Search and Rescue Optimization for Combined Economic Load and Emission Dispatch

Abstract

The goal of combined economic and emission dispatch (CEED) in the power system is to solve the economics management of generators in order to achieve both minimum fuel prices and pollution levels while meeting load demands and operating limits. The Search and Rescue (SAR) optimization methodology is developed in this study to address the CEED problem, and the results gained are compared with the Evolutionary Programming and Flower Pollination Algorithm methods. Those analyses are able to evaluate the effectiveness as well as the rate of convergence of the methods under consideration. In general, the CEED problem is initially considered a bi-objective problem that has been turned into a single objective function by the use of the price penalty element in its solution. Both solutions were tested on an IEEE 10-Generator 39-Bus System, which has a valve point impact with transmission loss. MATLAB is additionally utilized to run modeling for the evaluated system, with each system subjected to three separate load demands. The results reveal that the SAR technique performs better because it generates resilient and effective solutions to the CEED problem with the lowest fuel price, greenhouse gas emissions, CEED price, and power loss.