DocumentCode :
2637622
Title :
Unit commitment with nature and biologically inspired computing
Author :
Belede, Lingamurthy ; Jain, Amit ; Gaddam, Ravikanth Reddy
Author_Institution :
Power Syst. Res. Center, Int. Inst. of Inf. Technol., Hyderabad, India
fYear :
2010
fDate :
19-22 April 2010
Firstpage :
1
Lastpage :
6
Abstract :
Several strategies have been proposed to provide quality solutions to the Unit Commitment Problem and increase the potential saving in the power system operation. These include deterministic and stochastic search algorithms. One of the limitations of deterministic approaches is, they suffer from the curse of dimensionality when dealing with the modern power system with large number of generators. Recently evolutionary based search techniques are popularly applied to Unit Commitment Problem which may handle complex non-linear constraints and provide high quality solution. In this paper an attempt has been made to give a detailed survey of the application of the nature and biologically inspired computing techniques in the field of unit commitment problem in last two decades. This literature survey will be very useful to the new researchers working on this area of research.
Keywords :
Ant colony optimization; Artificial neural networks; Biology computing; Information technology; Lagrangian functions; Linear programming; Power systems; Relaxation methods; Simulated annealing; Stochastic processes; Ant Colony Optimization; Artificial Neural Networks; Genetic Algorithm; Particle Swarm Optimization; Simulated Annealing; Tabu Search; Unit Commitment;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Transmission and Distribution Conference and Exposition, 2010 IEEE PES
Conference_Location :
New Orleans, LA, USA
Print_ISBN :
978-1-4244-6546-0
Type :
conf
DOI :
10.1109/TDC.2010.5484284
Filename :
5484284
Link To Document :
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