C. Jiang (PRC)
Power System, Multi-Objective Optimization, ChaosMutation, Metropolis Selection Criteria, EvolutionaryProgramming
This paper deals with the mutation operators and the
selection Criteria that affect the convergence and
robustness of the evolutionary programming (EP), and
suggests a chaos mutation and metropolis selection
evolutionary programming method (CMMEP).
Introducing chaos dynamics into mutation operators of
evolutionary programming, the new method adopts the
certainty method of like-stochastic to get mutation
operators which breaks through the conventional thought
with mutation by stochastic numbers of fixed distribution.
Also, it introduces the metropolis selection of the
simulated annealing in evolutionary programming to
construct new selection operators. Applied to multi
objective OPF, this algorithm is proved to enjoy
timesaving convergence and perfect performance in the
multi-objective optimization dispatch in power system.