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Wijayanto, Rudi P.
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Enhancing wind energy prediction accuracy with a hybrid Weibull distribution and ANN model: a case study across ten locations in Java Island, Indonesia Fithri, Silvy Rahmah; Hesty, Nurry Widya; Wijayanto, Rudi P.; Pranoto, Bono; Wijaya, Prima Trie; Faqih, Akhmad; Kusuma, Wisnu Ananta; Nurrohim, Agus; Sugiyono, Agus; Yudiartono, Yudiartono
Indonesian Journal of Electrical Engineering and Computer Science Vol 41, No 1: January 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v41.i1.pp180-190

Abstract

Accurate wind speed forecasting is essential for optimizing renewable energy (RE) systems, especially in coastal and island regions with high variability. This study proposes a hybrid predictive model that combines Weibull distribution parameters with artificial neural networks (ANN) to enhance forecasting accuracy. Using ten years of hourly NASA POWER data from 10 locations across Java Island, 24 scenarios were tested with varying combinations of Weibull and meteorological variables. Results demonstrate that incorporating both Weibull shape (k) and scale (c) parameters significantly improves performance, with the best configuration (Scenario 1) achieving a MAPE of 0.44% in Garut. Excluding one or both parameters sharply reduced accuracy, with errors rising up to 35.12%. Beyond technical accuracy, the findings emphasize the practical relevance of Weibull-informed ANN models for energy planning. Reliable forecasts support better wind resource assessment, grid integration, and investment decisions, reducing uncertainties that often hinder wind power deployment. By providing accurate and stable predictions across diverse locations, this approach offers policymakers and planners a robust tool to accelerate RE development and meet national energy targets.
Co-Authors agus Nurrohim Agus Sugiyono Akhmad Faqih Fithri, Silvy Rahmah Hesty, Nurry Widya Pranoto, Bono Wijaya, Prima Trie Wisnu Ananta Kusuma yudiartono, yudiartono