کنفرانس بین المللی ماشین و محرکه های الکتریکی

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صفحه اصلی / icemd2023

Investigation study of Injecting Numerous DGs in IEEE 69 – bus Radial Networks Using Enhanced PSO and Ant Lion Optimization Algorithms

نویسندگان :

Ali Altahir¹ Ahmed Rahim Ali² Shamam Alwash³ Murtadha Al-Kaabi⁴

1- University of Kerbala 2- University of Kerbala 3- University of Babylon 4- School building department, Rusafa

کلمات کلیدی :

Ant Lion Optimization،distributed generations،best location and sizing،enhanced Particle Swarm Optimization،IEEE 69-bus،loss sensitivity،losses minimization.

چکیده :

Electric utilities are paying a lot of attention right now to the allocation of distributed generations (DGs) in radial networks for solving real loss, voltage profile and stability index. Active power loss reduction has several built-in advantages, such as feeder power flow being reduced, relieving tension on the feeder to extend its lifetime, increasing the possibility of the current ability to meet any increase in load request, avoiding the need to buy power from the grid and saving money on loss compensating equipment, and reducing customer bills. The proposed scenarios are used for selecting the best sizing and location of numerous DGs based on enhanced Particle Swarm Optimization (EPSO) and Ant Lion Optimization (ALO) that are tested for two different case studies. The main purpose of this study is to reduce the real losses on the radial network by injecting numerous DGs. This results in a large reduction with favorable voltage profiles and an issue in increasing loads on radial networks (RN). The convergence speed of the proposed EPSO is fast and has less iteration to reach the best solutions compared to the other optimization techniques reported in the related works. It is observed that the minimum VSI is from 0.6852 (Bus 65) in the initial case to 0.964 (Bus 27) in the best case using the EPSO algorithm and 0.9588 (Bus 27) using ALO. The numerical simulation results show that the results extracted by EPSO are more accurate than the corresponding obtained results by ALO from viewpoints of real loss reduction and allocation of DGs.