A review of enhancing wind power with AI: applications, economic implications, and green innovations

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27360%2F25%3A10258033" target="_blank" >RIV/61989100:27360/25:10258033 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/article/10.1007/s44265-025-00059-4" target="_blank" >https://link.springer.com/article/10.1007/s44265-025-00059-4</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

A review of enhancing wind power with AI: applications, economic implications, and green innovations

Popis výsledku v původním jazyce

Wind energy, a renewable resource characterized by its inexhaustibility and absence of pollutants, has garnered signifcant attention in recent years. The optimization of wind power generation for both economic and environmental benefts has emerged as a solution to contemporary energy challenges. Artifcial intelligence (AI), particularly machine learning (ML), enhances the efciency and sustainability of power generation in wind energy systems. This study employs a systematic literature review (SLR) methodology to examine the relevant literature. The fndings indicate that AI, predominantly represented by ML and hybrid AI models, contributes to wind energy systems in three primary domains: frst, the forecasting and analysis of variables, second the optimization of wind turbines (WTs) performance through advanced maintenance management and condition monitoring, and fnally wind farm layout and optimization. Subsequently, we discussed how AI facilitates optimizes employment and energy consumption structures, promotes the green transformation of wind power enterprises, and drives innovation in the wind power industry through wind variable forecasting and turbine maintenance. The application of AI in the wind energy domain presents opportunities for restructuring the energy landscape. Eforts could be made to accelerate AI-driven innovation in the renewable energy sector and promote transformative reorganization of the energy industry.

Název v anglickém jazyce

A review of enhancing wind power with AI: applications, economic implications, and green innovations

Popis výsledku anglicky

Wind energy, a renewable resource characterized by its inexhaustibility and absence of pollutants, has garnered signifcant attention in recent years. The optimization of wind power generation for both economic and environmental benefts has emerged as a solution to contemporary energy challenges. Artifcial intelligence (AI), particularly machine learning (ML), enhances the efciency and sustainability of power generation in wind energy systems. This study employs a systematic literature review (SLR) methodology to examine the relevant literature. The fndings indicate that AI, predominantly represented by ML and hybrid AI models, contributes to wind energy systems in three primary domains: frst, the forecasting and analysis of variables, second the optimization of wind turbines (WTs) performance through advanced maintenance management and condition monitoring, and fnally wind farm layout and optimization. Subsequently, we discussed how AI facilitates optimizes employment and energy consumption structures, promotes the green transformation of wind power enterprises, and drives innovation in the wind power industry through wind variable forecasting and turbine maintenance. The application of AI in the wind energy domain presents opportunities for restructuring the energy landscape. Eforts could be made to accelerate AI-driven innovation in the renewable energy sector and promote transformative reorganization of the energy industry.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

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OECD FORD obor

20200 - Electrical engineering, Electronic engineering, Information engineering

Projekt

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Návaznosti

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Digital Economy and Sustainable Development

ISSN

2731-9423

e-ISSN

2731-9423

Svazek periodika

2025

Číslo periodika v rámci svazku

3:11

Stát vydavatele periodika

SG - Singapurská republika

Počet stran výsledku

29

Strana od-do

1-29

Kód UT WoS článku

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EID výsledku v databázi Scopus

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