1. Stability Analysis of Microgrid Islanding Transients Based on Interconnected Dissipative Subsystems
- Author
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Phuong H. Nguyen, M.H. Roos, J.G. Slootweg, Johan Morren, Electrical Energy Systems, EIRES System Integration, EAISI Foundational, Cyber-Physical Systems Center Eindhoven, and Intelligent Energy Systems
- Subjects
Stability criteria ,General Computer Science ,Computer science ,microgrids ,020209 energy ,Resistance ,Islanding ,02 engineering and technology ,Fault (power engineering) ,Stability (probability) ,Transient analysis ,islanding ,Control theory ,0202 electrical engineering, electronic engineering, information engineering ,Inductance ,Lyapunov methods ,power system transients ,Stability analysis ,020206 networking & telecommunications ,Power system stability ,Nonlinear system ,Dissipative system ,Microgrid ,Transient (oscillation) ,Energy (signal processing) - Abstract
To ensure successful islanding of microgrids after a fault has occurred, the transient stability should be analyzed under a set of expected operating conditions during the design and operation of microgrids. Transient stability analysis is conventionally performed with time-domain analysis which is computationally expensive and does not quantify the stability margin. Energy-based methodologies can determine the stability margin, however existing methodologies require significant simplifications to be applied to the microgrid model. The energy-based stability analysis methodology proposed in this paper enables the analysis of high-dimension nonlinear microgrid systems and quantification of the stability margin within reasonable time. The performance of the methodology is validated by analyzing a case study microgrid and comparing the results to time-domain analysis and to a state-of-the-art methodology proposed in the literature. The results indicate that the proposed methodology has a significantly lower computational burden and similar accuracy compared to existing energy-based methodologies. The methodology is able to improve the probability of stable islanding of the case study microgrid from 74% up to 94% when only optimizing the design, and up to 100% when optimizing design and control actions.
- Published
- 2021
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