Data-Driven Approaches for Green Energy Transition
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F5: Artificial Intelligence and Smart Energy".
Deadline for manuscript submissions: 10 August 2026 | Viewed by 160
Editors
Interests: data-driven management strategies and policy making; energy economics; energy transition
Special Issue Information
Dear Colleagues,
The transition to a sustainable and carbon-neutral energy system is a complex challenge that requires an integrated perspective across generation, distribution, and consumption. As the energy landscape becomes increasingly decentralized and interconnected, data-driven approaches have become essential tools for navigating this complexity and ensuring a stable transition.
This Special Issue invites original research that applies diverse data-driven methodologies to any sector of the green energy transition. We welcome both theoretical and empirical studies that leverage data—from statistical modeling to machine learning—to optimize energy systems, evaluate policies, and understand market dynamics. Our goal is to provide a comprehensive forum for discussing how evidence-based analysis can support a resilient and sustainable energy future.
The focus of this Special Issue is on (but is not limited to):
- Optimization of Integrated Energy Systems: Data-driven strategies for managing complex, multi-sector energy networks.
- Predictive Analytics for Energy Resources: Forecasting and modeling the variability of sustainable energy supply and demand.
- System Reliability and Resilience: Quantitative analysis of infrastructure stability in the face of energy transition.
- Techno-Economic and Market Analysis: Empirical studies on energy market design, pricing, and economic viability.
- Policy Impact and Evaluation: Data-based assessment of the effectiveness and social impact of energy transition policies.
- Sustainability and Environmental Assessment: Quantitative modeling of carbon reduction and the environmental footprint of energy systems.
- Innovation and Technology Diffusion: Tracking and predicting the development and spread of emerging green technologies.
- Data-centric Decision Support Systems: Frameworks for evidence-based decision-making in the public and private energy sectors.
Dr. Hyungbin Moon
Dr. Stephen Youngjun Park
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
- energy transition
- data-driven approaches
- energy systems
- forecasting
- modeling
- energy economics
- energy policy
- energy market
- energy supply
- carbon reduction
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