Bio-inspired approaches for a combined economic emission dispatch problem
Journal
Human-Assisted Intelligent Computing
Date Issued
2023
Author(s)
Vasant, Pandian
Banik, Anirban
Thomas, J. Joshua
Marmolejo Saucedo, José Antonio
Fiore, Ugo
Weber, Gerhard-Wilhelm
Type
text::book::book part
Abstract
In chapter 3, economic load dispatch (ELD) and emission dispatch problems are optimized separately using particle swarm optimization, quantum-inspired particle swarm optimization, and quantum-inspired bat algorithm for the various numbers of units. Later, both objectives are assumed simultaneously as an optimization problem with multiple objectives. The emission dispatch problem is divided into three independent objectives to minimize SO2, NO X and CO2 emissions. Thus, the combined economic emission dispatch (CEED) problem is an optimization problem with four objectives. A unit-wise price penalty factor was assumed to change over all the targets into a single target. The idea is to attain a balanced trade-off between secured and profitable energy choices while maintaining a healthy and sound environment. The quantum computing phenomenon was integrated with swarm intelligence-based particle swarm optimization (PSO) and bat algorithm (BA) to make them computationally more powerful and robust. The results obtained from quantum-inspired bat algorithm (QBA) and quantum particle swarm optimization (QPSO) to solve the CEED problem contrasted with other existing techniques such as Lagrangian relaxation, PSO, and simulated annealing. © Copyright 2024 IOP Publishing