Prediksi Energi Listrik Kincir Angin Berdasarkan Data Kecepatan Angin Menggunakan LSTM - Muhammad Qubaisy Andiyantama; Iffah Zahira; Ade Irawan (JITCE (Journal of Information Technology and Computer Engineering), 2021)
Fossil energy is well known as the most energy resource consumed by humans. However, the exploitation leads to damage both in the process of taking raw materials and in the use of those. Furthermore, the amount has become decreasing nowadays. Renewable energy could solve the energy crisis. One kind of renewable energy that has been successfully used by a human is by utilizing wind turbines. However, there are still many problems in its implementation and usage. One of the problems is the unstable generated electricity that is caused by instability of the wind speed. Inappropriate plans for utilizing wind turbines in such areas with varying wind speed could harm renewable energy investment. Therefore, forecasting the wind speed is necessary to anticipate the stability and embrace optimal produced energy. This study proposes the Long Short Term Memory (LSTM) algorithm to predict the generated energy by using the wind speed dataset. Thus, wind turbines can be utilized effectively and efficiently in the right area with sufficient average wind speed.