Tareq Hamadneh¹, Belal Batiha², Frank Werner^3,*, Mehrdad Ahmadi Kamarposhti^4,*, Ilhami Colak⁵, El Manaa Barhoumi⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1519-1548, 2025, DOI:10.32604/cmes.2025.063571 - 30 May 2025

Abstract Reconfiguration, as well as optimal utilization of distributed generation sources and capacitor banks, are highly effective methods for reducing losses and improving the voltage profile, or in other words, the power quality in the power distribution system. Researchers have considered the use of distributed generation resources in recent years. There are numerous advantages to utilizing these resources, the most significant of which are the reduction of network losses and enhancement of voltage stability. Non-dominated Sorting Genetic Algorithm II (NSGA-II), Multi-Objective Particle Swarm Optimization (MOPSO), and Intersect Mutation Differential Evolution (IMDE) algorithms are used in this… More >

Bo Yang¹, Rui Zhang¹, Jie Zhang², Xianlong Cheng², Jiale Li³, Yimin Zhou¹, Yuanweiji Hu¹, Bin He¹, Gongshuai Zhang⁴, Xiuping Du⁴, Si Ji⁵, Yiyan Sang⁶, Zhengxun Guo^7,8,*

Energy Engineering, Vol.121, No.12, pp. 3487-3547, 2024, DOI:10.32604/ee.2024.054662 - 22 November 2024

Abstract In recent years, the large-scale grid connection of various distributed power sources has made the planning and operation of distribution grids increasingly complex. Consequently, a large number of active distribution network reconfiguration techniques have emerged to reduce system losses, improve system safety, and enhance power quality via switching switches to change the system topology while ensuring the radial structure of the network. While scholars have previously reviewed these methods, they all have obvious shortcomings, such as a lack of systematic integration of methods, vague classification, lack of constructive suggestions for future study, etc. Therefore, this… More >

Wenlu Ji^*, Teng Tu, Nan Ma

Energy Engineering, Vol.121, No.5, pp. 1223-1243, 2024, DOI:10.32604/ee.2024.046112 - 30 April 2024

Abstract To improve the resilience of a distribution system against extreme weather, a fuel-based distributed generator (DG) allocation model is proposed in this study. In this model, the DGs are placed at the planning stage. When an extreme event occurs, the controllable generators form temporary microgrids (MGs) to restore the load maximally. Simultaneously, a demand response program (DRP) mitigates the imbalance between the power supply and demand during extreme events. To cope with the fault uncertainty, a robust optimization (RO) method is applied to reduce the long-term investment and short-term operation costs. The optimization is formulated More >

Caixia Tao, Shize Yang^*, Taiguo Li

Energy Engineering, Vol.121, No.1, pp. 187-201, 2024, DOI:10.32604/ee.2023.042421 - 27 December 2023

Abstract With the current integration of distributed energy resources into the grid, the structure of distribution networks is becoming more complex. This complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent algorithms. Consequently, traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local optima. To tackle this issue, a more advanced particle swarm optimization algorithm is proposed. To address the varying emphases at different stages of the optimization process, a dynamic strategy is implemented to regulate the social and self-learning factors. The Metropolis criterion is introduced into… More >

K. Dharani Sree^*, P. Karpagavalli

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1181-1195, 2023, DOI:10.32604/iasc.2023.025303 - 06 June 2022

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;… 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 - 08 February 2022

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 More >