Computational Intelligence Techniques for Future Power Systems
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".
Deadline for manuscript submissions: closed (15 September 2024) | Viewed by 3634
Special Issue Editors
Interests: particle swarm optimization, model predictive control; stochastic optimization; energy management systems; microgrid clusters; system dynamics
Interests: digital twins; support vector machine; relevance vector machine; system identification; Bayesian analysis; robotics; hybrid systems
Interests: power systems; energy storage systems; microgrids; photovoltaic systems; renewable energy sources; control strategy; energy management systems
Special Issues, Collections and Topics in MDPI journals
Interests: microgrids; space power systems; psychobiology; brain networks
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Learning and adaptation are two essential requirements for solving real-world problems. The increasing complexity of systems and their interaction with the dynamic environment make it necessary to develop new efficient computational tools. Computational intelligence (CI) encompasses models and methods inspired by Nature, biological evolution, and human brain and language to address complex non-linear problems. Neural networks, fuzzy systems, swarm intelligence, and evolutionary algorithms are some of the widely used CI techniques. CI plays an important role in power systems. The ever-increasing complexity of power systems, and the presence of uncertainty make it impracticable to use traditional computing methods.
Prospective authors are invited to submit their original research and review papers to this Special Issue on Computational Intelligence Techniques for Future Power Systems in Electronics.
Topics of interest include, but are not limited to, the recent advances of CI applied to the following areas:
- Planning, design, control, and operation management;
- Renewable energy integration;
- Resilience and cybersecurity;
- Power quality;
- Load shedding and load forecasting;
- Demand-side management;
- Battery management systems;
- Fault detection;
- Power system protection;
- Prognostics and health management;
- Electricity markets;
- Power-to-X technologies;
- Digital shadow and digital twins;
- State of health monitoring and predictive maintenance;
- Decision-support systems;
- Electric vehicles;
- Planning of electric vehicle charging stations.
Dr. Najmeh Bazmohammadi
Dr. Ahmad Madary
Prof. Dr. Juan C. Vasquez
Prof. Dr. Josep M. Guerrero
Guest Editors
Manuscript Submission Information
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Keywords
- computational intelligence
- evolutionary algorithms
- swarm intelligence
- fuzzy systems
- neural networks
- heuristic and metaheuristic
- microgrids
- power systems
- data-driven
- big data
- data analytics
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