Spectral and gradient-based analysis of wind variability for renewable energy planning
Year: 2025
Type: article
Abstract: The rapid expansion of wind energy in power systems has heightened the need for accurate variability assessments and advanced forecasting. Morocco exemplifies this trend, with an estimated wind potential of 22 GW offshore and 25 GW onshore and 1.77 GW of capacity installed as of 2023. The country aims to reach 5 GW of wind capacity by 2030 and achieve 80% decarbonization by 2050, underscoring the growing importance of wind energy. Additionally, Morocco’s “Green Hydrogen Offer” targets an annual production of 3 million tons of green hydrogen by 2030, further emphasizing the need for robust wind resource characterization. In response to local and global imperatives, this study analyzes wind patterns at Boujdour and Ben Guerir using three years of hourly data (ERA5 and ground observations), applying a hybrid methodology combining Fast Fourier Transform (FFT), Signal-to-Noise Ratio (SNR), Peak-Trough-Mean (PTM) analysis, and Global Variability Gradient (GVG). Results show Boujdour exhibits stronger but more stable wind conditions (6.35 m/s at 10 m, TI = 0.12, SNR = 46.1 dB), while Ben Guerir experiences weaker, more variable winds (2.72 m/s, TI = 0.33, SNR = 36.6 dB). GVG and PTM analyses confirm seasonal regularity and higher wind acceleration at Ben Guerir (0.60 m/s/h). The Siemens Gamesa SG 5.0–132 turbine was used to set thresholds for low, middle and high variability. The proposed indicators enhance site characterization and support planning in wind-to-hydrogen systems, offering scalable tools for short-term forecasting and resource optimization.
Source: Results in Engineering
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,940
OpenAlex ID: W7117233156