Rescheduling based congestion management using particle swarm optimization strategy

P. Nisha, A. Gayathri, G. Sudhagar, T. Jarin
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Abstract

In the deregulated environment, the transmission grids are used optimally. This utilization of the transmission system makes some lines congested due to the capacity constraints of the line. Congestion becomes a barrier of power trading and it affects the security of the power system. Congestion Management (CM) acts as a major issue that threatens the system security and it is a most difficult task for the system operators. This paper tries to introduce a novel optimization based CM model with advanced soft computing technique. An algorithm is introduced in this paper to deal with CM, which obviously optimize the generating power of added generators with the bus system. This manages the congestion with minimum rescheduling cost. The proposed optimization algorithm termed as Whale Optimization algorithm (WOA) involves in the management of congestion optimally. Subsequently, the experimentation is performed in the test bus system of 118 bus systems. The effectiveness of proposed model is compared with the conventional methods, with respect to cost and convergence.
基于粒子群优化策略的重调度拥塞管理
在放松管制的环境下,输电网得到了最佳利用。传输系统的这种利用使得一些线路由于容量的限制而出现拥塞。拥塞成为电力交易的障碍,影响着电力系统的安全运行。拥塞管理是威胁系统安全的主要问题之一,也是困扰系统运营者的一大难题。本文尝试采用先进的软计算技术,提出一种新的基于优化的CM模型。本文介绍了一种处理同步调度的算法,该算法能明显地优化母线系统中附加发电机的发电功率。这以最小的重新调度成本来管理拥塞。所提出的优化算法被称为鲸鱼优化算法(WOA),涉及到对拥塞的最优管理。随后,在118个母线系统的测试母线系统中进行了实验。从成本和收敛性两方面比较了该模型与传统方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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