Reliability enhancement and power loss reduction in medium voltage distribution feeders using modified jellyfish optimization

Abstract

The reliability of electrical systems is a critical operational characteristic for distribution companies. On the other hand, they pay great attention on reducing losses in primary and secondary distribution lines. In this article, a modified Jellyfish Search (MJFS) algorithm is presented for handling Optimal Network reconfiguration (ONR) in Medium Voltage Distribution Feeders (MVDFs). An ONR formulation is proposed for reliability enhancement and power loss reduction in a multi-objective model where three reliability measures are incorporated which are total energy not supplied (TENS), system average interruption unavailability index (SAIUI) and system average interruption frequency index (SAIFI). The proposed MJFS expands on the JFS searching benefits by introducing a quasi-oppositional-based learning and social neighborhood strategies. Also, a proposed bus-line feeding matrix (BLFM) is incorporated to develop the MJFS. Through the BLFM, each distribution line is simulated as an outage and the regarding distribution nodes which are not supplied is estimated. The simulation results are performed on a large-scale IEEE MVFD of 137-bus which derive significant improvements of the proposed MJFS over the standard JFS algorithm. Considering the proposed multi-objective model, the proposed MJFS achieves great reduction in power losses, TENS, SAIUI and SAIFI with 44.42, 30.57, 30.78 and 23.92 %, respectively compared to the initial case. Also, versus the standard JFS, grey wolf optimizer, tuna swarm optimization, equilibrium optimizer and tunicate swarm optimization, the proposed MJFS acquires great reduction in the standard deviation with improvement of 2.5, 92.51, 10.67, 91.53 and 96.51%, respectively.

Keywords

• Reliability enhancement
• Total energy not supplied
• Jellyfish search optimization
• Power losses
• Reconfiguration