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A very short term wind power forecasting using back-propagation algorithm in neural networks

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Title: A very short term wind power forecasting using back-propagation algorithm in neural networks

Authors: Priyadarshni S., Booma J., Dhanarega A.J., Dhanalakshmi P.

Journal: ARPN Journal of Engineering and Applied Sciences

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
X 2020-07-01 2021-06-30

Publisher: Khyber Medical College, Peshawar

Country: Pakistan

Year: 2015

Volume: 10

Issue: 6

Language: English

Categories
Electrical Engineering (5972) Neural Networks (134) Wind Power (14) Forecasting (195) Renewable Energy (1237)

Abstract

This paper presents an application of Artificial Neural Networks-Back Propagation (ANN-BP) for wind power forecasting. The need for accurate forecasting keeps on increasing as power demands and power markets are becoming more competitive and complex structure in integrating wind power into the grid power system. This paper presents a model for wind power forecasting for the very short term scheduling.

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