Advanced hybrid genetic algorithm for short-term generation scheduling

IEE Proceedings: Generation, Transmission and Distribution

Volumn 148, Issue 6, 2001, Pages 511-517

  El Desouky, A A ^a   Aggarwal, R ^a   Elkateb, M M ^a   Li, F ^a  

^a UNIVERSITY OF BATH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; GENETIC ALGORITHMS; NEURAL NETWORKS; OPTIMIZATION;

LOAD FORECAST ERROR; PRIORITY LIST (PL);

ELECTRIC POWER GENERATION;

EID: 0035518675     PISSN: 13502360     EISSN: None     Source Type: Journal    
DOI: 10.1049/ip-gtd:20010642     Document Type: Conference Paper

References (13)

1. A genetic algorithm solution to the unit commitment problem
2. Short-term generation scheduling with transmission and environmental constraints using an augmented Lagrangian relaxation
3. A solution method of unit commitment by artificial neural networks
4. Hybrid adaptive techniques for electric-load forecast using ANN and ARIMA
5. A heuristic short-term unit commitment
6. Scheduling of generators with a hybrid genetic algorithm
7. IEEE reliability test system
8. Refined genetic algorithm- economic dispatch example
9. Effects of ramp-rate limits on unit commitment and economic dispatch