Cyber-Enabled Intelligence Control and Security Optimization for Complex Microgrid Networks
1RWTH Aachen University, Aachen, Germany
2Wuhan University, Wuhan, China
3Wuhan University of Technology, Wuhan, China
Cyber-Enabled Intelligence Control and Security Optimization for Complex Microgrid Networks
Description
Microgrids as typical Cyber-Physical Systems (CPS), characterized by the deep integration of physical power processes with information and communication technologies, can be generally modelled as a complex network of interacting CPS-based power elements with a large amount of data that involves heavy computation load. This can be used to tackle significant challenges in a variety of aspects, such as performance, security, reliability, scalability, flexibility, and sustainability. Handling such complex microgrid networks requires innovative computation architectures and salient computation techniques.
In past years, CPS-oriented complex microgrid networks have become popular paradigms that enable intelligent and self-configuring microgrid devices and sensors to be connected with the cloud in a CPS context. However, there are still some critical issues and challenges for cyber-enabled intelligence control and security optimization in their applications in complex microgrid networks, including networking, autonomy, software platform, physics-based analytics, big data mining and processing, and cybersecurity, and how to bring these technologies into practice. To address these issues, theories and solutions need to be developed, and engineering practices need to be demonstrated.
This Special Issue aims to promote new trends in state-of-the-art research covering all aspects of design, optimization, implementation, and evaluation of advanced solutions for CPS-oriented microgrid applications. We welcome both original research and review articles.
Potential topics include but are not limited to the following:
- Robustness control for CPS-based microgrid complex networks
- Security and safety solutions for CPS-oriented microgrid complex networks
- The control and optimization of CPS-oriented microgrid clusters
- Cyber-enabled distributed intelligence of microgrid complex networks
- Cyber-based security control for microgrid complex networks
- Ontology-based models for CPS-oriented microgrid complex networks
- Multi-agent system intelligence of microgrid complex networks
- Model-driven nonlinear dynamics of microgrid complex networks
- Resilient control frameworks for CPS-based microgrid system development
- Human-in-the-loop control for CPS-oriented microgrid complex networks