Secure and continuous power flow in the transmission line is one of the critical issues that must be rectified. In fact, rescheduling-based congestion management is considered to be one of the promising solutions for this aspect. Still, the model faces issues on the basis of rescheduling costs. More research works have been addressed so far to solve the problems of congestion management. Optimization algorithms also play a vital role in solving this problem. Under this scenario, this paper introduces a new rescheduling-based congestion management model that incorporates a new algorithm, refractor update-based ROA (RU-ROA) that optimizes the generating power of added generators with the bus system. The proposed RU-ROA algorithm is the hybridization of two algorithms, namely rider optimization algorithm (ROA) and water wave optimization (WWO), that aims to manage the congestion with the reduced cost of rescheduling. Further, the proposed model compares its performance over other conventional models like particle swarm optimization, FireFly, grey wolf optimization, traditional ROA and traditional WWO-based rescheduling strategy with respect to cost analysis and convergence analysis, and proves the efficiency of proposed work over others.

中文翻译：

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一种基于重新调度的电力系统拥塞管理方案的新型混合算法

输电线路中安全和持续的电力流动是必须纠正的关键问题之一。事实上，基于重新调度的拥塞管理被认为是这方面的有前途的解决方案之一。尽管如此，该模型仍面临重新安排成本的问题。到目前为止，已经有更多的研究工作来解决拥塞管理的问题。优化算法在解决这个问题中也起着至关重要的作用。在这种情况下，本文介绍了一种新的基于重新调度的拥塞管理模型，该模型采用了一种新算法，即基于折射器更新的 ROA (RU-ROA)，该算法通过总线系统优化增加的发电机的发电功率。提出的RU-ROA算法是两种算法的混合，即骑手优化算法（ROA）和水波优化（WWO），其目的是通过降低重新调度的成本来管理拥塞。此外，所提出的模型在成本分析和收敛分析方面将其性能与粒子群优化、FireFly、灰狼优化、传统 ROA 和传统的基于 WWO 的重新调度策略等其他传统模型进行了比较，并证明了所提出的工作效率高于其他模型.