![]() The results of the two approaches indicated that among all the involved models, the ARIMA model has the best predicting performance. The data were collected in the meteorological station located in the experimental farm of the Atlantic University, in Barranquilla, Colombia, and variables analyzed included wind speed, wind direction, temperature, relative humidity, solar radiation, and pressure. In this paper, based on time series, Autoregressive Integrated Moving Average (ARIMA), and Multiple Regression with Ordinary Least Squares (OLS) in the study, two models are proposed and their performance for wind speed prediction is compared. This is a disadvantage because the potential of wind resources in this region is greater than the hydroelectric potential of the whole country, but all this potential has yet to be developed. However, although there are multiple studies, none are set up for the Colombia Caribbean coast. Greater incorporation of wind energy into power systems has necessitated the development of accurate and reliable techniques for wind speed forecasting.
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