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Probabilistic risk-based security assessment for power systems with wind power generation

Citation

Nguyen, DH and Negnevitsky, M, Probabilistic risk-based security assessment for power systems with wind power generation, Proceedings of the IEEE Power and Energy Society General Meeting, 21-25 July 2013, Vancouver, Canada, pp. 1-5. ISSN 1944-9925 (2013) [Refereed Conference Paper]

Copyright Statement

Copyright 2013 IEEE

DOI: doi:10.1109/PESMG.2013.6672231

Abstract

The increase in using renewable energy sources, particularly wind power generation, worldwide raises a need to investigate alternatives to current power system planning and operation approaches due to the uncertain nature of the intermittent generation. This paper proposes a probabilistic approach based on risk assessment techniques for assessing power system security under high penetration of wind power. A composite risk index which reflects both probability and severity of each system event is used to assess the system security. To illustrate the effectiveness of the proposed approach, we apply it to a modified IEEE 14-bus system, and compare this approach with traditional deterministic security assessment. The results show that the proposed probabilistic approach effectively deals with system uncertainties and provides a better view on the system security.

Item Details

Item Type:Refereed Conference Paper
Keywords:deterministic security assessment, power system security, probabilistic risk-based security assessment, wind power generation
Research Division:Engineering
Research Group:Electrical and Electronic Engineering
Research Field:Power and Energy Systems Engineering (excl. Renewable Power)
Objective Division:Energy
Objective Group:Energy Conservation and Efficiency
Objective Field:Industrial Energy Conservation and Efficiency
Author:Nguyen, DH (Mr Dinh Nguyen)
Author:Negnevitsky, M (Professor Michael Negnevitsky)
ID Code:88406
Year Published:2013
Deposited By:Engineering
Deposited On:2014-01-31
Last Modified:2017-11-06
Downloads:2 View Download Statistics

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