Distributed Generation Planning for Loss and Cost Minimisation in Power Distribution Systems

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Copyright: Anwar, Adnan
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Abstract
In this thesis, a method based on a sensitivity analysis and quadratic curve-fitting technique for power loss reduction in a low-voltage distribution area is proposed. Loss sensitivity based method is used to determine some potential DG sites and least-square based curve-fitting technique is used to find out optimum DG capacity. Results obtained from the proposed method is justified using the exhaustive search method which is a computer program that searches for all alternatives by evaluating each individually. For determining the optimum generation capacity of multiple DG units, a new methodology based on an unbalanced multi-phase optimal power flow (UM-OPF) is presented in this thesis. During the formulation of the UM-OPF, an optimisation algorithm is developed in Matlab and the unbalanced multi-phase power flow is solved using the Electric Power Research Institute’s (EPRI) software OpenDSS. To ensure a global minimum loss profile, a swarm intelligence-based adaptive weight particle swarm optimisation (AW-PSO) algorithm is used which shows better convergence profile compared with basic PSO algorithm. Validation of the proposed methodologies is also conducted using an exhaustive search algorithm. The results obtained from the proposed methods show that significant loss reduction is possible using multiple optimum sized DG units. To determine the optimum DG capacity, with varying generation and load, a cost minimisation planning methodology is also proposed. During the planning process, different DG technologies (such as solar and wind) are considered. The results obtained from this methodology show better loss reduction profile compared to the peak load planning.
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Author(s)
Anwar, Adnan
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Publication Year
2012
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Thesis
Degree Type
Masters Thesis
UNSW Faculty
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