A genetic algorithm based approach to thermal unit commitment of electric power systems

Electric Power Systems Research

Volumn 34, Issue 1, 1995, Pages 29-36

  Ma, X ^a   El Keib, A A ^a   Smith, R E ^a   Ma, H ^a  

^a UNIVERSITY OF ALABAMA   (United States)

Author keywords

Genetic algorithms; Optimization techniques; Unit commitment

Indexed keywords

COMBINATORIAL MATHEMATICS; ELECTRIC LOAD FORECASTING; ENCODING (SYMBOLS); GENETIC ALGORITHMS; MATHEMATICAL PROGRAMMING; OPTIMIZATION; PARALLEL PROCESSING SYSTEMS; PROBLEM SOLVING; ROBUSTNESS (CONTROL SYSTEMS);

FORCED MUTATION; THERMAL UNIT COMMITMENT;

ELECTRIC POWER SYSTEMS;

EID: 0029332876     PISSN: 03787796     EISSN: None     Source Type: Journal    
DOI: 10.1016/0378-7796(95)00954-G     Document Type: Article

References (27)

1. A study of the economic shutdown of generating units in daily dispatch
2. Large scale hydrothermal unit commitment method and results
3. Evaluation of dynamic programming based methods and multiple area representation for thermal unit commitment
4. A solution of the unit commitment problem via decomposition and dynamic programming
5. An enhanced dynamic programming approach for unit commitment
6. Integer programming approach to the problem of optimal unit commitment with probabilistic reserve determination
7. A branch-and-bound algorithm for unit commitment
8. Combination of Lagrangian relaxation and linear-programming approaches for fuel constrained unit commitment problems
9. A method for solving the fuel constrained unit commitment problem
10. Implementation of a Lagrangian relaxation based unit commitment problem
11. Environmentally constrained unit commitment
12. Unit commitment by simulated annealing
13. A note on Boltzmann tournament selection for genetic algorithms and population-oriented simulated annealing
14. Research and development needs for power system control through 2020
15. Real-time control and operation of power systems
16. Investigations on solving the load flow problem by genetic algorithms
17. Optimal capacitor placement in distribution systems by genetic algorithm
18. Optimal selection of capacitors for radial distribution systems using a genetic algorithm
19. Optimal clustering of power networks using genetic algorithms
20. A genetic algorithm-based approach to economic dispatch
21. Genetic algorithm solution of economic dispatch with valve point loading
22. Implementation of genetic algorithm for distribution systems loss minimum re-configuration
23. Optimal scheduling of thermal generating units