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一种基于有功功率损耗灵敏度指标和改进蚁狮优化算法的综合方法用于配电网中分布式电源的布置

An integrated approach using active power loss sensitivity index and modified ant lion optimization algorithm for DG placement in radial power distribution network.

作者信息

Rajakumar P, Balasubramaniam P M, Aldulaimi Mohammed Hasan, M Arunkumar, Ramesh S, Alam Mohammad Mukhtar, Al-Mdallal Qasem M

机构信息

Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu, India.

Department of Electronics and Communication Engineering, Hindusthan Institute of Technology, Coimbatore, Tamil Nadu, India.

出版信息

Sci Rep. 2025 Mar 26;15(1):10481. doi: 10.1038/s41598-025-87774-2.

Abstract

Power losses and voltage deviations in distribution power networks (DPNs) are high since they carry more power demand than transmission power networks. Also, voltage deviation beyond the allowable range causes voltage stability problems in the DPN. The power loss (PL) in the DPN should be kept at the minimum level for the economic operation of the electric grid. Integrating distributed generation (DG) in appropriate sites of the power networks can minimize the power losses and voltage drops. An integrated optimization approach is proposed in this paper, by combining an analytical and metaheuristic algorithm to optimize the placement and sizing of multiple DGs. The active power loss sensitivity (APLS) index is an analytical mathematical computation approach used to identify the optimal bus locations for DG placement. The modified ant lion optimization (MALO) algorithm is applied to optimize the ratings of the DG systems. The MALO algorithm is proposed by adopting the Lévy flights (LF) pattern in the random walk process (RWP). LF representation of RWPs enhances the exploration phase of the ALO algorithm and helps to obtain the near-optimal solution. The proposed integrated approach optimizes multiple units of photovoltaic (PV) and wind turbine (WT) units to minimize the multi-objective function, including AP loss and voltage deviation (VD) minimizations. The effectiveness of the proposed integrated approach is validated on the IEEE 69-bus, 85-bus, and 118-bus radial DPNs. Besides, the simulation study is extended for ant lion optimization (ALO), BAT, and artificial bee colony (ABC) algorithms-based techniques. The integrated approach has reduced the total AP loss of the IEEE 69-bus and 85-bus radial DPN from 225 kW to 70.51 kW and 316.12 kW to 162.80 kW, respectively, for the optimized three PV DG units allocation. Likewise, the total AP loss of the 118-bus radial DPN is cut down from 1296.3 kW to 432.3 kW after the optimized five PV DG units allocation. Meanwhile, the total AP LOSS of the 69-bus, 85-bus, and 118-bus radial DPNs is reduced to 4.78 kW, 53.87 kW, and 112.2 kW, respectively, after the optimized WT DG allocation. Additionally, the optimized inclusion of multiple DG units significantly minimized the VD of the DPNs. The minimum VD of the 69-bus, 85-bus, and 118-bus test systems is reduced from 0.0908 p.u., 0.1297 p.u., and 0.1312 p.u. to 0.0174 p.u., 0.0384 p.u., and 0.0201 p.u., respectively, for the multiple PV unit allocations. Similarly, the minimum VDs of the 69-bus, 85-bus, and 118-bus radial DPNs are minimized to 0.0048 p.u., 0.0190 p.u., and 0.0093 p.u., respectively, following the multiple WT DG unit allocations. The simulation findings of the APLS-MALO integrated approach are related to the various optimization techniques. The comparative study reveals that the proposed integrated approach gives a more effective and efficient solution than ALO, BAT, ABC, and other optimization techniques. Finally, the simulation findings of the APLS-MALO integrated technique are verified via the calculation of conventional statistical metrics and the conduction of a non-parametric Wilcoxon test.

摘要

配电网络(DPN)中的功率损耗和电压偏差较高,因为它们承载的电力需求比输电网络更多。此外,超出允许范围的电压偏差会导致DPN中的电压稳定性问题。为实现电网的经济运行,DPN中的功率损耗(PL)应保持在最低水平。在电网的适当位置集成分布式发电(DG)可以将功率损耗和电压降降至最低。本文提出了一种综合优化方法,通过结合解析算法和元启发式算法来优化多个DG的布局和容量。有功功率损耗灵敏度(APLS)指标是一种解析数学计算方法,用于确定DG布局的最佳母线位置。应用改进的蚁狮优化(MALO)算法来优化DG系统的额定值。MALO算法是通过在随机游走过程(RWP)中采用莱维飞行(LF)模式提出的。RWP的LF表示增强了ALO算法的探索阶段,并有助于获得近似最优解。所提出的综合方法优化了多个光伏(PV)和风力发电机组(WT),以最小化多目标函数,包括有功功率损耗和电压偏差(VD)的最小化。在IEEE 69节点、85节点和118节点辐射状DPN上验证了所提出综合方法的有效性。此外,对基于蚁狮优化(ALO)、蝙蝠算法(BAT)和人工蜂群(ABC)算法的技术进行了扩展仿真研究。对于优化后的三个PV DG单元分配,综合方法分别将IEEE 69节点和85节点辐射状DPN的总有功功率损耗从225kW降至70.51kW,从316.12kW降至162.80kW。同样,在优化后的五个PV DG单元分配后,118节点辐射状DPN的总有功功率损耗从1296.3kW降至432.3kW。同时,在优化后的WT DG分配后,69节点、85节点和118节点辐射状DPN的总有功功率损耗分别降至4.78kW、53.87kW和112.2kW。此外,优化包含多个DG单元显著降低了DPN的VD。对于多个PV单元分配,69节点、85节点和118节点测试系统的最小VD分别从0.0908标幺值、0.1297标幺值和0.1312标幺值降至0.0174标幺值、0.0384标幺值和0.0201标幺值。同样,在多个WT DG单元分配后,69节点、85节点和118节点辐射状DPN的最小VD分别降至最小0.0048标幺值、0.0190标幺值和0.0093标幺值。APLS - MALO综合方法的仿真结果与各种优化技术相关。对比研究表明,所提出的综合方法比ALO、BAT、ABC和其他优化技术提供了更有效和高效的解决方案。最后,通过计算传统统计指标和进行非参数威尔科克森检验,验证了APLS - MALO综合技术 的仿真结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ccd6/11947200/590e67edbf70/41598_2025_87774_Fig1_HTML.jpg

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