An efficient coupled GA and load flow algorithm for optimal placement and sizing of distributed generators

Makhol, Nadim; Alamuti, Mohsen Mohammadi; Nouri, Hassan

Abstract

A genetic algorithm is used in conjunction with an efficient load flow programme to determine the optimal locations and sizing of the predefined DGs within MATLAB software. The best location for the DGs and the sizing of the DGs are determined using the genetic algorithm. The branch electrical loss is considered as the objective function and the system total loss represent the fitness evaluation function for driving the GA. The load flow equations are considered as equality constraints and the equations of nodal voltage and branch capacity are considered as inequality constraints. The approach is tested on a 15 bus IEEE distribution feeder. © 2010 Inderscience Enterprises Ltd.

• Journal Article Type: Article
• Publication Date: Jan 1, 2010
• Journal: International Journal of Power and Energy Conversion
• Print ISSN: 1757-1154
• Electronic ISSN: 1757-1162
• Publisher: Inderscience
• Peer Reviewed: Peer Reviewed
• Volume: 2
• Issue: 1
• Pages: 59-77
• DOI: https://doi.org/10.1504/IJPEC.2010.030861
• Keywords: distribution networks, distributed generation, loss reduction, genetic algorithms, GAs, load flow, optimisation, generator placement, generator sizing, distributed generators, electrical loss
• Public URL: https://uwe-repository.worktribe.com/output/982330
• Publisher URL: http://dx.doi.org/10.1504/IJPEC.2010.030861