Smart and Sustainable Energy Systems: Optimization, Modeling, and Management for Global Energy Challenges

Dear Colleagues,

Achieving sustainable, efficient, and resilient energy systems is one of the most critical challenges of our time. Energy systems today are increasingly complex, integrating diverse technologies, data streams, and decision layers—from strategic design and planning to operation, maintenance, and decommissioning. Enhancing energy efficiency and promoting energy conservation across all phases of the energy system lifecycle is essential for meeting global energy demands while minimizing environmental impacts.

This Special Issue aims to bring together state-of-the-art research addressing the modeling, optimization, analysis, and management of energy systems. We encourage submissions that span the full energy lifecycle—including system design, planning, operation, maintenance, and sustainability—with particular emphasis on energy efficiency, reliability, and conservation strategies. We invite interdisciplinary research that combines advanced analytical techniques, engineering practices, and decision-making tools to improve energy system performance and sustainability.

Scope and Topics of Interest

We welcome contributions from a wide range of disciplines and methodological perspectives. Topics of interest include, but are not limited to, the following:

1. Energy System Design and Planning

• Optimization models for the sustainable and cost-effective design of energy systems;
• Long-term planning of renewable and hybrid energy systems;
• Energy infrastructure development under uncertainty;
• Integration of energy efficiency and conservation goals in system design;
• Lifecycle and techno-economic analyses of energy technologies.

2. Operation and Control of Energy Systems

• Optimization and control strategies for energy-efficient operations;
• Smart grid operation, microgrid control, and distributed energy management;
• Energy demand forecasting and load management;
• Demand response and dynamic pricing for conservation;
• Real-time scheduling of energy generation and consumption.

3. Maintenance, Reliability, and Asset Management

• Reliability engineering and predictive maintenance for energy assets;
• Condition monitoring and failure analyses using advanced data analytics;
• Asset health management and lifecycle extension strategies;
• Risk-based maintenance and cost-performance trade-offs;
• Resilience and fault-tolerant operations in energy networks.

4. Energy Analytics and Decision Support

• AI and machine learning for energy forecasting, optimization, and diagnostics;
• Big data applications in smart energy systems;
• Predictive and prescriptive analytics for performance enhancement;
• Multi-Criteria Decision Making (MCDM) for energy investment and policy decisions;
• Data-driven decision support for improving energy conservation outcomes.

5. Sustainability, Efficiency, and Conservation

• Metrics and models for energy efficiency evaluation;
• Policy modeling and incentives for energy conservation;
• Integration of energy systems with circular economy strategies;
• Sustainable energy transitions and decarbonization pathways;
• Environmental impact and lifecycle assessments of energy solutions.

6. Engineering and Project Management in Energy Systems

• Planning and management of energy infrastructure projects;
• Energy systems quality management and performance improvement;
• Lean Six Sigma and continuous improvement methods in energy operations;
• Total productive maintenance (TPM) for energy-intensive industries;
• Engineering economics and project risk management;
• Project integration and stakeholder management.

7. Supply Chain and Logistics for Energy Systems

• Renewable energy supply chain design and optimization;
• Hydrogen and battery storage supply chain modeling;
• Sustainable procurement and reverse logistics in energy sectors;
• Resilience of energy distribution and transmission networks;
• Logistics for decentralized and distributed energy systems;
• Circular economy in energy systems.

8. Advanced Modeling and Optimization Techniques

• Multi-objective and multi-criteria optimization for complex energy problems;
• Robust, stochastic, and dynamic programming under uncertainty;
• Simulation-based optimization for real-world energy systems;
• AI-integrated optimization and digital twin modeling;
• Metaheuristics, surrogate modeling, and hybrid solution techniques.

Dr. Ahmed Shaban
Dr. Nasr Al-Hinai
Dr. Mahmood Al-Kindi
Dr. Hakan Gultekin
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-blind 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.