Unit commitment problems using GA

In this paper, unit commitment (UC) using the genetic algorithm (GA) with different implementation techniques, such as different sampling space methods, different selection schemes, different fitness value scaling methods and different crossover/mutation rates, is developed and implemented in 10 units system and 110 units system. This paper thoroughly studies the effects on convergent time, convergent generation number and convergent value of GA based on different implementation techniques, which indicates that the algorithm is effective in a certain degree, and reveals that different implementation techniques have different effects on convergent time, convergent generation number, and convergent value of GA-based UC. A good foundation is settled for further practicable study of GA-based UC.