Wind Speed Prediction in the area of PLTB Tolo Jeneponto South Sulawesi using Artificial Neural Network

被引：0

作者：

Gunadin, Indar Chaerah ^{[1
]}

Safrizal ^{[2
]}

Rosyadi, Marwan ^{[3
]}

Siswanto, Agus ^{[4
]}

Syukriyadin ^{[5
]}

Muslimin, Zaenab ^{[1
]}

Gassing ^{[1
]}

机构：

[1] Hasanuddin Univ, Elect Engn Dept, Makassar, Indonesia

[2] Islamic Nandlatul Ulama Univ, Elect Engn Dept, Jepara, Indonesia

[3] PT Indah Karya Persero, Energy Div, Bandung, Indonesia

[4] Univ 17 Agustus 1945, Elect Engn Dept, Cirebon, Indonesia

[5] Syiah Kuala Univ, Elect & Comp Engn Dept, Banda Aceh, Indonesia

来源：

2020 1ST INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY, ADVANCED MECHANICAL AND ELECTRICAL ENGINEERING (ICITAMEE 2020) | 2020年

关键词：

forecasting; wind turbine; operating cost; artificial neural network; error;

D O I：

10.1109/ICITAMEE50454.2020.9398419

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Forecasting the output power of a wind turbine is very much determined by the ability to predict wind speed at the location of the wind turbine placement The results of this forecast are highly correlated with the operating patterns that will be applied to the electric power system and also with the system operating costs. Wind speed forecasting at PLTB Tolo Jeneponto, South Sulawesi, Indonesia is done by taking wind speed data for the last 20 years. The method used in forecasting is an Artificial Neural Network From the simulation results, it can be seen that the forecast error is 0.17883 percent. This shows that the ANN method can be accepted as a method in predicting wind speed.

引用

页码：106 / 110

页数：5

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