FORECASTING OF WIND SPEED USING EXPONENTIAL SMOOTHING METHOD AND ARTIFICIAL NEURAL NETWORK.
M. FIQRI AFFAN, ADE GAFFAR ABDULLAH, WASIMUDIN SURYA
Teknik Elektro, FPTK, Universitas Pendidikan Indonesia
Abstract
Wind Energy is an environmentally friendly and efficient energy source that is popular now. Wind Energy can be converted into electrical energy to meet the electricity needs of the community. In this paper purpose to determine potential of wind speed in the city of Bandung, and build a PLTB (Wind Power Plant) to meet the electricity needs of the community. Analyze by using Eksponential Smoothing method and Artificial Neural Network. The results obtained are average annual wind speed starting from 2019-2023 with the calculation of ANN and exponential smoothing, after knowing the results, compare the two method which method is more accurate. Benefit of this calculation is to determine whether the city of Bandung is feasible to establish a PLTB or not, judging by the results of its wind speed forecast.
Keywords: Wind Energy; Artificial Neural Network; Exponential Smoothing
Topic: Electrical Engineering