Spatial Wind Speed Forecasting Using Artificial Neural Networks

Abstract

Spatial interpolation is a commonly used technique to simulate wind speeds in areas which are devoid of such measuring devices. In this paper authors examine the applicability and efficiency of Artificial-Neural-Network (ANN) formalism aimed at interpolating wind speeds in space domain. Additionally, the effect of the correlation between the wind speed at target site and its correlated neighboring site is also examined in the present paper. Hourly wind speed data set comprising of wind speeds recorded from April 2016 to August 2018 provided by Energy Sector Management Assistance Program of World Bank is used for the study. The study is supported by including four different wind speed measuring stations in Pakistan, namely, TandoGhulamAli, Umer Kot, Sujawal and Sanghar. Best estimates from ANN model are obtained for TandoGhulamAli (MAPE= 7.37%) andworst estimates are observed forSanghar site (MAPE= 10.61%).

Keywords

• spatial interpolation
• artificial neural network
• prediction
• target station
• wind speed.