  Artificial intelligence (AI) has become a crucial instrument for streamlining
processes in various industries, including electrical power systems, as a
result of recent digitalization. Algorithms for artificial intelligence are
data-driven models that are based on statistical learning theory and are used
as a tool to take use of the data that the power system and its users generate.
Initially, we perform a thorough literature analysis of artificial intelligence
(AI) applications related to renewable energy (RE). Next, we present a thorough
analysis of renewable energy factories and assess their suitability, along with
a list of the most widely used and appropriate AI algorithms. Nine AI-based
strategies are identified here to assist Renewable Energy (RE) in contemporary
power systems. This survey paper comprises an extensive review of the several
AI techniques used for renewable energy as well as a methodical analysis of the
literature for the study of various intelligent system application domains
across different disciplines of renewable energy. This literature review
identifies the performance and outcomes of nine different research methods by
assessing them, and it aims to distill valuable insights into their strengths
and limitations. This study also addressed three main topics: using AI
technology for renewable power generation, utilizing AI for renewable energy
forecasting, and optimizing energy systems. Additionally, it explored AI's
superiority over conventional models in controllability, data handling,
cyberattack prevention, smart grid implementation, robotics- AI's significance
in shaping the future of the energy industry. Furthermore, this article
outlines future directions in the integration of AI for renewable energy.
