Chaotic Butterfly Optimization Algorithm Applied to Multi-objective Economic and Emission Dispatch in Modern Power System

Aims: To optimize the economic and emission dispatch of the thermal power plant. Background: Considering both the economic and environmental aspects, a combined approach has been developed to attain a solution for a problem known as the combined economic and emission dispatch problem. The CEED problem is a non-linear bi-objective problem with conflicting behaviour having all the practical constraints. Objective: A new optimization method is improvised by applying the chaotic mapping to the butterfly optimization algorithm. This method is applied to the Combined Economic and Emission Dispatch (CEED) problem for optimizing consumed fuel cost and produced environment pollutants. Methods: Improved Chaotic Butterfly algorithm is applied to the optimization problem to optimize combined economic and emission dispatch. Results: The proposed technique is tested on four different test systems with various practical constraints like valve point loading, ramp rate limit and prohibited operating zones. The obtained results from the chaotic butterfly optimization algorithm (CBOA) are compared with other optimization techniques providing an optimum solution for the CEED problem. Conclusion Considering the environmental impact, the novel metaheuristic swarm intelligence technique is applied. Different test systems with different practical operational constraints like valve-point loading, prohibited operating zones and ramp rate limits and emission dispatch have been analyzed to validate the implementation of the proposed algorithm in real life CEED problem situations.