Artificial Intelligence and Genetic Algorithms in Renewable Energy Systems
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".
Deadline for manuscript submissions: 15 September 2026 | Viewed by 36
Special Issue Editors
Interests: renewable energy systems; photovoltaic installations; interval type-2 fuzzy systems; time series forecasting; uncertainty modeling; genetic and evolutionary algorithms; multi-objective optimization; energy management; mathematical AI methods
Interests: computer science; operating systems; computer networks; cluster computing; real-time
Interests: smart grid; advanced distribution automation; renewable energy system design; heuristic optimization
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid global transition toward renewable and sustainable energy systems has positioned photovoltaic, hybrid, and autonomous energy installations as key components of modern energy infrastructures. However, the increasing penetration of renewable sources introduces significant challenges related to uncertainty, variability, nonlinearity, and data scarcity, particularly in short-term forecasting, system optimization, and real-time energy management.
Recent advances in artificial intelligence (AI), genetic algorithms, and evolutionary optimization offer powerful tools to address these challenges by enabling adaptive modeling, robust forecasting, and multi-objective decision-making under uncertainty. In particular, fuzzy systems, interval type-2 fuzzy sets, and footprint of uncertainty (FOU) modeling provide mathematically grounded frameworks for handling the imprecise and incomplete information commonly encountered in renewable energy data.
This Special Issue aims to bring together theoretical contributions, algorithmic developments, and applied studies that explore intelligent methods for modeling, forecasting, optimization, and controlling renewable energy systems. We are especially interested in innovative approaches that bridge AI methodologies and practical energy engineering applications, contributing to more reliable, efficient, and resilient renewable energy solutions.
Topics of interest include, but are not limited to, the following:
- Artificial intelligence and genetic algorithms in renewable energy systems;
- Fuzzy and interval type-2 fuzzy models for energy forecasting;
- Short time-series analysis under uncertainty;
- Multi-objective and Pareto-based optimization in energy management;
- Photovoltaic system modeling, configuration, and performance optimization;
- Battery storage, load scheduling, and demand-side management;
- Intelligent control of inverters and hybrid energy systems;
- Clustering and phase-space analysis of energy-related time-series.
We look forward receiving original research and review articles that contribute to the advancement of intelligent renewable energy systems.
Dr. Ekaterina Gospodinova
Dr. Stanislav Simeonov
Prof. Dr. Jen-Hao Teng
Guest Editors
Manuscript Submission Information
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Keywords
- photovoltaic systems
- renewable energy electronics
- intelligent control
- artificial intelligence
- fuzzy systems
- interval type-2 fuzzy logic
- energy management
- power electronics
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