分布式发电、电容器组和D-STATCOM在配电系统中的优化配置

IF 1.5 Q3 ENGINEERING, MULTIDISCIPLINARY
S. Salkuti
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引用次数: 0

摘要

本文演示了配电网中分布式发电(DG)、并联电容器组(CB)和基于配电FACTS的D-STATCOM的同时优化分配问题,以提高整个系统的性能。这里,考虑了两个目标,总功率损耗最小化和总电压稳定指数(VSI)最大化。通常,功率损耗最小化是主要目标,并且VSI被考虑用于提高电压稳定性。VSI必须为正才能获得稳定的操作,并且VSI值越高表示RDS的稳定性越好。这些目标是在与功率平衡、DG、CB、D-STATCOM功率、总线电压和VSI相关的约束条件下解决的。这里,单目标问题使用粒子群优化(PSO)求解,多目标问题使用多目标PSO(MO-PSO)求解。为了解决这个问题,考虑了标准的33总线RDS。结果表明,所提出的优化方案改善了RDS的电压分布和整体VSI,并将系统功率损耗降至最低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Allocation of Distributed Generation, Capacitor Banks and D-STATCOM in Distribution Systems
This paper demonstrates the problem of simultaneous optimal allocation of distributed generations (DGs), shunt capacitor banks (CBs), and distribution FACTSs based D-STATCOMs in distribution network for the improvement of the entire system performance. Here, two objectives, total power loss minimization, and overall voltage stability index (VSI) maximization are considered. In general, minimization of power loss is the primary objective, and VSI is considered for improved voltage stability. VSI must be positive to obtain a stable operation and a higher VSI value represents better stability of the RDS. These objectives are solved subject to constraints related to power balance, DGs, CBs, D-STATCOM powers, bus voltages, and VSI. Here, single objective problem is solved using Particle swarm optimization (PSO), and the multi-objective problem is solved using multi-objective PSO (MO-PSO). Standard 33 bus RDS is considered for solving this problem. The results obtained show that proposed optimization has improved the voltage profile and overall VSI of the RDS and minimized the system power losses.
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来源期刊
CiteScore
3.80
自引率
6.20%
发文量
57
审稿时长
20 weeks
期刊介绍: IJMEMS is a peer reviewed international journal aiming on both the theoretical and practical aspects of mathematical, engineering and management sciences. The original, not-previously published, research manuscripts on topics such as the following (but not limited to) will be considered for publication: *Mathematical Sciences- applied mathematics and allied fields, operations research, mathematical statistics. *Engineering Sciences- computer science engineering, mechanical engineering, information technology engineering, civil engineering, aeronautical engineering, industrial engineering, systems engineering, reliability engineering, production engineering. *Management Sciences- engineering management, risk management, business models, supply chain management.
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