DocumentCode :
3283084
Title :
Two-Stage Multi-objective Unit Commitment Optimization under Future Load Uncertainty
Author :
Bo Wang ; You Li ; Watada, Junzo
Author_Institution :
Grad. Sch. of Inf., Production & Syst., Waseda Univ., Kitakyushu, Japan
fYear :
2012
fDate :
25-28 Aug. 2012
Firstpage :
128
Lastpage :
131
Abstract :
The unit commitment problem is to reduce the total generation cost as much as possible while satisfying future power demands. Therefore, optimization must be performed based on correct predictions of future demands. However, various uncertain factors affect these loads making an exact forecasting unsuccessful. This study mitigates this difficulty by applying fuzzy set theory and the objective is to build a two-stage multi-objective fuzzy programming model. to define the supply reliability effectively, we propose a new concept of maximal blackout time based on the fuzzy credibility theory. in addition, an improved two-layer multi-objective particle swarm optimization algorithm is designed as the solution. Finally, the performance of this study is discussed in comparison with experimental results from several test systems.
Keywords :
fuzzy set theory; particle swarm optimisation; power generation dispatch; power generation scheduling; future load uncertainty; fuzzy credibility theory; fuzzy set theory; total generation cost; two-layer multiobjective particle swarm optimization algorithm; two-stage multiobjective fuzzy programming model; two-stage multiobjective unit commitment optimization; Cost function; Equations; Mathematical model; Particle swarm optimization; Reliability; Schedules; Fuzzy set theory; Load uncertainty; Maximal blackout time; Particle swarm optimization algorithm; Two-stage multiobjective;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Genetic and Evolutionary Computing (ICGEC), 2012 Sixth International Conference on
Conference_Location :
Kitakushu
Print_ISBN :
978-1-4673-2138-9
Type :
conf
DOI :
10.1109/ICGEC.2012.147
Filename :
6457196
Link To Document :
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