Application Of Computational Intelligence Techniques For Economic Load Dispatch

Swain, Sarat Chandra; Panda, Sanjib Kumar; Mohanty, A.R.; Ardil, Cemal

doi:10.5281/zenodo.1056689

Cited by 3 publications

(1 citation statement)

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“…12, No. 2, April 2022: 1131-1138 1132 generation system is one that allows for a shift from a demand-driven generation system to one based on electricity supply, feed-in tariffs and electrical energy storage [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

Statistical modeling and optimal energy distribution of cogeneration units by genetic algorithms

Maakoul

Omari

Abid

2022

IJECE

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Our main objective is to evaluate the performance of a new method to optimize the energy management of a production system composed of six cogeneration units using artificial intelligence. The optimization criterion is economic and environmental in order to minimize the total fuel cost, as well as the reduction of polluting gas emissions such as COx, NOx and SOx. First, a statistical model has been developed to determine the power that the cogeneration units can provide. Then, an economic model of operation was developed: fuel consumption and pollutant gas emissions as a function of the power produced. Finally, we studied the energy optimization of the system using genetic algorithms (GA), and contribute to the research on improving the efficiency of the studied power system. The GA has a better optimization performance, it can easily choose satisfactory solutions according to the optimization objectives, and compensate for these defects using its own characteristics. These characteristics make GA have outstanding advantages in iterative optimization. The robustness of the proposed algorithm is validated by testing six cogeneration units, and the obtained simulation results of the proposed system prove the value and effectiveness of GA for efficiency improvement as well as operating cost minimization.

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Section: Introductionmentioning

confidence: 99%

Statistical modeling and optimal energy distribution of cogeneration units by genetic algorithms

Maakoul

Omari

Abid

2022

IJECE

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Economic load dispatch calculator

Singh

Deepika

Kumar³

2014

2014 6th IEEE Power India International Conference (PIICON)

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This paper presents a software package tool designed using a MATLAB GUI for solving economic load dispatch problem. This proposed software tool help user to modify the input detail according to the requirements of the power system operation for optimization of generating cost.This could be explained bysolving economic load dispatch problem using conventional techniques, i.e. proportional load division,Lagrange multiplier and population based, i.e. PSO with real time coal quality as an additional inequality constraint. The results obtained are compared with other units of the same system i.e. with coal quality and without taking coal quality into consideration and plotted in an axis palette of software tools.

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Performance Analysis & Comparison of Optimal Economic Load Dispatch using Soft Computing Techniques

Kumar¹,

Singh²,

Singh³

et al. 2016

ijacsa

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Abstract-Power plants not situated at similar space from center of loads and their fuel prices are dissimilar. In this paper, ELD of actual power generation measured.ELD is preparation of generators to reduce total functioning price of generator units exposed to equality constraint of power balance within minimum and maximum working limits of producing units. In this paper FL, GAs & hybridization of GA-FL is utilized to find optimal solution of ELD systems. ELD resolutions found by resolving conservative load flow equations though at same time reducing fuel prices. Performance of results is analyzed by comparing the data values obtained with the help of soft computing techniques in ELD.

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Application Of Computational Intelligence Techniques For Economic Load Dispatch

Cited by 3 publications

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Statistical modeling and optimal energy distribution of cogeneration units by genetic algorithms

Statistical modeling and optimal energy distribution of cogeneration units by genetic algorithms

Economic load dispatch calculator

Performance Analysis & Comparison of Optimal Economic Load Dispatch using Soft Computing Techniques

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