Rasool M. Imran^1,2,*, Mohammed R. Saeed¹, Mohammed Amer Mohammed³, Osama A. Suhry³, Ihsan H. Abdulqadder⁴, Hasan Wahhab Salih⁵, Mohammed R. Almallah⁶, Firas M. F. Flaih³

Energy Engineering, Vol.119, No.6, pp. 2447-2467, 2022, DOI:10.32604/ee.2022.021871

Abstract

Usually, rural areas can be electrified via three-phase distribution transformers with relatively large capacities. In such areas, low voltage lines are used for long distances, which cause power losses and voltage drop for different types of consumers. Reducing losses and improving voltage profiles in rural distribution networks are significant challenges for electricity distribution companies. However different solutions were proposed in the literature to overcome these challenges, most of them face difficulties when applied in the conventional distribution network. To address the above issues, an applicable solution is proposed in this paper by installing a number of small-capacity distribution transformers instead… More >

K. Dharani Sree^*, P. Karpagavalli

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1181-1195, 2023, DOI:10.32604/iasc.2023.025303

Abstract The distributed generators in the radial distribution network are to improve the Grid performance and its efficiency. These Distributed Generators control the PV bus; it is converted as a remote controlled PVQ bus. This PVQ bus reduces the power loss and reactive power. Initially, the distributed generators were placed in the system using mathematical modelling or the optimization. This approach improves the efficiency but it has no effect in loss minimization. To minimize the loss the reconfigured network with Genetic algorithm based Distributed generator placement proposed as existing work. This approach minimizes the loss effectively; but the genetic algorithm takes… More >

S. Arun Kumar^*, S. Padma, S. Madhubalan

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 777-789, 2022, DOI:10.32604/iasc.2022.023702

Abstract Energy management carried in a power system by configuration process is a difficult activity. So, reconfiguration has been introduced to solve this problem. Numerous optimization topologies have been utilized to solve this problem so far. However, they exhibit some drawbacks such as convergence, etc. Hence to overcome this issue, this work formulated a new hybrid optimization topology Genetic Algorithm Enabled Particle Swarm Optimization (PSOGA) to solve the energy configuration problem with low power loss in the Distribution System (DS). The proposed topology’s effectiveness was evaluated on the IEEE 33 bus Distribution System, and the results were compared to methods reported… More >