Theory and Application of Computational Intelligence in Electric Vehicles and their Integration within Smart Energy Networks
A special issue of Energies (ISSN 1996-1073).
Deadline for manuscript submissions: closed (16 June 2017) | Viewed by 43818
Special Issue Editors
Interests: distributed energy resources management; electric vehicles integration in power systems; virtual power players, microgrids and smart grids management; multi-agents systems and power systems visualization
2. Air Institute, IoT Digital Innovation Hub, 37188 Salamanca, Spain
3. Department of Electronics, Information and Communication, Faculty of Engineering, Osaka Institute of Technology, Osaka 535-8585, Japan
Interests: artificial intelligence; smart cities; smart grids
Special Issues, Collections and Topics in MDPI journals
Interests: integration of different intelligent algorithms such as neural networks, fuzzy algorithms, swarm intelligence, and apply them for intelligent decision-making
Interests: optimal charging of electric vehicles and storages for secure power distribution system operation and power system balancing; Transactive control for managing distributed energy resources; multi-agent theory and simulation
Special Issues, Collections and Topics in MDPI journals
Interests: machine learning and pattern recognition for the smart grid (e.g., energy task scheduling, non-intrusive load monitoring, computational Intelligence for vehicle to grid) and intelligent audio analysis (e.g., multiroom voice activity detection and speaker localization)
Special Issue Information
Dear Colleagues,
The fast developments of the electric vehicles impose new challenges for power system management and planning. However, considering the recent EVs’ evolution perspectives, such as vehicle-to-grid technology, EVs also present opportunity for a smart grid in the near future. Within the smart grids context, the integration of EVs can be seen as a flexible load, as well as a generation resource, with the capacity to provide different services to the system, such as the frequency regulation and peak shaving.
Beyond the integration with power systems, the management of EVs can be integrated in a more embracing perspective like smart energy network management and planning, e.g., an integrated planning of traffic network, heating network, and power distribution network. With smart energy network planning technology, it can help in building an efficient and low-carbon society.
In the present Special Issue, we invite original and unpublished submissions concerning the integration of electric vehicles in future power systems allowing the development of the smart grids and smart energy network. Intelligent computing methods developments and applications in electric vehicles fields should be specifically addressed in the papers.
Potential topics include, but are not limited to:
- Electric vehicle charging infrastructure planning
- Electric vehicle fleet operation management
- Multi-agents’ application on electric vehicles charging and discharging
- Energy resources management considering electric vehicles
- Stochastic analysis and optimization of electric vehicles management in smart grids
- Use of electric vehicles/battery for frequency regulation, peak shaving and load leveling
- Power quality enhancement with electric vehicles
- Integrated management of electric vehicles considering the power grid and other critical infrastructures in a smart energy network context
- Electric vehicle driving pattern analysis and prediction
- Intelligent methods for electric motor fault detection
- Impact of communication delay on system integration of electric vehicles within a smart grid context
Dr. Hugo Morais
Prof. Dr. Juan Manuel Corchado
Prof. Dr. Lei Wang
Dr. Junjie Hu
Dr. Emanuele Principi
Guest Editors
Manuscript Submission Information
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Keywords
- electric vehicles
- smart grids
- smart cities
- intelligent energy resources management
- electric vehicle fleet
- stochastic analysis
- driving patterns forecast
- charging stations planning
- intelligent charging technologies
- battery management and operation
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