Optimal distribution feeder reconfiguration with optimal planning of distributed generation for loss reduction and voltage improvement using differential evolution algorithm. (28th January 2020)

• Record Type: Journal Article
• Authors: Ghaweta, Ahmad B.; Liao, Yuan
• Is Part Of: International journal of forensic software engineering. Volume 1:Number 1(2020)
• Page Start: 73
• Page End: 90
• Publication Date: 2020-01-28
• Subjects: network reconfiguration -- differential evolution algorithm -- DEA -- distributed generation -- DG -- sensitivity analysis -- optimal size and location
• Languages: English
• ISSNs: 1743-5099

Abstract

In the late years, there has been a noticeable influx of DGs onto the grid. This shift alters the manner in which electricity is being generated, transmitted, and managed. DGs conflicts have already risen between distribution systems designed for one-way power flow and DGs that want to force power flow in the opposite direction. Screening methods exist to avoid adverse impacts due to DGs, but this addressing the abundance of DGs interconnection requests and can result in higher overall costs if the resource is not fully integrated and located appropriately. A method to determine the optimal feeder reconfiguration and optimal allocation and size of DGs is proposed. The DG location is determined using the sensitivity of power losses. Then, the proposed differential evolution algorithm (DEA) is used to obtain the optimal size of the DG unit. The proposed algorithm is validated using the revised version of IEEE 33-bus radial distribution system.