Wenlu Ji^*, Teng Tu, Nan Ma

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

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 as a tri-level defender-attacker-defender (DAD)… More >

Caixia Tao, Shize Yang^*, Taiguo Li

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

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 the simulated annealing algorithm to… More >

Gang Lei^1,*, Chunxiang Xu²

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

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 to add equipment to the… 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 >

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

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 swooping through walk and grabbing… More > Graphic Abstract

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 >