DocumentCode
2622737
Title
Application of meta-heuristics algorithms in discrete model of steady-state load-shedding
Author
Rad, B.F. ; Abedi, M.
Author_Institution
Dept. of Electr. Eng., Amirkabir Univ. of Technol., Tehran
fYear
2008
fDate
22-24 May 2008
Firstpage
173
Lastpage
177
Abstract
Optimal load-shedding during contingency situations is one of the most important issues in planning, security, and operation of power systems. Load-shedding is necessary to prevent phenomena such as voltage collapse and line over load which may lead to cascade outages and then black-out. In this paper, a new optimal load-shedding approach is presented. One of the important specifications of this method is that amount of load shed from each bus is determined. In this research, studies consist of critical single line and generator outage based on contingency ranking. The optimal load-shedding is formulated as a nonlinear optimization problem subject to operation and security constraints, where objective function is the service interruption cost. Finally, the load-shedding problem is also solved by genetic and particle swarm optimization algorithms, in which weighting factors are determined using AHP method. The proposed method is tested on the IEEE 30 bus system, and the results are presented.
Keywords
genetic algorithms; load shedding; particle swarm optimisation; AHP method; IEEE 30 bus system; contingency ranking; discrete model; genetic algorithm; meta-heuristics algorithms; nonlinear optimization problem; optimal load-shedding approach; particle swarm optimization algorithms; power system planning; power system security; steady-state load-shedding; Constraint optimization; Cost function; Genetics; Load modeling; Particle swarm optimization; Power system modeling; Power system planning; Power system security; Steady-state; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Optimization of Electrical and Electronic Equipment, 2008. OPTIM 2008. 11th International Conference on
Conference_Location
Brasov
Print_ISBN
978-1-4244-1544-1
Electronic_ISBN
978-1-4244-1545-8
Type
conf
DOI
10.1109/OPTIM.2008.4602362
Filename
4602362
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