Smart Evolutionary Algorithm for Static Economic Load Dispatch Optimization in a Thermal Generating Station

TL;DR: The paper demonstrated a novel approach to solving certain kinds of real-world problems, contributing a method that have advanced the state of the art in solving a specific optimization problem in the area of economic load dispatch.

Abstract: The Economic Load Dispatch (ELD) problem is an optimization task with emphasis on how power generating companies (GENCOs) will be able to meet the power demands of the distribution companies (DISCOs) and electricity consumers, and at the same time minimize both under/over generation of electricity, and also minimize the operational costs of running the units in their various stations. This paper implemented a Smart Evolutionary Algorithm, which combines a standard Evolutionary Algorithm with a smart mutation operator that is applied to the Static ELD problem. It also investigated and analyzed three distinct variants of the smart mutation operator. The operator focused mutation on genes contributing mostly to cost of generation and penalty violations in the fitness function. Rather than using a generic off-the-shelf optimization package, the paper demonstrated a novel approach to solving certain kinds of real-world problems, contributing a method that have advanced the state of the art in solving a specific optimization problem in the area of economic load dispatch.