AI-Based Forecasting Models for Renewable Energy Management

Dear Colleagues,

The Guest Editor is inviting submissions to a Special Issue of Energies on the “AI-Based Forecasting Models for Renewable Energy Management”.

In the context of carbon-neutral, the focus of energy development and utilization at a global scale has been shifting from conventional energy, such as coal and oil, to renewable energy, aiming to alleviate the adverse effects of the greenhouse effect. As an important research direction of renewable energy management, renewable energy forecasting is of great significance to realize the safe operation and scientific dispatch of the power system.

At present, artificial intelligence (AI)-related technologies (such as deep learning, heuristic algorithm, reinforcement learning and transfer learning) are in the ascendant. AI has been favored in other fields (such as financial time series forecasting and fault diagnosis) due to its adaptive learning ability and excellent generalization ability. Therefore, research on how to scientifically and effectively apply AI-based models and algorithms to renewable energy forecasting is a promising direction. This Special Issue expects scholars in the field to make significant contributions and advance the field.

This Special Issue aims to exploit the advantages of AI in the field of renewable energy forecasting and drive innovation in renewable energy forecasting methods. Topics of interest for publication include, but are not limited to:

• Renewable energy forecasting;
• Wind power integration;
• Photovoltaic system;
• Tidal power generation;
• Biomass energy;
• Wave energy;
• Data analytics;
• Neural network;
• Deep learning;
• Optimization;
• Hybrid model;
• Transfer learning;
• Probabilistic forecasting;
• Interval prediction;
• Attention mechanism;
• Feature extraction.

Dr. Tong Niu
Prof. Dr. Mingjian Cui
Dr. Pei Du
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies 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 2600 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.