A Comparison Wind Power Forecasting with Different Methods. Issue 1 (9th June 2022)

• Record Type: Journal Article
• Authors: Yan, Jian
• Is Part Of: Integrated ferroelectrics. Volume 227:Issue 1(2022)
• Page Start: 191
• Page End: 201
• Publication Date: 2022-06-09
• Subjects: Offshore wind power -- forecasting methods -- comparison of methods; Ferroelectric devices -- Periodicals; Integrated circuits -- Periodicals; 537.244805
• DOI: 10.1080/10584587.2022.2065585
• Languages: English
• ISSNs: 1058-4587

Abstract

Abstract: Accurate prediction of wind power can improve the quality and consistency of the wind energy to the grid, However, this task remains challenging due to the strong stochastic nature and dynamic uncertainty of wind speed. To forecast the wind power, different methods like auto regressive integrated moving average, ordinary least square method and k-nearest neighbors methods are used in this analysis. Different methods use different kernel and the qualitative results shows that wind power can be forecasted with different forecasting techniques with reasonable accuracy while quantitative analysis shows that forecasting error of wind power is less than 20%.