Artificial fish swarm algorithm is a typical intelligent algorithm, which is suitable for solving nonlinear optimization problems, such as unit commitment optimization. However, the algorithm has some defectiveness including premature convergence and easily trapped into local extremes. To make up these disadvantages, this paper proposes a modified artificial fish swarm algorithm, which adopts a variable vision, makes adjustment to the movement strategy and combines the mutation operation of genetic algorithm. A mathematical model of unit commitment with phased optimization is established to solve the problem of long computing time results from large scale units. According to the results of simulations for up to 1000 units, the modified algorithm performs better in convergence and global search, and has certain advantages in solving unit commitment problems, and the phased optimization significantly shortens the calculation time of large-scale unit commitment optimization.
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