Nonconvex Power Economic Dispatch by Improved Genetic Algorithm with Multiplier Updating Method

This paper presents an improved genetic algorithm with multiplier updating method (IGAMUM) to solve the nonconvex power economic dispatch problems (NPEDPs) constrained by reserve and prohibited operating zones (POZ). A genetic algorithm (GA) equipped with the improved evolutionary direction operator (IEDO) and migration called the improved genetic algorithm (IGA) is proposed, which can efficiently search and explore solutions. The multiplier updating method (MUM) is introduced to avoid deforming the augmented Lagrange function and resulting in difficulty of solution searching. The proposed method combining with the IGA and the MUM can use a wide range of penalty parameters and a small population size in evolutionary computation. Three examples are investigated, and the computational results of the proposed method are compared with that of the previous methods.

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