FACTS devices allocation for congestion management considering voltage stability by means of MOPSO
FACTS devices allocation for congestion management considering voltage stability by means of MOPSO
复制标题
通过 MOPSO 考虑电压稳定性的 FACTS 设备分配用于拥塞管理
DOI：
10.1109/td-asia.2009.5357015
复制
发表时间：
2009
期刊：
影响因子：
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通讯作者：
Y. Sasaki
中科院分区：
文献类型：
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作者：
R. S. Wibowo;N. Yorino;M. Eghbal;Y. Zoka;Y. Sasaki
本文提出了一种通过优化分配FACTS设备来解决拥塞管理问题的方法。该问题通过利用优化方法来解决，该方法在满足电压稳定性指标的同时优化发电和安装成本。本文的主要贡献是提供帕累托最优解，描述拥塞期间和拥塞消除后的先前目标。此外，该方法能够对缓解拥塞的最佳位置进行排序，描述解决方案的可行性，并在提高电压稳定性方面展示更好的解决方案。因此，对于决策者来说，确定从中受益的设备的位置和尺寸是很有价值的。由于问题的复杂性，采用多目标粒子群优化（MOPSO）作为主子问题来优化设备分配；采用顺序二次规划（SQP）求解运行子问题，采用崩溃点法计算意外事故时的负荷裕度。该技术的有效性在改进的 IEEE 14 总线系统中得到了证明。
This paper proposes a method for solving congestion management problem by optimally allocating FACTS devices. The problem is approached by utilizing optimization method which optimizes generation and installation costs while satisfying voltage stability index. The main contribution of this paper is to provide pareto optimal solutions which describe previous objectives during congestion and after congestion removed. Moreover, the method is able to rank optimal location in relieving congestion, to describe feasibility of solutions and to show better solution in improving voltage stability. Therefore, it is valuable for decision maker in determining locations and sizes of devices which gaining the benefit. Due to the complexity of the problem, Multi Objective Particle Swarm Optimization (MOPSO) is utilized to optimize devices allocation as master sub-problem; Sequential Quadratic Programming (SQP) is used to solve the operation sub-problem, and Point of Collapse method is applied to calculate load margin during contingency. The effectiveness of this technique is demonstrated in modified IEEE 14 bus system.
进化多目标优化算法在最优VAR扩展和ATC增强问题中的应用
DOI：
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发表时间：
2008
期刊：
影响因子：
--
作者：
T.Fukaya;T.Mizojiri;M.Kando;M. Eghbal
通讯作者：
M. Eghbal