Forecasting of wind speed using Exponential Smoothing and Artificial Neural Networks (ANN)

M.F. Affan; A.G. Abdullah; W. Surya

doi:10.1088/1742-6596/1402/3/033082

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Forecasting of wind speed using Exponential Smoothing and Artificial Neural Networks (ANN)

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M.F. Affan, A.G. Abdullah, W. Surya

2019 Journal of Physics: Conference Series Vol. 1402 Issue 3 Conference paper Cited by 4 SDG 7

Abstract

Wind energy is an environmentally and efficient energy source that is popular. Wind energy can be converted into electrical energy to meet the electricity needs of the community. This research presents results of Bandung's wind speed forecasting for the next 5 years which aims to determine the wind speed potential in Bandung and plan for the application of a power plant to meet the electricity needs of community, using Exponential Smoothing and Artificial Neural Network (ANN) methods), simulation process of the calculation use Zaitun time-series software. Based on simulation results forecasting value with the least error value is obtained using the Artificial Neural Network (ANN) method. The results of the study determined that the city of Bandung was not suitable for the establishment of a wind power because it did not meet minimum wind speed limit suitable for a wind power. © Published under licence by IOP Publishing Ltd.

Affiliations

Department of Electrical Engineering, Universitas Pendidikan Indonesia, Jl. Dr. Setiabudhi 229, Bandung, 40154, Indonesia

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