SMO Algorithm to Unravel CEED Problem using Wind and Solar

Abstract

This research proposes a more advanced way to address Combined Economic Emission Dispatch (CEED) concerns. Economic Load Dispatch (ELD) and Economic Emission Dispatch (EED) have been implemented to reduce generating unit fuel costs and emissions. When both economics and emission targets are taken into account, the dispatch of an aggregate cost-effective emission challenge emerges. This research affords a mathematical modeling-based analytical technique for solving economic, emission, and collaborative economic and emission dispatch problems with only one goal. This study takes into account both the fuel cost target and the environmental impact of emissions. This bi-intention CEED problem is converted to a solitary goal function using a price penalty factor technique. In this case, a metaheuristic and an environment-inspired, intelligent Spider Monkey Optimization technique (SMO) are used to address the CEED dilemma. By following the generator’s scheduling process, the SMO method is used to regulate the output from the power generation system in terms of pollution and fuel cost. The Fission-Fusion social (FFS) structure of spider monkeys promotes them to utilize a global optimization method known as SMO during foraging behaviour. The emphasis is mostly on lowering the cost of generation and pollution in order to improve the efficiency of the power system and handle dispatch problems with constraints. The economic dispatch has been remedied, and the improved result demonstrates that the system’s performance is stable and flexible in real time. Finally, the system’s output demonstrates that the system has improved in resolving CEED difficulties. When compared to earlier investigations, the proposed model’s findings have improved. As the generating units, wind and solar are used to explore the CEED crisis in the IEEE 30 bus system.