Implementation and Optimal Sizing of TCSC for the Solution of Reactive Power Planning Problem Using Quasi-Oppositional Salp Swarm Algorithm

Abstract

In this article, innovative algorithms named as salp swarm algorithm (SSA) and hybrid quasi-oppositional SSA (QOSSA) techniques have been proposed for finding the optimal coordination for the solution of reactive power planning (RPP). Quasi-oppositional based learning is a promising technique for improving convergence and is implemented with SSA as a new hybrid method for RPP. The proposed techniques are successfully implemented on standard test systems for deprecation of real power losses and overall cost of operation along with retention of bus voltages under acceptable limits. Optimal planning has been achieved by minimizing reactive power generation and transformer tap settings with optimal placement and sizing of TCSC. Identification of weakest branch in the power network is done for optimal TCSC placement and is tendered through line stability index method. Optimal TCSC placement renders a reduction in transmission loss by 8.56% using SSA and 8.82% by QOSSA in IEEE 14 bus system and 7.57% using SSA and 9.64% by QOSSA in IEEE 57 bus system with respect to base condition.

Optimizing transmission line parameter estimation with hybrid evolutionary techniques

“…The algorithm aims to iteratively enhance the solution by adjusting the positions of the salps based on rules inspired by the biological behaviour of salps. SSA has been successfully applied to solve various optimization problems [50,51], and its performance has been evaluated in different scenarios. Similar to PSO, SSA is employed in optimization tasks where finding the optimal solution is the primary objective.…”

Enhancement of available transfer capability usingTCSCwith hybridized model: Combining lion and moth flame algorithms

“…In 2021, Raj et al 32 have introduced SSA and QOSSA to find the optimal harmonization for RPP. The suggested solutions have been effectively done for reducing losses and total operating costs while maintaining safe bus voltages.…”

A Solution of RPM for Active and Reactive Loading Compensation

“…Several transition states may arise as a result of this under various loading situations. As a result, the goal of multiload level RPM is to maintain a profile of low operating costs and low transmission loss while avoiding bus voltage violations (Ahmed et al, 2021;Burle and Chintapalli, 2021;Raj et al, 2021). In this paper, load ability is expressed as a single-valued scalar parameter whose value is changed from zero to maximum.…”