A Comparative Smart Computation Algorithm for Economic And Emission Dispatch Optimization of Tanjung Jati Power Plant

Abstract

This research delves into optimization strategies for enhancing power generation efficiency and reducing costs in PLTU Tanjung Jati. The study explores three computational algorithms for optimization: Grey Wolf Optimization (GWO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), focusing on optimizing power generation costs while considering penalty costs and emissions. Through extensive simulations and evaluations, the results indicate that the GWO algorithm achieves the most optimal outcomes in terms of cost optimization, demonstrating fast convergence and lesser simulation time compared to the other algorithms. The research provides valuable insights into selecting optimal algorithms for complex optimization problems like Combined Economic Emission Dispatch (CEED) in power generation systems, ultimately contributing to more efficient and cost-effective power generation.