Enhancing Power System Performance via TCSC Technology Allocation With Enhanced Gradient-Based Optimization Algorithm

Abstract

This paper addresses the critical challenge of optimal allocation of Thyristor-Controlled Series Compensator (TCSC) devices in transmission power systems through an innovative optimization framework. Leveraging an Enhanced Gradient-Based Algorithm (EGBA) augmented with a crossover operator, the proposed methodology seeks to promote diversity in the solutions generated in each iteration, aiming to maximize the efficiency of power transmission networks. The algorithm incorporates key components such as the Gradient Search Process (GSP) and Local Escaping Process (LEP) to guide the exploration process and prevent premature convergence to suboptimal solutions. Additionally, the crossover operator, a novel addition in the EGBA, facilitates the exchange of TCSC configurations between solutions, contributing to solution diversity and potentially revealing novel optimal allocations. Initially, the EGBA and GBA performances are estimated using the CEC 2017 benchmarks. Moreover, to assess the practical applicability of the suggested EGBA, it is specifically tailored and implemented to enhance the operation of transmission power systems. The primary objective is to minimize technical power losses, considering varying numbers of TCSC devices with experimentation on two distinct IEEE power systems, one with 30 buses and another with 57 buses. The results are analyzed to validate the ability of the EGBA method in optimizing power systems and addressing technical losses. The novel proposed EGBA method significantly reduces power losses compared to the original GBA method in both tested power systems. In the first system, the EGBA achieved 0.85%, 2.99%, and 1.32% lower losses than the GBA when optimizing for one, two, and three TCSC devices, respectively. In addition, the objective of enhancing the security margin of the transmission lines is involved to optimize the power flow besides the minimization function of power losses. Similarly, in the second system, the EGBA outperformed the original GBA by 5.19%, 6.32%, and 5.12% for the same TCSC configurations. The simulation results demonstrate that the proposed EGBA is not only more effective but also more efficient than the original GBA and other recent approaches.

Keywords

• TCSC technology
• TCSC allocation optimization
• gradient-based algorithm
• CEC 2017 benchmarks
• transmission systems