Digitalization and renewable energy sustainability: an empirical analysis of artificial intelligence and wind power in Europe
Environment, Development and Sustainability, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Basım Tarihi: 2026
- Doi Numarası: 10.1007/s10668-026-07895-0
- Dergi Adı: Environment, Development and Sustainability
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, BIOSIS, Geobase, Greenfile, Index Islamicus, Natural Science Collection (ProQuest), Biomedical Reference Collection: Corporate Edition (EBSCO), Business Source Ultimate (EBSCO), Materials Science & Engineering Collection (ProQuest), Pharma Collection (ProQuest), Technology Collection (ProQuest)
- Anahtar Kelimeler: Artificial intelligence, European countries, Panel data analysis, Renewable energy, Wind energy
- Erciyes Üniversitesi Adresli: Evet
Özet
Renewable energy sources lie at the core of the global energy transition toward sustainable development, with wind energy playing a strategic role in the shift to low-carbon energy systems. However, the intermittent and variable nature of wind energy brings forth significant challenges in forecasting and optimization. At this juncture, artificial intelligence (AI) emerges as a critical instrument for enhancing energy efficiency, improving system reliability, and accelerating technological innovation. This study investigates the impact of AI on wind energy generation by employing a panel dataset covering 28 European countries over the period 2009–2024. The empirical strategy first tests long-run relationships through the Pedroni cointegration approach, while dynamic interactions are estimated using the ARDL model. Robustness checks are conducted via Panel FMOLS, OLS, and FGLS estimators, and their forecast performances are further compared using the Diebold–Mariano test. The Dumitrescu–Hurlin panel causality test is employed to explore the directional linkages between variables. The findings reveal that AI exerts a statistically significant and positive effect on wind energy generation, primarily through technological progress and innovation channels. Overall, the study provides empirical evidence on the role of AI in Europe’s renewable energy transition and underscores the importance of digitalization and efficiency-oriented applications in shaping future energy policies.