Short-term wind power prediction models in complex terrain based on statistical time series analysis

• Main Author: Fossem, Andreas Aarhuus
• Format: Master Thesis
• Language: English
• Published: UiT The Arctic University of Norway 2019
• Subjects: VDP::Technology: 500::Environmental engineering: 610; Renewable energy; Wind power; Wind resource mapping; VDP::Mathematics and natural science: 400::Mathematics: 410::Statistics: 412; VDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Statistikk: 412; Markov chains; VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411; VDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Analyse: 411; Time series analysis; VDP::Teknologi: 500::Miljøteknologi: 610; EOM-3901; Fakken; Norway; Nygårdsfjellet; Kjøllefjord; Northern Norway
• Online Access: https://hdl.handle.net/10037/17251

One of the largest challenges with the utilization of wind as a renewable resource, is its natural variability and intermittent nature. To achieve a sustainable integration of wind power into the power grid, a precise and reliable prediction method is therefore required. In this study, several short...