Optimization analysis of influencing factors on wind power integration based on continuous ant colony support vector machine

In order to improve the reliability of wind power integration, using the continuous ant colony support vector machine theory based on the analysis of peaking need, we put forward the method of optimization analysis of influencing factors on wind power integration. According to the influence of param...

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Vydáno v:	China International Conference on Electricity Distribution s. 1 - 4
Hlavní autoři:	Du Qiushi, Lu Yu, Cong Li
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 01.08.2016
Témata:	continuous ant colony optimization algorithms Harmonic analysis Kernel Optimization power Network Operation Short-circuit currents support vector machine Support vector machines Wind farms Wind power generation wind power Integration
ISSN:	2161-749X
On-line přístup:	Získat plný text
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Shrnutí:	In order to improve the reliability of wind power integration, using the continuous ant colony support vector machine theory based on the analysis of peaking need, we put forward the method of optimization analysis of influencing factors on wind power integration. According to the influence of parameter selection to optimization effect, we discuss the continuous ant colony support vector machine model and case study Wind Power Integration of Jilin Province. The result proves support vector function based on MG-CACO Algorithm improves the accuracy of the model, and it is very practical and effective in Wind Power Integration.
ISSN:	2161-749X
DOI:	10.1109/CICED.2016.7576010