JOURNAL ARTICLE

Evolutionary algorithm solution for economic dispatch problems

Balasim Mohammed Hussein

Year: 2022 Journal:   International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering Vol: 12 (3)Pages: 2963-2963   Publisher: Institute of Advanced Engineering and Science (IAES)

Abstract

<span>A modified firefly algorithm (FA) was presented in this paper for finding a solution to the economic dispatch (ED) problem. ED is considered a difficult topic in the field of power systems due to the complexity of calculating the optimal generation schedule that will satisfy the demand for electric power at the lowest fuel costs while satisfying all the other constraints. Furthermore, the ED problems are associated with objective functions that have both quality and inequality constraints; these include the practical operation constraints of the generators (such as the forbidden working areas, nonlinear limits, and generation limits) that makes the calculation of the global optimal solutions of ED a difficult task. The proposed approach in this study was evaluated in the IEEE 30-Bus test-bed; the evaluation showed that the proposed FA-based approach performed optimally in comparison with the performance of the other existing optimizers, such as the traditional FA and particle swarm optimization. The results show the high performance of the modified firefly algorithm compared to the other methods.</span>

Keywords:
Firefly algorithm Particle swarm optimization Economic dispatch Schedule Computer science Mathematical optimization Electric power system Task (project management) Span (engineering) Power (physics) Algorithm Mathematics Engineering

Metrics

6
Cited By
0.65
FWCI (Field Weighted Citation Impact)
20
Refs
0.63
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
Metaheuristic Optimization Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence

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