Application of Float Genetic Algorithms-Partially Solved Combined With Punishing Function in Power Plant Units Commitment Problem

To address the optimization premature convergence problem of unit commitment problem(UCP) in power plant with float genetic algorithms(FGA) ,a refined FGA with the constrained conditions of partially solved combined with punishing function(FGA-PPF) were introduced FGA-PPF refined in the dealing with its constrained conditions,the strategy of mutation,initialization of population of FGA with respect to the features of UCP. FGA-PPF resolved the problem of pre-mature in FGA,in the application to a five units power plant UCP,The results shows that the optimization success rate can reach 100% with the FGA-PPF.