Economic Dispatch in IEEE 26 Bus System using Quantum Behaved Particle Swarm Optimization

Pressa Perdana Surya Saputra; Farid Dwi Murdianto; Rifqi Firmansyah; Kukuh Widarsono

doi:10.1109/iCAST51016.2020.9557625

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Economic Dispatch in IEEE 26 Bus System using Quantum Behaved Particle Swarm Optimization

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Pressa Perdana Surya Saputra, Farid Dwi Murdianto, Rifqi Firmansyah, Kukuh Widarsono

2020 3rd International Conference on Applied Science and Technology, iCAST 2020 Conference paper Cited by 8

Abstract

Economic Dispatch (ED) is used to determine the optimal schedule of on-line generating outputs so as to meet the load demand at the minimum operating cost. The researcher usually using conventional method such us Lagrange and more modern methods, Artificial Intelligence, such us Particle Swarm Optimization (PSO), firefly (FA), Genetic Algorithm (GA), etc to solve economic dispatch problem. The newest technology in Artificial Intelligence had invented a new method to solve economic dispatch, it’s named Quantum behaved PSO (QPSO). In this paper, QPSO is applied to solve economic dispatch at IEEE 26 bus system. Then the result will be compared by Lagrange and conventional PSO. Thus, the simulation shows that QPSO has better result than Lagrange and conventional PSO. On IEEE 26 Bus, QPSO can save the cost generation until 55.63 $/h compared with Lagrange, and 3.1 $/h compared by conventional PSO. © 2020 IEEE.

Affiliations

Electrical Engineering, Universitas Muhammadiyah, Gresik, Indonesia; Electronics Engineering, Polytechnic Institute of Surabaya, Surabaya, Indonesia; Electrical Engineeriing, Universitas Negeri Surabaya, Surabaya, Indonesia; Politeknik Negeri Madura, Madura, Indonesia

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