A genetic algorithm based economic dispatch (GAED) with environmental constraint optimisation
Contribuinte(s) |
Abertay University. School of Arts Media & Computer Games |
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Data(s) |
09/03/2016
09/03/2016
2011
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Resumo |
The role of renewable energy in power systems is becoming more significant due to the increasing cost of fossil fuels and climate change concerns. However, the inclusion of Renewable Energy Generators (REG), such as wind power, has created additional problems for power system operators due to the variability and lower predictability of output of most REGs, with the Economic Dispatch (ED) problem being particularly difficult to resolve. In previous papers we had reported on the inclusion of wind power in the ED calculations. The simulation had been performed using a system model with wind power as an intermittent source, and the results of the simulation have been compared to that of the Direct Search Method (DSM) for similar cases. In this paper we report on our continuing investigations into using Genetic Algorithms (GA) for ED for an independent power system with a significant amount of wind energy in its generator portfolio. The results demonstrate, in line with previous reports in the literature, the effectiveness of GA when measured against a benchmark technique such as DSM. |
Identificador |
King, D.J. , Ozveren, C.S. and Warsono, 2011. A genetic algorithm based economic dispatch (GAED) with environmental constraint optimisation. In: Proceedings of the 46th International Universities' Power Engineering Conference (UPEC), Soest, Germany, 5-8 September 2011. 9783800734023 |
Idioma(s) |
en |
Publicador |
VDE |
Direitos |
This is the authors' version of a paper ©2011 IEEE. published in Universities' Power Engineering Conference (UPEC), Proceedings of 2011 46th International. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Palavras-Chave | #Genetic algorithms #Economic dispatch #Renewable energy generators #Environmental constraints #Genetic algorithms |
Tipo |
Conference Paper published peer-reviewed accepted |