New Optimization Algorithm Inspired by Kernel Tricks for the Economic Emission Dispatch Problem With Valve Point

Abstract

With the increasing concern over environment protection, Economic Emission Dispatch (EED) problem has received much attention. It is essentially a Multi-objective Optimization Problem, which minimizes both fuel cost and emission pollution simultaneously, as well as meets some system limits. This study transforms EED problem to a single-objective problem with weighted sum method, and then use Newton method to solve the equality constraint iteratively and introduce a common penalty function to deal with the inequality constraint. Moreover, this study tries to propose a new meta-heuristic algorithm inspired by kernel tricks to solve EED problem with no hyper parameters to be tuned. The new algorithm can map a non-linear objective function into a linear one with higher-dimension. Thus the optimization process could be transformed into a linear process, which is more likely to get the optimum solution. When applied in the 3 real-world EED cases with valve point, the new algorithm achieved a better performance compared with other algorithms in the literature.

Keywords

• Economic emission dispatch
• Kernel search optimization
• meta-heuristic algorithm
• swarm intelligence