DocumentCode :
3219389
Title :
Unit commitment in composite generation and transmission systems using Genetic Algorithm
Author :
Chandrasekaran, K. ; Simon, Sishaj P.
Author_Institution :
Dept. of EEE, Nat. Inst. of Technol., Tiruchirappalli, India
fYear :
2009
fDate :
9-11 Dec. 2009
Firstpage :
1115
Lastpage :
1120
Abstract :
This paper proposes a new method for the incorporation of the generation unit and transmission line unavailability in the solution of the unit commitment problem. The above parameters are taken into account in order to assess the required spinning reserve capacity at each hour of the dispatch period, so as to maintain an acceptable reliability level. The unit commitment problem is solved by a Genetic Algorithm resulting in near-optimal unit commitment solutions. The evaluation of the required spinning reserve capacity is performed by implementing reliability constraints, based on the expected unserved energy and loss of load probability indexes. In this way, the required spinning reserve capacity is effectively scheduled according to the desired reliability level. The results are compared with LR to prove the efficiency of the proposed method.
Keywords :
genetic algorithms; power generation dispatch; power generation planning; power generation reliability; power generation scheduling; power transmission lines; power transmission planning; power transmission reliability; acceptable reliability level; composite generation; expected unserved energy; genetic algorithm; loss of load probability indexes; reliability constraints; spinning reserve capacity; transmission systems; unit commitment; Capacity planning; Costs; Genetic algorithms; Lagrangian functions; Load forecasting; Maintenance; Quadratic programming; Spinning; Transmission lines; Uncertainty; Expected unserved energy (EUE) indexes; Genetic Algorithm (GA); Loss of load probability (LOLP); Spinning reserve assessment; Unit commitment (UC); composite Generation and transmission systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4244-5053-4
Type :
conf
DOI :
10.1109/NABIC.2009.5393813
Filename :
5393813
Link To Document :
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