A novel Multi-objective Modified Honey Bee Mating Optimization algorithm for Economic/Emission Dispatch

The main goal of Economic Dispatch (ED) in power systems is to distribute the total required generation between the generation units economically, while the equality and inequality constraints are satisfied. The conventional economic dispatch cannot satisfy the environmental protection requirements, since it only considers minimizing the total fuel cost. In this paper, a novel Multi-objective Modified Honey Bee Mating Optimization (MHBMO) algorithm to solve the Multi-objective Economic/Emission Dispatch (MEED) is presented. The MEED problem is formulated as a non-linear constrained multi-objective optimization problem. Therefore, in order to solve this problem, evolutionary methods because of independence on the type of objective function and constraints can be used. Honey Bee Mating Optimization (HBMO) is one of new evolutionary method in which presented by researchers. Original HBMO often converges to local optima, in order to avoid this shortcoming we propose a new method that improve the mating process. The proposed algorithm maintains a finite-sized repository of non-dominated solutions to generate Pareto-optimal set. Since the cost and emission functions are conflicting to each other, a fuzzy clustering technique is used to control the size of the repository. Numerical results for two standard IEEE test systems have been presented to illustrate the performance of the proposed method.