Allocation of optimal distributed generation using GA for minimum system losses in radial distribution networks

Abstract

The distributed generation (DG) is one of the viable options for mitigation of problems of load growth, overloading of lines, quality of supply and reliability in tern extending equipment maintenance intervals and to reduce line losses. However, the line loss reduction is the obvious parameter easily expressible in terms of system parameters. Therefore, this paper aims to minimize active power loss by placing DG strategically in a radial distribution system. The problem is formulated as an optimization problem and solution is obtained using genetic algorithm (GA). The strategic locations are decided on the basis of loss sensitivity to active power injection at various nodes. This approach helps in reducing the computational efforts of selecting appropriate location(s). The performance of the method is tested on 33-bus test system and comparison of the results with a reported method reveals that the proposed method yields superior results. In addition, long term economic benefit of optimal DG placement is also demonstrated.

A Comprehensive Review on Optimal Location and Sizing of Reactive Power Compensation Using Hybrid-Based Approaches for Power Loss Reduction, Voltage Stability Improvement, Voltage Profile Enhancement and Loadability Enhancement

“…The loss sensitivity factor with respect to shunt compensation was computed using total real power losses in system, also known as exact loss formula [65][66]. This index is commonly used for determining optimal location of DG which can be found in [67][68][69][70]. For each bus, the sensitivity factor can be expressed as partial derivatives of total system real power losses with respect to the reactive power output of the shunt RPC as,…”

Optimasi Penempatan dan Kapasitas PLTS on grid Pada Sistem Distribusi Radial Menggunakan Metode Algoritma Genetika Multi Konstrain

“…Metode algoritma genetika dengan berbagai teknik dalam kasus pencarian lokasi dan kapasitas optimal pada pembangkit maupun peralatan listrik telah dilakukan oleh beberapa peneliti dunia. Metode algoritma genetika pada kasus pencarian lokasi dan kapasitas pembangkit tersebar (Distributed Generations) dapat menurunkan rugi-rugi daya dan meningkatkan indeks tegangan bus pada sistem distribusi yang lemah [20], [21]. Kombinasi Algoritma Genetika, PSO, dan WIPSO dapat meningkatkan kestabilan tegangan [22]- [24].…”

Direct search approach for multiple distributed generator allocation in radial distribution systems

“…Moradi, M Abedini [15] GA and PSO M. Padma Lalitha et al [16] Fuzzy and Clonal Selection algorithm Martin Garcia & Gil Mena [17] modified teachinglearning algorithm A.C. Rueda-Medina et al [18] Based on mixed-integer linear programming approach G. Celli, et al [19], Carpinelli et al [20] multi-objective programming and GA R.Srinivasa Rao, et al [21] Harmony Search algorithm Nara et al [22] Tabu search algorithm R.K. Singh et al [23], Teng et al[24] T.N. Shukla et al [25] Genetic algorithm M.F. Sohi et al [26] Bee colony algorithm (BCO)…”