A New Optimization Algorithm Integrated With Power Flow Analysis for Efficient Shunt Capacitor Bank Allocation in Radial Distribution Networks
Abstract
The main objective of this paper is to enhance the performance of radial distribution networks (RDNs) by developing a new optimization technique integrated with an efficient load flow analysis for the optimal placement and sizing of shunt capacitor banks (SCBs). The key feature of the proposed method lies in the development of an innovative branch-bus incidence matrix (C-Matrix), which enables fast and accurate load flow computation with reduced computational complexity, combined with a mathematical programming-based optimization approach. The enhancement is achieved through power losses reduction, minimization of the annual energy losses cost, network voltage profile improvement, and enhancement of the power factor at the slack bus bar. The proposed technique has been implemented on IEEE 33-bus and IEEE 69-bus RDNs. The results demonstrate that the proposed approach consistently outperforms existing techniques while maintaining high effectiveness. The proposed method achieves a reduction in apparent power losses of 34.61% with annual savings of 11,816 USD and approximate unity power factor (0.9971 lag) at the slack bus bar for the IEEE 33-bus system, while for the IEEE 69-bus system, it achieves a loss reduction of 35.25% with annual savings of 12,857 USD at operating power factor of 0.9917 lag. In addition, a sensitivity analysis under ±20% load variation is conducted to evaluate the robustness of the proposed method. and reliability assessment of IEEE 33-bus RDN is presented which demonstrate by calculation of reliability indices, that RDN is more reliable.
Fields of Study & Subjects
Optimal Power Flow Distribution
Electric Power System Optimization
Power Systems Fault Detection
Publication details
- Journal / source
- IEEE Access
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Volume
- 14
- Pages
- 93484–93497
- Publication date
- 1 January 2026
- Language
- EN