Probabilistic Reactive Power Flow Optimization of Distribution System in Presence of Distributed Units Uncertainty Using Combination of Improved Taguchi Method and Dandelion Algorithm

Document Type : Original Article

Authors

Electrical Engineering Department, Faculty of Electrical and Computer Engineering, Urmia University, Urmia, Iran

Abstract

Nowadays, due to the growing population, rising global warming, environmental pollution, and the reduction of fuel sources, the use of Distributed Generation Sources (DGs) has grown, and because of their random nature, the conventional performance of power systems is being changed. Reactive power has a considerable role in power systems management and control indexes such as loss, stability, reliability, and security, among which the loss index usually can be easily minimized and controlled. Thus the modeling and optimizing of reactive power must be done accurately and correctly. This paper uses a novel metaheuristic algorithm which is called Dandelion, to solve the constrained non-linear optimal reactive power dispatch problem, and the Improved Taguchi method based on orthogonal arrays has been applied in order to the uncertainty of DG units modeling. The applied optimal reactive power dispatch algorithm is tested and validated using standard IEEE 30-bus test power systems. These results show that the Computational time of the applied algorithm in comparison with other used algorithms is the least value and reduces the reactive power from 22.244 to 2.366 Mvar; also, the losses of the power system significantly will be decreased with the tested and introduced algorithm. Genetic Algorithm(GA), Particle swarm optimization algorithm (PSO), and Prairie dog optimization algorithm (PDO) have been utilized to solve the problem.

Graphical Abstract

Probabilistic Reactive Power Flow Optimization of Distribution System in Presence of Distributed Units Uncertainty Using Combination of Improved Taguchi Method and Dandelion Algorithm

Keywords

Main Subjects

References

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International Journal of Engineering
Volume 37, Issue 1
TRANSACTIONS A: Basics
January 2024
Pages 37-47

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