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A study on wind speed prediction using artificial neural network at Jeju Island in Korea II

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5 Author(s)
Fengming Zhang ; Electr. Eng., Gyeongsang Nat. Univ., Jinju, South Korea ; Kyeonghee Cho ; Jaeseok Choi ; Young-Mi Lee
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Wind power is one of the most successfully utilized of renewable sources to produce electrical energy. The available wind energy depends on the wind speed, which is a random variable. For the wind-farm operator, this poses difficulty in the system scheduling and energy dispatching, as the schedule of the wind-power availability is not known in advance. This paper proposes to use the two-layered artificial neural networks for predicting the actual wind speed from the previous values of the same variable.

Published in:

2011 IEEE 54th International Midwest Symposium on Circuits and Systems (MWSCAS)

Date of Conference:

7-10 Aug. 2011