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March 4, 2026Energies3 citationsOpen Access

Review of Artificial Intelligence Applications in the Digital Energy and Renewable Energy Infrastructures

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VZVladimir ZinovievDKDimitrina KoevaPTPlamen Tsankov

Key Points

  • The aim is to review successful AI integration in renewable energy systems, exploring its potential in enhancing energy management.
  • Comprehensive review of AI applications in the energy sector.
  • Identification of key areas such as forecasting generation and demand.
  • Presentation of a three-phase roadmap for AI adoption and a 4-layer model for digitalization.
  • Identified five significant application areas for AI in renewable energy.
  • Presented a structured taxonomy for understanding AI technologies and algorithms.
  • Developed guidelines for successful AI decision-making aligned with standards.

Abstract

The increasing use of integrated renewable energy sources (RESs) is undoubtedly reshaping the structure of power systems. In such conditions, achieving energy efficiency and sustainability requires the development and integration of digital solutions to manage energy flows and assets optimization. This paper aims to provide a comprehensive review of the successful integration of artificial intelligence (AI) in the energy sector, particularly in relation to the high penetration of renewable energy. The paper presents trends and potential scenarios in the digitalization of energy, along with the associated challenges. It analyzes particular applications of AI tools in strategic areas of the energy sector. Five key areas of the energy sector are identified where AI tools are applied: forecasting electricity generation from RES; forecasting demand and price fluctuations on the electricity spot market; the real-time management of energy flows and assets in active microgrids; and data processing and analyzing, and general industrial direction. The article also attempts to summarize the current status, goals, key areas, and activities in the irreversible transformation of power structures into digital intelligent ones. This digital transformation is a gradual process with consecutive steps. To improve understanding and clarity, the authors present a three-phase roadmap of AI adoption. To develop an adequate AI integration strategy, it is necessary to understand the technologies, algorithms, hierarchical structure, and connections within this structure. Accordingly, the article presents a taxonomy of the hierarchical structure of AI. The subsequent step involves the sequential construction of a digitalization model. Here, the authors consider it necessary to present a 4-layer structure model of AI energy democracy. Finally, through a comparative analysis of different types of intelligent applications for energy problem solving, guidelines are provided for successful decision making in compliance with the specified harmonized standards and protocols.

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Cite This Study

Zinoviev et al. (2026) studied this question.

synapsesocial.com/papers/69a7cdaed48f933b5eeda3dbhttps://doi.org/10.3390/en19051250
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