Performance Assessment of Grey Wolf Optimizer for Economic and Emission Load Dispatch

This article proposes grey wolf optimization (GWO), a novel evolutionary optimization technique for the best operating strategy of economic load dispatch (ELD) that is based on the behavior of grey wolves. The problem takes into account the nonlinear features of generators, such as forbidden operating zones, valve point discontinuities, and ramp rate restrictions. When looking for an optimal solution, the Gray Wolf Optimization (GWO) approach doesn't require a comprehension of the objective function's gradient. When applied to nonlinear ELD problems, the GWO algorithm concept seems to be a strong and dependable optimization approach. 13 unit test system with 50 and 100 iterations are used to implement and evaluate the suggested algorithm. The results compare with Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) for validation of results, its potential and efficacy. The result is highly promising and demonstrates that the GWO is a highly successful optimization method for resolving a variety of ELD challenges.

Institutions

Publication Details

Published
2025-05-15
DOI
https://doi.org/10.1109/ic2e365635.2025.11167641
Primary Topic
Agricultural Economics and Policy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Performance Assessment of Grey Wolf Optimizer for Economic and Emission Load Dispatch

Agricultural Economics and Policy
article

Performance Assessment of Grey Wolf Optimizer for Economic and Emission Load Dispatch

article en

Abstract

This article proposes grey wolf optimization (GWO), a novel evolutionary optimization technique for the best operating strategy of economic load dispatch (ELD) that is based on the behavior of grey wolves. The problem takes into account the nonlinear features of generators, such as forbidden operating zones, valve point discontinuities, and ramp rate restrictions. When looking for an optimal solution, the Gray Wolf Optimization (GWO) approach doesn't require a comprehension of the objective function's gradient. When applied to nonlinear ELD problems, the GWO algorithm concept seems to be a strong and dependable optimization approach. 13 unit test system with 50 and 100 iterations are used to implement and evaluate the suggested algorithm. The results compare with Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) for validation of results, its potential and efficacy. The result is highly promising and demonstrates that the GWO is a highly successful optimization method for resolving a variety of ELD challenges.

Sri Sai University (IN), Punjab Technical University (IN)
Openalex Percentile: Top 34%
Agricultural Economics and Policy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.