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Optimizing distributed generation parameters through economic feasibility assessment


Muttaqi, KM and Le, ADT and Aghaei, J and Mahboubi-Moghaddarn, E and Negnevitsky, M and Ledwich, G, Optimizing distributed generation parameters through economic feasibility assessment, Applied Energy, 165 pp. 893-903. ISSN 0306-2619 (2016) [Refereed Article]

Copyright Statement

Copyright 2016 Elsevier Ltd. All rights reserved.

DOI: doi:10.1016/j.apenergy.2016.01.006


To meet the fast growth of electricity demand, the traditional network solution tends to expand existing substations, build more new substations, and build transmission lines. Distributed Generation (DG) is posed as an alternative method for the network providers not only to accommodate the load increase and relieve network overload, but also to offer other additional technical and economic benefits. This paper addresses the issue of DG planning and has proposed a technique for optimizing the DG size and location to minimize the overall investment and operational cost of the system. The proposed optimization methodology assesses the compatibility of different generation schemes in terms of their cost factors that can be significantly contributed by a DG. The direct and indirect costs of power supply quality, reliability, energy loss, total power operation, and DG investment are used as key cost components of the DG siting and sizing strategy. The Particle Swarm Optimization (PSO) method is applied to obtain the optimal DG planning solutions. Finally, the proposed approach is tested on a distribution feeder of an Australian power network. Simulation results are presented to illustrate the feasibility and effectiveness of the proposed method.

Item Details

Item Type:Refereed Article
Keywords:distributed generation, optimal placement, optimal size, supply quality, supply reliability, energy losses
Research Division:Engineering
Research Group:Electrical engineering
Research Field:Electrical energy generation (incl. renewables, excl. photovoltaics)
Objective Division:Energy
Objective Group:Energy storage, distribution and supply
Objective Field:Energy services and utilities
UTAS Author:Le, ADT (Mr An Le)
UTAS Author:Negnevitsky, M (Professor Michael Negnevitsky)
ID Code:114440
Year Published:2016
Web of Science® Times Cited:33
Deposited By:Engineering
Deposited On:2017-02-15
Last Modified:2017-12-11

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