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AI-Driven Multi-Technology Renewable Energy Systems: Climate Resilience and Sustainable Management

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 44

Special Issue Editor


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Guest Editor
Department for Energy Efficiency, ENEA-Italian National Agency for New Technologies, Energy and Sustainable Economic Development, Rome, Italy
Interests: energy efficient buildings; energy efficiency monitoring and evaluation; energy end-use efficiency and energy services; renewable energy sources; RES integration in buildings; photovoltaic performance analysis; PV generation forecasting methods; artificial intelligence predictive methods for photovoltaic systems
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Special Issue Information

Dear Colleagues,

The global transition to renewable energy requires sophisticated optimization strategies that address performance variability, climate adaptation, and grid integration challenges. This Special Issue will explore the convergence of artificial intelligence, advanced analytics, and sustainability frameworks to enhance renewable energy system efficiency and resilience.

This Special Issue will also examine AI-driven approaches, including machine learning-based forecasting, performance degradation modeling across technologies, hybrid energy systems integration, and climate-adaptive management strategies. We welcome contributions spanning wind, solar thermal, hydroelectric, biomass, geothermal, and emerging renewable technologies, with particular emphasis on their intelligent coordination and optimization.

The primary objective of this Special Issue is to advance scientific understanding through innovative AI applications, performance analysis, and integrated sustainability assessments that support reliable clean energy deployment across diverse environmental conditions. This Special Issue welcomes practical studies that demonstrate measurable improvements in energy efficiency, grid stability, and environmental impact reduction.

Most current research examines renewable energy technologies separately or uses single-optimization methods in isolation. This Special Issue fills this knowledge gap by focusing on comprehensive approaches that combine multiple technologies, adapt to changing climate conditions, and ensure long-term environmental and economic sustainability. We particularly encourage submissions that present practical implementations, validate theoretical models using real-world data, and demonstrate scalable solutions for different geographic regions and energy system configurations.

Proposed topics for submissions include the following:

  1. AI-enhanced energy system optimization:
  • Machine learning algorithms for multi-source energy management;
  • Predictive analytics for renewable energy forecasting;
  • Neural networks for grid stability and load balancing.
  1. Climate-adaptive energy systems:
  • Performance degradation modeling across renewable technologies;
  • Climate resilience strategies for energy infrastructure;
  • Weather pattern analysis for energy planning.
  1. Smart grid integration and management:
  • Distributed energy resource coordination;
  • Energy storage optimization strategies;
  • Electric vehicle integration and demand response.
  1. Hybrid renewable energy systems:
  • Multi-technology integration frameworks;
  • Biomass–solar–wind hybrid configurations;
  • Microgrids and islanding strategies.
  1. Sustainability assessment and policy:
  • Life cycle assessment methodologies for renewable systems;
  • Carbon footprint optimization across energy portfolios;
  • Economic viability and policy impact studies.
  1. Advanced monitoring and real-world implementation:
  • IoT-enabled performance monitoring systems;
  • Fault detection and diagnostic algorithms;
  • Practical case studies and scalable deployment strategies.

This Special Issue will provide a comprehensive platform for researchers to share innovative solutions that address critical challenges in renewable energy system optimization, climate adaptation, and sustainable energy management across diverse technologies and applications.

We look forward to receiving your contributions.

Dr. Maria Malvoni
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence
  • renewable energy systems
  • machine learning
  • smart grid integration
  • climate resilience
  • hybrid energy systems
  • sustainability assessment
  • multi-technology integration

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Published Papers

This special issue is now open for submission.
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