Publication: A self-adaptive differential evolution algorithm for dynamic economic dispatch with valve-point effects
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Issued Date
2012
Resource Type
File Type
application/pdf
Other identifier(s)
2-s2.0-84872858150
Rights Holder(s)
มหาวิทยาลัยศรีนครินทรวิโรฒ
Bibliographic Citation
Proceedings of the Universities Power Engineering Conference. Vol , No. (2012), p.-
Suggested Citation
Sum-Im T. A self-adaptive differential evolution algorithm for dynamic economic dispatch with valve-point effects. Proceedings of the Universities Power Engineering Conference. Vol , No. (2012), p.-. doi:10.1109/UPEC.2012.6398551 Retrieved from: https://hdl.handle.net/20.500.14740/6884
Author(s)
Abstract
In this paper, a self-adaptive differential evolution algorithm (SaDEA) is proposed for solving dynamic economic dispatch (DED) problem with valve-point effects consideration. The purpose of DED problem is to minimize the total generation costs of thermal power plants associated with the technical and economical constraints. The software development has been performed within the mathematical programming environment of MATLAB in this work. The efficiency and effectiveness of the proposed technique is initially demonstrated via the analysis of 3-unit and 10-unit test systems considering valve-point loading and ramp rate constraints. A detailed comparative study among an evolutionary programming (EP), a particle swarm optimization (PSO), an enhanced particle swarm optimization (EPSO), an enhanced particle swarm optimization with Gaussian mutation (EPSO-GM), a hybrid method between evolutionary programming and sequential quadratic programming (EP-SQP), a modified hybrid EP-SQP (MHEP-SQP) and the proposed method is presented. From the experimental results, the proposed method has the achieved solutions with good accuracy, stable convergence characteristics, simple implementation and satisfactory computational time. © 2012 IEEE.
Subject(s)
Comparative studies
Computational time
Dynamic economic dispatch
Enhanced particle swarm optimization
Gaussian mutation
Generation cost
Hybrid method
Ramp rate constraints
Self-adaptive differential evolution algorithms
Sequential quadratic programming
Stable convergence
Test systems
Thermal power plants
Valve point effects
Computer programming
Mathematical programming
Power generation
Thermoelectric power plants
Particle swarm optimization (PSO)
Computational time
Dynamic economic dispatch
Enhanced particle swarm optimization
Gaussian mutation
Generation cost
Hybrid method
Ramp rate constraints
Self-adaptive differential evolution algorithms
Sequential quadratic programming
Stable convergence
Test systems
Thermal power plants
Valve point effects
Computer programming
Mathematical programming
Power generation
Thermoelectric power plants
Particle swarm optimization (PSO)