1. Model Order Reduction for Reliability Assessment of Flexible Power Networks
- Author
-
Ran Li, Chenghong Gu, Antonio De Paola, Ignacio Hernando-Gil, Mike Brian Ndawula, ESTIA Recherche, and Ecole Supérieure des Technologies Industrielles Avancées (ESTIA)
- Subjects
Computer science ,020209 energy ,Monte Carlo method ,Complex system ,Balanced truncation ,Distributed energy resources ,Energy Engineering and Power Technology ,02 engineering and technology ,7. Clean energy ,distributed energy resources ,[SPI.AUTO]Engineering Sciences [physics]/Automatic ,Robustness (computer science) ,0202 electrical engineering, electronic engineering, information engineering ,SDG 7 - Affordable and Clean Energy ,Electrical and Electronic Engineering ,Monte Carlo simulation ,Model order reduction ,Mathematical model ,business.industry ,balanced truncation ,[SDE.IE]Environmental Sciences/Environmental Engineering ,020208 electrical & electronic engineering ,[SPI.NRJ]Engineering Sciences [physics]/Electric power ,system reliability ,Reliability engineering ,[SPI.TRON]Engineering Sciences [physics]/Electronics ,[SPI.ELEC]Engineering Sciences [physics]/Electromagnetism ,System reliability ,Smart grid ,distribution networks ,Distribution networks ,model order reduction ,Distributed generation ,business ,Network analysis - Abstract
International audience; Model order reduction (MOR) has demonstrated its robustness and wide applicability in simulating large-scale mathematical models in the engineering research domain. In this paper, MOR techniques are applied to quantify relevant reliability metrics of power distribution systems and the impact associated with the integration of different smart grid technologies. To the best of the authors' knowledge, this is the first application of MOR techniques of balanced truncation to derive reliability models of electricity networks, which exhibit a reduced number of equivalent components and thus simplify the complexity for network analysis. The extensive case studies presented, based on both radial and meshed systems, demonstrate that the proposed technique allows for a faster reliability assessment through Monte Carlo simulation while preserving high accuracy. The proposed methodology can also be applied to systems endowed with photovoltaic and energy storage technologies, emphasising that this approach represents a promising starting point for reliability analysis of more complex systems, which are normally characterised by a large penetration of these distributed energy resources.
- Published
- 2021