptive differential harmony search algorithm

Rajagopalan

Sengoden

Ravi

2014

Int. Trans. Electr. Energ. Syst.

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Summary In this paper, two improved differential harmony search algorithms called self‐adaptive differential harmony search (SADHS) algorithm and chaotic SADHS (CSADHS) algorithm are proposed to solve economic load dispatch problems with valve‐point effect, ramp‐rate limits, prohibited operating zones, and multiple fuel options. The effectiveness and suitability of the proposed algorithms are demonstrated on test systems consisting of 13, 15, and 40 generating units with valve‐point effect and 10 generating units with multiple fuel options and valve‐point effect. The simulation results obtained by the proposed algorithms are compared with the results obtained using DHS and with the results of other methods reported in the literature. The solution obtained by the proposed CSADHS algorithm is found to be better than the other methods in terms of solution quality. In terms of convergence speed and computation time, the proposed CSADHS algorithm is better than DHS and the other proposed SADHS algorithms. Copyright © 2014 John Wiley & Sons, Ltd.

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DSPSO–TSA for economic dispatch problem with nonsmooth and noncontinuous cost functions

Cited by 111 publications

References 18 publications

Improved Firefly Algorithm: A Novel Method for Optimal Operation of Thermal Generating Units

Improved Firefly Algorithm: A Novel Method for Optimal Operation of Thermal Generating Units

An Improved Quantum-Behaved Particle Swarm Optimization Method for Economic Dispatch Problems with Multiple Fuel Options and Valve-Points Effects

Solving economic load dispatch problems using chaotic self-adaptive differential harmony search algorithm

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