# Wind Speed Prediction in the area of PLTB Tolo Jeneponto South Sulawesi using Artificial Neural Network
> Gunadin I.C.

URL kanonis: https://discover.unhas.ac.id/publications/wind-speed-prediction-in-the-area-of-pltb-tolo-jeneponto-south-sulawesi-using-ar
Jurnal / Konferensi: Proceeding 1st International Conference on Information Technology Advanced Mechanical and Electrical Engineering Icitamee 2020
Tahun terbit: 2020
DOI: https://doi.org/10.1109/ICITAMEE50454.2020.9398419
Citations: 7

## Authors
- Gunadin I.C.

## Abstract
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.

## Keywords
- Wind speed
- Artificial neural network
- Turbine
- Wind power
- Computer science
- Meteorology
- Power (physics)
- Environmental science
- Artificial intelligence
- Engineering
- Electrical engineering
- Geography
- Mechanical engineering
- Physics
- Quantum mechanics

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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