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

共 50 条

[1] Prediction of Solar Wind Speed at 1 AU Using an Artificial Neural Network
Yang, Yi
Shen, Fang
Yang, Zicai
Feng, Xueshang
[J]. SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS, 2018, 16 (09): : 1227 - 1244
[2] A Study on Wind Speed Prediction using Artificial Neural Network at Jeju Island in Korea
Wu, Liang
Park, Jeongje
Choi, Jaeseok
Cha, Junmin
Lee, Kwang Y.
[J]. T& D ASIA: 2009 TRANSMISSION & DISTRIBUTION CONFERENCE & EXPOSITION: ASIA AND PACIFIC, 2009, : 431 - +
[3] Wind speed prediction based on simple meteorological data using artificial neural network
Ghanbarzadeh, A.
Noghrehabadi, A. R.
Behrang, M. A.
Assareh, E.
[J]. 2009 7TH IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS, VOLS 1 AND 2, 2009, : 664 - +
[4] Wind speed prediction in the mountainous region of India using an artificial neural network model
Ramasamy, P.
Chandel, S. S.
Yadav, Amit Kumar
[J]. RENEWABLE ENERGY, 2015, 80 : 338 - 347
[5] Wind Speed Prediction from Site Meteorological Data Using Artificial Neural Network
Ahmed, Khawaja Masood
Khan, Muhammad Arshad
Siddiqui, Imran
Khan, Siraj
Shoaib, M.
Zia, Ibrahim
[J]. 2022 GLOBAL CONFERENCE ON WIRELESS AND OPTICAL TECHNOLOGIES (GCWOT), 2022, : 99 - 106
[6] Application of Artificial Neural Network for Long Term Wind Speed Prediction
Malik, Hasmat
Savita
[J]. 2016 CONFERENCE ON ADVANCES IN SIGNAL PROCESSING (CASP), 2016, : 217 - 222
[7] Improved Wind Speed Prediction Results by Artificial Neural Network Method
Sirdas, Asilhan Sevinc
Nilcan, Akatas
Ercan, Izgi
[J]. EXERGY FOR A BETTER ENVIRONMENT AND IMPROVED SUSTAINABILITY 2: APPLICATIONS, 2018, : 651 - 665
[8] Hybrid boosting algorithms and artificial neural network for wind speed prediction
Dosdogru, Ayse Tugba
Ipek, Asli Boru
[J]. INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2022, 47 (03) : 1449 - 1460
[9] Forecasting South Sulawesi Electrical Energy Consumption Using Artificial Neural Network
Said, Sri Mawar
Ilyas, Andi Muhammad
[J]. PRZEGLAD ELEKTROTECHNICZNY, 2024, 100 (03): : 191 - 195
[10] Prediction Of Vertical Wind Speed By Artificial Neural Network For Wind Energy Application In Algeria
Adjiri, S.
Nedjari-Daaou, H.
Boudia, S. M.
[J]. 2018 INTERNATIONAL CONFERENCE ON WIND ENERGY AND APPLICATIONS IN ALGERIA (ICWEAA' 2018), 2018,

← 1 2 3 4 5 →