Economic Load Dispatch with Multiple Fuel Options and Valve Point Effect Using Cuckoo Search Algorithm with Different Distributions

Tran, Cuong Dinh; Dao, Tam Thanh; Vo, Ve Song; Nguyen, Thang Trung

doi:10.14257/ijhit.2015.8.1.27

Cited by 16 publications

(8 citation statements)

References 14 publications

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“…A meta-heuristic approach based on the insect's casual nature like Cuckoo and Levy have been developed known as Cuckoo Search Algorithms (CSA), [31]. In [32] and [33] a detailed review of different modifications of Cuckoo algorithms discussed for the purpose of optimization and its significance in the research.…”

Section: Related Workmentioning

confidence: 99%

Economic Dispatch Solution for Generating Units through Optimization

Nazeer¹,

Jamil²,

Mohsin³

et al. 2020

IJEW

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The complex nature of the modern power system is because of the interconnection of the generating units and day by day increased load demand. The main purpose of the power system is to tantalize the load needs and generate reliable and cheap energy i.e. cost of generation should be optimum i.e. operating every generating unit in such a way to optimize the cost. The cost function of every generating unit is different from other generating unit, so load has to be divided among various generating units to obtain optimum generation. The optimization of power system is done by Economic load dispatch (ELD). ELD is of immense importance in power system operation and planning (PSOP). The primary purpose of ELD is to pacify the load needs at lowest cost while satiating all kind of equality and inequality constraints. Power system has highly non-linear input output characteristics because of different generation constraints. In ELD cost function of each and every generating unit is equated as quadratic function. Numerous methods have been devised to figure out ELD problem incorporating conventional methods like Lambda iteration method and Gradient method, and artificial intelligent method like Particle Swarm Optimization, Generic Algorithms etc. In this thesis optimization of generating units is done through General Algebraic Modelling System (GAMS). GAMS is a modelling system used for mathematical programming and optimization on a large scale. It helps to develop a mathematical model similar to their corresponding mathematical expression and gives more accurate results.

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Section: Related Workmentioning

confidence: 99%

Economic Dispatch Solution for Generating Units through Optimization

Nazeer¹,

Jamil²,

Mohsin³

et al. 2020

IJEW

View full text Add to dashboard Cite

show abstract

“…of iterations = 800, Crossover rate (CR) = 0.6, Mutation factor (MF) = 0.5 and the results are presented after 30 trials. Table 6 shows the results obtained from the proposed SDE in solving non-convex PED problem for the 2700 MW power demand and are compared to other optimizers in literature such as Improved Genetic Algorithm with Multiplier Updating (IGA_MU) [28], Modified Shuffled Frog Leaping Algorithm (MSFLA) [40], Particle Swarm Optimization (PSO) [49], conventional DE [49], Real-coded Genetic Algorithm (RGA) [49], New Particle Swarm Optimization with Local Random Search (NPSO-LRS) [50], Back-tracking Search Algorithm (BSA) [51], Cuckoo Search Algorithm with Cauchy distribution (CSA-Cauchy) [52] and BAT [16]. Table 7 shows the simulation results of SDE for the power demand of 2600 MW and are compared with conventional PSO [49], RGA [49], DE [49], MSFLA [40], Global-best Harmony Search (GHS) [40], BAT [16], SaDE [32].…”

Section: System 2: 10 Machine Multiple Fuel Non-convex Ped (With Valvmentioning

confidence: 99%

Multiple Fuel Machines Power Economic Dispatch Using Stud Differential Evolution

et al. 2018

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This paper presents an optimization method for solving the Power Economic Dispatch (PED) problem of thermal generation units with multiple fuels and valve point loadings. The proposed optimizer is a variant of Differential Evolution (DE) characterized as a Stud Differential Evolution (SDE), which has been proposed earlier and implemented on a hydrothermal energy system. In SDE, an operator named Stud Crossover (SC) is introduced in the conventional DE during the trial vector updating process. In SC operator, a best vector gives its optimal information to all other population members through mating. The proposed algorithm's effectiveness to solve Multiple Fuel PED problem, with and without Valve Point Loading Effects (VPLEs), has been validated by testing it on 10 machine multiple fuel standard test systems having 2400 MW, 2500 MW, 2600 MW, and 2700 MW load demands. The results depict the strength of SDE over various other methods in the literature.

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“…In Cuckoo Search Algorithm (CSA), the natural phenomena of cuckoo species and Levy flights has been considered and is widely applied on the various optimization problems. Tran et al [16] in its work modifies CSA by using two distributions including Gaussian distribution and Cauchy's distribution to solve the economic dispatch problem with multi fuel options and valve point loading effects. Direct search methods like simplex search method, pattern search method, Powell's method and others are also integrated with the optimization methods to improve the results at local minima [17].…”

Section: Introductionmentioning

confidence: 99%

Economic Power Dispatch using Hybrid Particle Swarm Optimization with Simplex Search Method

2020

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This paper presents the solution of economic power dispatch (EPD) in thermal power plants using the hybridization of particle swarm optimization (PSO) and simplex search method (SSM). EPD is obtaining the best generating schedule to supply the power demand and covering the transmission losses with minimum overall fuel cost. Physical constraints like valve point loading effects, ramp rate limits and prohibited operating zones are also included with basic EPD problem to increase the practicability in the problem. As PSO performs well in finding the global best solution and SSM in finding the local best solution, thus their combination improves the overall minimum results obtained for the generation fuel cost objective function. The performance of the proposed methodology is tested on different test systems having categories of small-scale, medium-scale and large-scale power system problems. The results obtained are then compared with other reported methods to show the superiority of the proposed algorithm.

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Economic Load Dispatch with Multiple Fuel Options and Valve Point Effect Using Cuckoo Search Algorithm with Different Distributions

Abstract: Cuckoo Search Algorithm (CSA), a new meta-heuristic algorithm based on natural phenomenon of Cuckoo species and

Cited by 16 publications

References 14 publications

Economic Dispatch Solution for Generating Units through Optimization

Economic Dispatch Solution for Generating Units through Optimization

Multiple Fuel Machines Power Economic Dispatch Using Stud Differential Evolution

Economic Power Dispatch using Hybrid Particle Swarm Optimization with Simplex Search Method

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