Unit commitment using hybrid models: A comparative study for dynamic programming, expert system, fuzzy system and genetic algorithms

International Journal of Electrical Power and Energy Systems

Volumn 23, Issue 8, 2001, Pages 827-836

  Padhy, N P ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY ROORKEE   (India)

Author keywords

Dynamic programming; Expert system; Fuzzy system; Neural network and genetic algorithms; Unit commitment

Indexed keywords

COMPUTATIONAL COMPLEXITY; DYNAMIC PROGRAMMING; ELECTRIC CURRENTS; ELECTRIC LOADS; EXPERT SYSTEMS; FUZZY SETS; GENETIC ALGORITHMS; MATHEMATICAL MODELS; NEURAL NETWORKS;

POWER SYSTEM OPERATORS;

ELECTRIC POWER SYSTEM INTERCONNECTION;

EID: 0035501988     PISSN: 01420615     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0142-0615(00)00090-9     Document Type: Article

References (21)

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7. Fuzzy dynamic programming: An application to unit commitment
8. A solution method of unit commitment by artificial neural networks
9. Neural networks approach for solving economic dispatch problem with transmission capacity constraints
10. A hybrid artificial neural network-dynamic programming approach to unit commitment
11. Multi-objective generation scheduling using fuzzy optimal search technique
12. A genetic algorithm for generator scheduling in power systems
13. Refined genetic algorithm - Economic dispatch example
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15. Evolutionary-programming-based algorithm for environmentally-constrained economic dispatch
16. Fuzzy sets
17. An evolutionary programming solution to the unit commitment problem