Periodic Reporting for period 1 - CRMG (Cyber Resilience of Micro-Grids)
Reporting period: 2021-10-01 to 2023-09-30
The microgrid is a small-scale power system consisting of distributed energy resources and local loads, which can operate independently or grid-connected, to increase system flexibility, resilience, and economics. As the control and operation functions in microgrids are achieved by communication infrastructures, it brings along cyber-security problems. The information manipulation and disruption in the control process will damage the secure and stable operation of the microgrid systems. In this project, we provide cyber-resilience analysis and enhancement methods for microgrids from the system and control perspective. The microgrid small-signal stability under cyber-attacks that aims to destabilize the system is analyzed. The data-driven cyber-resilient control strategy is developed based on adversarial deep reinforcement learning. The proposed research is important and timely, as the cyber resilience of the electricity grid is an emerging and urgent concern. The networked control system and its cyber-security of microgrids are important topics to be explored before large-scale applications in future power systems. The analysis and countermeasures in this project could contribute to the cyber-resilience of the electricity grid and future microgrid development in Europe.
The project includes 6 work packages (WP1-WP6), which were originally carried out in a 24-month period. As the fellow accepted a faculty job offer, this project ends up with a 12-month period. The work packages regarding scientific and training parts are all compressed into one year. However, the core work is still accomplished. The WP1 is conducted to provide the modelling and analysis of MG under cyber-attack. The WP2 is conducted to provide the cyber resilience enhancement method by using deep reinforcement learning. As for the reduction of the original research plan and Covid-19 influence on laboratory entry, WP3 is changed to a co-simulation-based validation of the proposed method. In general, the technical content of this project is accomplished, where a cyber-resilience analysis and enhancement framework for microgrids has been established. There are one journal paper and one conference paper submission to report the results. The researchers have attended conferences and organized activities and webinars to increase the research impact.
Through this CRMG project, the researcher has a deeper understanding of the stability, control, and security of electrical systems as well as model-based and data-driven control approaches. As interdisciplinary research of power systems, cyber-security, control, and machine learning, the deliverables, and publications of this project are expected to have a high impact on the research community and promote the emerging research on cyber-resilience of microgrids. The submitted paper has received very positive comments from the reviewers. Besides, the researcher has given talks at the CAP group of Imperial and IEEE IES Guangzhou Chapter to share the progress of this project. A special panel session has also been organized at IEEE PES GM 2022 to promote the development of this area. The researcher has established new collaborations and extended his network, which also contribute to the dissemination of this project.