Combined Economic and Emission Dispatch of Thermal Power Generation Systems for 24-Hours Load Demand

A fundamental difficulty in the turf of power engineering is the optimization of thermal power generation systems to meet 24-hour load demand while minimizing economic costs and emissions. This study suggests a combined economic and emission dispatch (CEED) method as a comprehensive solution to this delinquent. The goalmouth of the CEED problem is to find the best distribution of generation resources while taking into account both environmental and economic considerations, such as emissions and fuel costs. The CEED problem is represented mathematically in this paper, taking into account a number of limitations, including power balance, generator capacity restrictions, and emission limitations. Metaheuristic algorithms such as genetic algorithm (GA), particle swarm optimization (PSO), and simulated annealing (SA) are employed to solve this multifaceted optimization problem. These algorithms offer efficient solutions by exploring the answer space to find the finest trade-off between economic costs and emissions. To illustrate the success of the suggested tactic, a case study featuring a thermal power generation system with several generators is used. The findings suggest that, in comparison to conventional dispatch techniques, the CEED strategy can considerably lower economic expenses as well as emissions. Additionally, the sensitivity analysis shows how different parameters affect the best solution, giving system operators and policymakers valuable information. All things considered, the CEED technique discussed in this study provides a workable and successful way to optimize environmental and economic goals in thermal power generation systems at the same time, enhancing the longevity and financial viability of power production operations.