Grasshopper Optimization-based Optimal Sizing of DG/DSTATCOM in Distribution Networks

Document Type : Research Studies

Authors

1 Assistant Lecture, Electrical Engineering Department, Faculty of Engineering, Mansoura University, Egypt

2 Associated Professor in Electrical Engineering Dept., Faculty of Engineering, Mansoura Univ., Egypt.

3 Prof. in Electrical Engineering Department, Faculty of Engineering Mansoura University, Egypt

Abstract

This paper adopts the application of the new optimization technique to attain the optimal size and location of the distributed static synchronous compensators (DSTATCOMs) and distributed generators (DGs) in the electrical distribution network. The optimization technique is based on simulating the behavior of the Grasshopper insects and is called grasshopper optimizer algorithm (GOA). The proposed objective function that is used to obtain the size and locations of the DSTATCOMs and DGs is devised for reducing the losses in the active power and improving the voltage stability index, which is employed to detect the weak busses in the distribution network (DN). First, the optimal locations of the DGs and the DSTATCOMs are identified by using the loss sensitivity factor (LSF). Then, the proposed Multi-objective GOA is implemented to obtain the optimal penetration of the DGs and DSTATCOMs in the DNs. This methodology is tested on a radial distribution system (IEEE 33-bus) for different scenarios to inspect its effectiveness. The results proved that the reduction in the total power losses (TPLs) and the improvement in the voltage stability index (VSI) were 81.5% and 30.7%, respectively at cases which combined multi DGs and DSTATCOMs for the modified IEEE 33-bus test system. Also, the proposed method is compared with several existing algorithms; Particle Swarm Optimization technique, Backtracking Search, Immune Algorithm, Sine Cosine Algorithm, lightning Search Algorithm, and Bacterial Foraging Optimization Algorithm. The results confirm that the GOA method has better performance

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MEJ- Mansoura Engineering Journal
Volume 47, Issue 2
With Cover
March and April 2022
Pages 6-16

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