Name
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICGEC.2012.147 | ICGEC |
Keywords | Field | DocType |
load uncertainty,fuzzy set theory,exact forecasting,correct prediction,maximal blackout time,two-stage multiobjective fuzzy programming model,improved two-layer multi-objective particle,particle swarm optimisation,power generation dispatch,total generation cost,two-stage multiobjective unit commitment optimization,two-stage multiobjective,fuzzy credibility theory,future load uncertainty,future demand,two-stage multi-objective fuzzy programming,two-layer multiobjective particle swarm optimization algorithm,future power demand,swarm optimization algorithm,particle swarm optimization algorithm,power generation scheduling,two-stage multi-objective unit commitment | Particle swarm optimization,Mathematical optimization,Computer science,Fuzzy logic,Power system simulation,Multi-swarm optimization,Credibility theory,Fuzzy set,Artificial intelligence,Blackout,Machine learning,Metaheuristic | Conference |
ISSN | ISBN | Citations |
1949-4653 | 978-1-4673-2138-9 | 0 |
PageRank | References | Authors |
0.34 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bo Wang | 1 | 224 | 53.43 |
| You Li | 2 | 30 | 4.45 |
| Junzo Watada | 3 | 411 | 84.53 |