This article develops a model of load frequency control for an interconnected two-area thermal–hydro power system under a deregulated environment. In this article, a fuzzy logic controller is optimized by a genetic algorithm in two steps. The first step of fuzzy logic controller optimization is for variable range optimization, and the second step is for the optimization of scaling and gain parameters. Further, the genetic algorithm-optimized fuzzy logic controller is compared against a conventional proportional-integral-derivative controller and a simple fuzzy logic controller. The proposed genetic algorithm-optimized fuzzy logic controller shows better dynamic response following a step-load change with combination of poolco and bilateral contracts in a deregulated environment. In this article, the effect of the governor dead band is also considered. In addition, performance of genetic algorithm-optimized fuzzy logic controller also has been examined for various step-load changes in different distribution unit demands and compared with the proportional-integral-derivative controller and simple fuzzy logic controller.