Nisa Nacar Çıkan^*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3279-3327, 2025, DOI:10.32604/cmes.2025.065442 - 30 June 2025

Abstract This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks (UPDNs), focusing on the complex 123-Bus test system. Three scenarios are investigated: (1) simultaneous power loss reduction and voltage profile improvement, (2) minimization of voltage and current unbalance indices under various operational cases, and (3) multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index, active power loss, and current unbalance index. Unlike previous research that oftensimplified system components, this work maintains all equipment, including capacitor banks, transformers, and voltage regulators, to ensure realistic results. The study evaluates twelve metaheuristic More >

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 >

Shuang Li¹, Suoying He², Shen Cheng^1,*, Jiarui Wu¹, Ruiting Meng¹

Energy Engineering, Vol.122, No.6, pp. 2309-2335, 2025, DOI:10.32604/ee.2025.062216 - 29 May 2025

Abstract In view of the situation of multi-temperature, multi-medium and multi-discharge equipment on the integrated exhaust end platform of a natural gas distributed energy station, which is compact in layout, mutual influence, complex aerodynamic field and complex heat and mass transfer field, the temperature field and aerodynamic field of the platform were comprehensively studied through field experiments and numerical simulation. The research results show that the high temperature flue gas discharged from the chimney is hindered by the chimney cap and returns downward. The noise reduction walls around the chimney make the top of the platform… More >

Murat Cikan^*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 673-721, 2025, DOI:10.32604/cmes.2025.061699 - 11 April 2025

Abstract This study examines various issues arising in three-phase unbalanced power distribution networks (PDNs) using a comprehensive optimization approach. With the integration of renewable energy sources, increasing energy demands, and the adoption of smart grid technologies, power systems are undergoing a rapid transformation, making the need for efficient, reliable, and sustainable distribution networks increasingly critical. In this paper, the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms. Among these advanced search algorithms, the Bonobo Optimizer (BO) has demonstrated superior performance in handling the complexities of unbalanced power… 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 >

Gang Lei^1,*, Chunxiang Xu²

Energy Engineering, Vol.119, No.5, pp. 2005-2029, 2022, DOI:10.32604/ee.2022.021154 - 21 July 2022

Abstract In the present paper, the distribution feeder reconfiguration in the presence of distributed generation resources (DGR) and energy storage systems (ESS) is solved in the dynamic form. Since studies on the reconfiguration problem have ignored the grid security and reliability, the non-distributed energy index along with the energy loss and voltage stability indices has been assumed as the objective functions of the given problem. To achieve the mentioned benefits, there are several practical plans in the distribution network. One of these applications is the network rearrangement plan, which is the simplest and least expensive way… More >

Dong An¹, Junqing Jia¹, Wenchao Cai¹, Deyu Yang¹, Chao Lv¹, Jiawei Zhu², Yingying Jiao^3,*

Energy Engineering, Vol.119, No.4, pp. 1531-1545, 2022, DOI:10.32604/ee.2022.019284 - 23 May 2022

Abstract This paper develops a real-time PV arrays maximum power harvesting scheme under partial shading condition (PSC) by reconfiguring PV arrays using Aquila optimizer (AO). AO is based on the natural behaviors of Aquila in capturing prey, which can choose the best hunting mechanism ingeniously and quickly by balancing the local exploitation and global exploration via four hunting methods of Aquila: choosing the searching area through high soar with the vertical stoop, exploring in different searching spaces through contour flight with quick glide attack, exploiting in convergence searching space through low flight with slow attack, and More > Graphic Abstract