Simulation and Optimisation for Operational Decision-Making in Renewable Energy Supply Chains and Systems—2nd Edition
A Special Issue of Energies (ISSN 1996-1073) belonging to the section "A: Sustainable Energy".
Deadline for manuscript submissions: 25 April 2027 | Viewed by 17
Editors
Interests: artificial intelligence, agentic AI, and machine learning; renewable energy supply chain and demand-side management; household energy consumption optimisation; logistics and transportation optimisation; AI-driven decision support systems; predictive analytics for sustainable operations and energy management
Special Issues, Collections and Topics in MDPI journals
Interests: power system operation and optimisation; integrated energy systems; energy system planning and operation; reliability assessment; smart grids; renewable energy systems; operational decision-making in energy systems
Special Issue Information
Dear Colleagues,
The global transition towards sustainable energy systems has increased the need for advanced operational decision-making tools capable of improving efficiency, resilience, and sustainability across renewable energy supply chains and systems. Effective operation and management are essential for addressing the uncertainties associated with renewable energy generation, energy demand, and resource allocation.
Recent advances in simulation, optimisation, artificial intelligence, digital twins, and data-driven analytics provide significant opportunities for improving operational performance and supporting real-time decision-making in renewable energy environments.
This Special Issue focuses on the latest research and practical applications related to the simulation, optimisation, control, and management of renewable energy supply chains and systems. Contributions addressing operational, logistical, economic, environmental, and policy challenges are particularly encouraged.
Topics of interest include, but are not limited to, the following:
- Renewable energy supply chains;
- Energy system optimisation;
- Operational decision-making in energy systems;
- Simulation and optimisation techniques;
- Artificial intelligence and machine learning for energy systems;
- Digital twins and Industry 4.0 applications;
- Energy forecasting and predictive analytics;
- Demand-side management
- Energy logistics and transportation systems;
- Distributed and integrated energy systems;
- Hydrogen production, storage, and distribution systems;
- Energy storage and resource allocation;
- Risk and uncertainty modelling;
- Energy policy evaluation and regulatory frameworks;
- Sustainable energy operations and management;
- Internet of Things (IoT) applications in energy systems.
Dr. Ammar Al-Bazi
Dr. Zeyu Liu
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.
Keywords
- renewable energy supply chains
- energy system optimisation
- operational decision-making
- simulation and optimisation
- artificial intelligence
- machine learning
- digital twins
- predictive analytics
- demand-side management
- sustainable energy operations
- hydrogen systems
- IoT in energy systems
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