DocumentCode :
560857
Title :
A solution to dynamic economic dispatch with prohibited zones using a Hopfield neural network
Author :
Benhamida, Farid ; Bendaoued, Abdelber ; Medles, Karim ; Ayad, Abdelghani ; Tilmatine, Amar
Author_Institution :
Dept. of Electr. Eng., UDL Univ., Sidi Belabbes, Algeria
fYear :
2011
fDate :
1-4 Dec. 2011
Abstract :
A solution to the dynamic economic dispatch (DED) for 24-hour dispatch intervals (one day) with practical constraints using a Hopfield neural network (HNN) is proposed in this paper. The DED in this paper must satisfy the following constrained the system load demand, the spinning reserve capacity, the ramping rate limits and finally the prohibited operating zone. The feasibility of the proposed approach is demonstrated using two power systems, and it is compared with the other methods in terms of solution quality and computation efficiency.
Keywords :
Hopfield neural nets; power engineering computing; power generation dispatch; power generation economics; Hopfield neural network; dynamic economic dispatch; power systems; prohibited zones; ramping rate; spinning reserve capacity; system load demand; Economics; Generators; Genetic algorithms; Neurons; Power system dynamics; Propagation losses; Spinning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Electronics Engineering (ELECO), 2011 7th International Conference on
Conference_Location :
Bursa
Print_ISBN :
978-1-4673-0160-2
Type :
conf
Filename :
6140224
Link To Document :
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