Hybrid GWO-PSO based optimal placement and sizing of multiple PV-DG units for power loss reduction and voltage profile improvement

Assen Beshr Alyu; Ayodeji Olalekan Salau; Baseem Khan; Joy Nnenna Eneh

doi:10.1038/s41598-023-34057-3

Hybrid GWO-PSO based optimal placement and sizing of multiple PV-DG units for power loss reduction and voltage profile improvement

Sci Rep. 2023 Apr 27;13(1):6903. doi: 10.1038/s41598-023-34057-3.

Authors

Assen Beshr Alyu¹, Ayodeji Olalekan Salau^{2

3}, Baseem Khan⁴, Joy Nnenna Eneh⁵

Affiliations

¹ School of Electrical and Computer Engineering, Dilla University, Dilla, Ethiopia.
² Department of Electrical/Electronics and Computer Engineering, Afe Babalola University, Ado-Ekiti, Nigeria. ayodejisalau98@gmail.com.
³ Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India. ayodejisalau98@gmail.com.
⁴ Department of Electrical and Computer Engineering, Hawassa University, Hawassa, Ethiopia.
⁵ Department of Electronic Engineering, University of Nigeria, Nsukka, Nigeria.

Abstract

Distributed generation (DG) is integrated in a passive distribution system to reduce power loss, improve voltage profile, and increase power output. To reap the most benefits of the distribution system, the best location and appropriate DG size must be determined. This paper presents a hybrid Grey wolf Optimizer (GWO) and Particle swarm optimization (PSO) approach for determining the best placement and DG size while considering a multi-objective function that includes active and reactive power loss minimization as well as voltage profile enhancement. Dilla distribution system was used as a case study and the weighted technique was used to convert to a single objective function while taking into account multiple constraints such as bus voltage limit, DG output limit, and branch current limit. DG penetration is limited to up 60% of the total active load on the feeder and a forward-backward sweep load flow algorithm was used to generate the load flow solutions. The findings of the study show that combining three PV-DGs (Case 3) is the best way to improve voltage profile and minimize losses. In addition, the proposed hybrid GWO-PSO algorithm performed better compared to the other four algorithms (Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), Particle swarm optimization (PSO), and sine cosine algorithm (SCA)) in terms of achieving the best multi-objective function (MOF) outcome.