Special Issue

New Progress and Trends in Energy Forecasting

Submission Deadline: December 30, 2026 (Open) Submit Now

Guest Editor

Abdel-Nasser Sharkawy, PhD

1. Associate Professor, Mechanical Engineering Department, Faculty of Engineering, South Valley University, Qena 83523, Egypt

2. Assistant Professor, Mechanical Engineering Department, College of Engineering, Fahad Bin Sultan University, Tabuk 47721, Saudi Arabia

Website1 | Website2 | Website3 | E-Mail

Research Interests: Mechatronics; robotics; human-robot cooperation; artificial intelligence; machine learning; neural networks; automation; control systems; MATLAB and simulation; C++; system modeling

About This Topic

Energy forecasting is a very important aspect of energy field. It deserves to be investigated and analyzed by using different innovative methods and techniques. The high accuracy, reliability, and stability are some of the main factors that should be taken into consideration during the design of the novel method. The main objectives of forecasting energy are obtaining and predicting future trends in generation, transportation, distribution, pricing, and consumption. Energy forecasting can be achieved using model-based methods or data-based methods. Model-based methods need the knowledge of all the parameters of the system, whereas the data-based methods are based on data gathering and processing. Most popular data-based methods are using machine learning algorithms.

Topics of interest of this special issue includes, but are not limited to:

• New trends in energy forecasting
• Energy demand forecasting
• Traditional and renewable energy forecasting
• Model-Based Methods for energy forecasting
• Data-based methods for energy forecasting
• Machine learning techniques for energy forecasting
• Energy generation, distribution, consumption, pricing forecasting
• Performance and effectiveness analysis

Keywords

New Trends; Forecasting; Traditional Energy; Renewable Energy; Model-Based Methods; Data-Based Methods; Machine Learning Algorithms; Statistics and Analysis; High Performance; Method Effectiveness

Manuscript Submission Information

Manuscripts should be submitted through the LIDSEN Submission System. Detailed information on manuscript preparation and submission is available in the Instructions for Authors. All submitted articles will be thoroughly refereed through a single-blind peer-review process and will be processed following the Editorial Process and Quality Control policy. Upon acceptance, the article will be immediately published in a regular issue of the journal and will be listed together on the special issue website, with a label that the article belongs to the Special Issue. LIDSEN distributes articles under the Creative Commons Attribution (CC BY 4.0) License in an open-access model. The authors own the copyright to the article, and the article can be free to access, distribute, and reuse provided that the original work is correctly cited.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). Research articles and review articles are highly invited. Authors are encouraged to send the tentative title and abstract of the planned paper to the Editorial Office (jept@lidsen.com) for record. If you have any questions, please do not hesitate to contact the Editorial Office.

Welcome your submission!