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

Saurav Raj, Sheila Mahapatra, Chandan Kumar Shiva and Biplab Bhattacharyya
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Saurav Raj: Institute of Chemical Technology, Mumbai, India
Sheila Mahapatra: Alliance University, India
Chandan Kumar Shiva: S R Engineering College, Warangal, India
Biplab Bhattacharyya: Indian Institute of Technology, Dhanbad, India

International Journal of Energy Optimization and Engineering (IJEOE), 2021, vol. 10, issue 2, 74-103

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.

Date: 2021
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