Chaotic Singer Grasshopper Optimization Algorithm for solving Combined Economic and Emission Dispatch

In this paper, a Chaotic Singer Grasshopper Optimization Algorithm (CS-GOA) is proposed to solve the Combined Economic and Emission Dispatch optimization problem. The premier objectives of CEED problem are to find the minimum fuel cost of power generation for the lowest possible pollutant emission, which is achieved simultaneously by a proper distribution of power generation duty among the generators. Price Penalty Factor (PPF) methodology is used to transform CEED into a single-objective optimization problem. A Chaotic Singer version of Grasshopper Optimization Algorithm is proposed and tested for solving CEED. The performance assessment tests consist of four different benchmark test systems with complexities such as different load demands and Valve-point loading of turbine. The attained simulation results highlight the superiority of CS-GOA in solving CEED problem in aspects of reduced fuel cost, emission and rapid convergence.