Multi-objective economic-emission optimal load dispatch using bacterial foraging algorithm

Abstract

The optimal economic-emission dispatch problem (EED) is addressed in this paper considering the environmental aspects. To solve this multi-objective problem, a modified bacterial foraging algorithm (MBFA) is implemented. In addition to minimizing the cost function, the minimization of NO _x , SO ₂ and CO ₂ gaseous emissions is also considered using the weighted-sum method. The BFA is an evolutionary optimization technique inspired by the foraging behavior of the E. coli bacteria. The BFA has been successfully used to tackle small scale optimization problems. However, when applied to larger constrained problems, it shows poor convergence properties. To overcome these difficulties, due to the complexity and high-dimensionality of the search space of the EED problem, significant modifications are introduced. The MBFA is applied to obtain the optimal or near optimal load dispatch and capture the trade-off set of solutions.