DocumentCode :
3666143
Title :
Experimental implementation of Multi-Agent System Algorithm to prevent Cascading Failure after N-1-1 contingency in smart grid systems
Author :
R. Belkacemi;A. Babalola;S. Zarrabian
Author_Institution :
Department of Electrical and Computer Engineering, Tennessee Technological University, Cookeville, USA
fYear :
2015
fDate :
7/1/2015 12:00:00 AM
Firstpage :
1
Lastpage :
5
Abstract :
Cascading Failure and Blackout Event is one of the major concerns to all in the Power System industry. Recent literature mainly focused on predicting the occurrence of this catastrophic event and suggestions on ways to curtail the spread of Cascading Failure. No research, to our knowledge, as focused on preventing Cascading Failure without the use of high cost precautionary steps. This work utilizes an adaptive Multi-Agent System Algorithm in a smart grid system with two-way communication capability to successfully prevent Cascading Failure and Blackout Event after N-1-1 transmission line contingency condition with more than one transmission line overloaded. The proposed algorithm stops the cascading failure after the N-1-1 contingency by redispatching the power from the generators through the use of pre-stated mathematical combinations and the consideration of necessary constraints and factors. We obtained experimental results instead of the popular simulation results that has been the norm for publications on Cascading Failures and Blackout Event. The generation and transmission side of IEEE 30-bus system was used as the experimental test bed. It was ascertained that the test bed can experience a Cascading Failure and Blackout Event if no preventive measure was taken. We then utilized the algorithm to prevent Cascading Failure. The experimental results affirm the efficacy of the proposed algorithm.
Keywords :
"Generators","Power system faults","Power system protection","Power transmission lines","Multi-agent systems","Smart grids"
Publisher :
ieee
Conference_Titel :
Power & Energy Society General Meeting, 2015 IEEE
ISSN :
1932-5517
Type :
conf
DOI :
10.1109/PESGM.2015.7286630
Filename :
7286630
Link To Document :
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