Resilience of smart integrated energy systems

Start Page
1887
End Page
1913
Citation
Springer 978-3-030-97940-9: 1887-1913 (2023)
Publisher DOI
10.1007/978-3-030-97940-9_109
Scopus ID
2-s2.0-85208318684
Publisher
Springer
ISBN of container
978-3-030-97940-9
Energy systems, particularly power systems as critical infrastructures, are of supreme importance to society. The current significant developments, namely evolving producer and consumer characteristics (e.g., volatile and hard-to-predict renewables), higher growth of sector-coupling solutions, and on top, sophisticated control and digitalization solutions – transforming the energy systems into a complex cyber-physical system of systems – jeopardize the operation of the overall system. If it fails to make the new energy system as robust and resilient as the current system, the consequences can be drastic and a threat to society. This chapter defines the resilience concept and presents the current practices and methods to evaluate and enhance the resilience of smart energy systems. To this end, after providing a comprehensive background to the paradigm shift, resilience metrics suggested by communities such as IEEE and Cigré are presented – focusing mainly on power systems. A multi-domain approach that outlines resilience indexes for heat, gas, and electricity sectors is also presented to as a more holistic methodology. In addition, it is explained how emerging technologies such as digital twins and artificial intelligence can support the evaluation of system resilience. This chapter also motivates key resilience strategies and addresses the state-of-art approaches in two important categories: (1) situational awareness and system knowledge and (2) operational flexibility and adaptive mechanism. Different examples of these categories, such as anomaly-aware monitoring systems, software-defined networking, and cellular concepts, are provided here – from mutually cyber and physical viewpoints.
Subjects
digitalization
ICT
Integrated energy system
sector coupling
Resilience
DDC Class
004: Computer Sciences
621: Applied Physics
333.7: Natural Resources, Energy and Environment