JOURNAL ARTICLE

Comparison Study On Economic Load Dispatch Using Metaheuristic Algorithm

Widi Aribowo

Year: 2021 Journal:   GAZI UNIVERSITY JOURNAL OF SCIENCE Vol: 35 (1)Pages: 26-40

Abstract

This paper presents an approach to overcome economic load dispatch (ELD) using a metaheuristic algorithm. Economic load dispatch (ELD) is one of the most important problems in a power system, and solving it quickly is extremely important. The main problem that will be addressed in this paper is how to optimize the economy of the power grid with various operational limitations, the loss in transmission line power, and consider minimizing the fuel costs produced. In this study, some of the newest metaheuristics inspired by nature will be explored, namely Seagull Optimization Algorithm (SOA), Marine Predator Algorithm (MPA), Sine Tree-Seed Algorithm (STSA), Chimp Optimization Algorithm (ChOA), Equilibrium Optimizer (EO), and Giza Pyramids Construction (GPC). The performance appraisal of the method applied in this study was tested using 2 case studies, namely a system with 3 and 6 power system units. The results are presented by comparing between metaheuristic and mathematical methods. The experimental results is showed that the Sine Tree-Seed Algorithm (STSA) is presented the best performance with various case studies with constraints.

Keywords:
Metaheuristic Economic dispatch Computer science Electric power system Mathematical optimization Algorithm Parallel metaheuristic Heuristic Ant colony optimization algorithms Tabu search Optimization algorithm Tree (set theory) Power (physics) Mathematics Meta-optimization

Metrics

12
Cited By
0.83
FWCI (Field Weighted Citation Impact)
23
Refs
0.73
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Electric Power System Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Energy Load and Power Forecasting
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Islanding Detection in Power Systems
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
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