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

摘要

In this thesis, a method based on a sensitivity analysis and quadratic curve-fittingtechnique for power loss reduction in a low-voltage distribution area is proposed.Loss sensitivity based method is used to determine some potential DG sites andleast-square based curve-fitting technique is used to find out optimum DG capacity.Results obtained from the proposed method is justified using the exhaustive searchmethod which is a computer program that searches for all alternatives by evaluatingeach individually. For determining the optimum generation capacity of multipleDG units, a new methodology based on an unbalanced multi-phase optimal powerflow (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-phasepower flow is solved using the Electric Power Research Institute’s (EPRI) softwareOpenDSS. To ensure a global minimum loss profile, a swarm intelligence-based adaptiveweight particle swarm optimisation (AW-PSO) algorithm is used which showsbetter convergence profile compared with basic PSO algorithm. Validation of theproposed methodologies is also conducted using an exhaustive search algorithm. Theresults obtained from the proposed methods show that significant loss reduction ispossible using multiple optimum sized DG units. To determine the optimum DGcapacity, with varying generation and load, a cost minimisation planning methodologyis also proposed. During the planning process, different DG technologies (suchas solar and wind) are considered. The results obtained from this methodology showbetter loss reduction profile compared to the peak load planning.