A genetic algorithm solution to the unit commitment problem
- Aristotle Univ. of Thessaloniki (Greece). Dept. of Electrical and Computer Engineering
This paper presents a Genetic Algorithm (GA) solution to the Unit Commitment problem. GAs are general purpose optimization techniques based on principles inspired from the biological evolution using metaphors of mechanisms such as natural selection, genetic recombination and survival of the fittest. A simple Ga algorithm implementation using the standard crossover and mutation operators could locate near optimal solutions but in most cases failed to converge to the optimal solution. However, using the Varying Quality Function technique and adding problem specific operators, satisfactory solutions to the Unit Commitment problem were obtained. Test results for systems of up to 100 units and comparisons with results obtained using Lagrangian Relaxation and Dynamic Programming are also reported.
- OSTI ID:
- 244732
- Report Number(s):
- CONF-950103--
- Journal Information:
- IEEE Transactions on Power Systems, Journal Name: IEEE Transactions on Power Systems Journal Issue: 1 Vol. 11; ISSN 0885-8950; ISSN ITPSEG
- Country of Publication:
- United States
- Language:
- English
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