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Title: Optimal distribution feeder reconfiguration with optimal planning of distributed generation for loss reduction and voltage improvement using differential evolution algorithm

Authors: Ahmad B. Ghaweta; Yuan Liao

Addresses: Department of Electrical and Computer Engineering, University of Kentucky, Lexington, Kentucky 40506, USA ' Department of Electrical and Computer Engineering, University of Kentucky, Lexington, Kentucky 40506, USA

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.

Keywords: network reconfiguration; differential evolution algorithm; DEA; distributed generation; DG; sensitivity analysis; optimal size and location.

DOI: 10.1504/IJFSE.2019.104731

International Journal of Forensic Software Engineering, 2019 Vol.1 No.1, pp.73 - 90

Received: 13 Dec 2018
Accepted: 14 May 2019

Published online: 28 Jan 2020 *

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